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8,887,047 | 43 | 46 |
43. Non-transitory machine readable media that stores executable instructions, which, when executed by the one or more processing devices, are configured to cause the one or more processing devices to perform operations comprising: providing for display on a terminal a learning content input user interface configured to receive learning content; receiving learning content via the learning content input user interface and storing the received learning content in machine readable memory; providing for display on the terminal a framework user interface configured to receive a framework definition, wherein the framework definition defines an order of presentation to a learner with respect to learning content; receiving, independently of the received learning content, a framework definition via the framework user interface and storing the received framework definition in machine readable memory, wherein the framework definition specifies a presentation flow; receiving from the user a publishing instruction via a publishing user interface; at least partly in response to the received publishing instruction, accessing from machine readable memory the received learning content, the received framework definition, a received style set definition, and a received protocol selection, wherein the received style set definition is received via a style set user interface that enables the user to select from a plurality of protocols, including at least a version of HTML and a non-HTML protocol, which protocol is to be used in packaging rendered merged learning content and framework definition; merging the received learning content and the received framework definition; rendering the merged the received learning content and the received framework definition in accordance with the received style set definition; and packaging the rendered merged learning content and framework definition in accordance with the selected protocol to provide a published learning document.
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43. Non-transitory machine readable media that stores executable instructions, which, when executed by the one or more processing devices, are configured to cause the one or more processing devices to perform operations comprising: providing for display on a terminal a learning content input user interface configured to receive learning content; receiving learning content via the learning content input user interface and storing the received learning content in machine readable memory; providing for display on the terminal a framework user interface configured to receive a framework definition, wherein the framework definition defines an order of presentation to a learner with respect to learning content; receiving, independently of the received learning content, a framework definition via the framework user interface and storing the received framework definition in machine readable memory, wherein the framework definition specifies a presentation flow; receiving from the user a publishing instruction via a publishing user interface; at least partly in response to the received publishing instruction, accessing from machine readable memory the received learning content, the received framework definition, a received style set definition, and a received protocol selection, wherein the received style set definition is received via a style set user interface that enables the user to select from a plurality of protocols, including at least a version of HTML and a non-HTML protocol, which protocol is to be used in packaging rendered merged learning content and framework definition; merging the received learning content and the received framework definition; rendering the merged the received learning content and the received framework definition in accordance with the received style set definition; and packaging the rendered merged learning content and framework definition in accordance with the selected protocol to provide a published learning document. 46. The media as defined in claim 43 , wherein the framework user interface includes editable fields configured to receive a sequence specification, a framework name, a repeat specification, and a layer specification.
| 0.807965 |
9,569,424 | 1 | 4 |
1. A method for use with a voicemail transcription system that processes a voicemail message and generates a textual representation of at least a portion of the voicemail message, the method comprising: determining based, at least in part, on the textual representation of the at least a portion of the voicemail message, at least one emotion expressed in the voicemail message, wherein the determining comprises applying at least one emotion classifier to the textual representation of the at least a portion of the voicemail message; storing preference information for a user of a client device configured to receive voicemail transcriptions, wherein the preference information describes preferences for how the user of the client device wants emotion information associated with the received voicemail transcriptions to be conveyed to the user on the client device; and providing on the client device, in accordance with the stored preference information, an indication of the determined at least one emotion prior to displaying the textual representation of the at least a portion of the voicemail message on the client device, wherein providing an indication of the determined at least one emotion comprises displaying on the client device at least one graphical symbol representing the determined at least one emotion with a truncated version of the textual representation.
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1. A method for use with a voicemail transcription system that processes a voicemail message and generates a textual representation of at least a portion of the voicemail message, the method comprising: determining based, at least in part, on the textual representation of the at least a portion of the voicemail message, at least one emotion expressed in the voicemail message, wherein the determining comprises applying at least one emotion classifier to the textual representation of the at least a portion of the voicemail message; storing preference information for a user of a client device configured to receive voicemail transcriptions, wherein the preference information describes preferences for how the user of the client device wants emotion information associated with the received voicemail transcriptions to be conveyed to the user on the client device; and providing on the client device, in accordance with the stored preference information, an indication of the determined at least one emotion prior to displaying the textual representation of the at least a portion of the voicemail message on the client device, wherein providing an indication of the determined at least one emotion comprises displaying on the client device at least one graphical symbol representing the determined at least one emotion with a truncated version of the textual representation. 4. The method of claim 1 , wherein the at least one graphical symbol comprises an icon separated from but associated with the truncated version of the textual representation.
| 0.747093 |
7,765,212 | 14 | 15 |
14. A method comprising: employing a processor executing computer executable instructions stored on a computer-readable storage medium to implement the following acts: receiving a plurality of emails; clustering the plurality of emails into multiple clusters; performing key phrase extraction upon emails within at least one of the clusters; characterizing a topic with one or more extracted key phrases, the topic being a cohesive concept that is relevant to a user associated with the plurality of emails, the topic being at least one of: an activity in which the user participates, an event the user organized or attended, a person or group of people within an organization to which the user belongs, or a project; and automatically organizing non-email documents of the user stored in a first data store and the plurality of emails based upon the topics characterized with the one or more extracted key phrases from the emails, the non-email documents stored in the data store being organized by comparing content of each non-email document with the key phrases extracted from the multiple clusters of the plurality of emails for associating each non-email document with one or more of the topics, the non-email documents comprising at least one of: word processing documents, spreadsheets, presentation files, video files, audio files or digital images.
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14. A method comprising: employing a processor executing computer executable instructions stored on a computer-readable storage medium to implement the following acts: receiving a plurality of emails; clustering the plurality of emails into multiple clusters; performing key phrase extraction upon emails within at least one of the clusters; characterizing a topic with one or more extracted key phrases, the topic being a cohesive concept that is relevant to a user associated with the plurality of emails, the topic being at least one of: an activity in which the user participates, an event the user organized or attended, a person or group of people within an organization to which the user belongs, or a project; and automatically organizing non-email documents of the user stored in a first data store and the plurality of emails based upon the topics characterized with the one or more extracted key phrases from the emails, the non-email documents stored in the data store being organized by comparing content of each non-email document with the key phrases extracted from the multiple clusters of the plurality of emails for associating each non-email document with one or more of the topics, the non-email documents comprising at least one of: word processing documents, spreadsheets, presentation files, video files, audio files or digital images. 15. The method of claim 14 , further comprising supplying tokens to each email within the plurality of emails corresponding to deliverers of the emails and recipients of the emails, the tokens employed to refine a topic and to separate topics that are lexically similar.
| 0.761905 |
8,560,853 | 17 | 18 |
17. The system as recited in claim 15 , wherein the digital signing policy further defines a sub-set of a discrete part as protected such that the digital signature is invalidated when the sub-set of the discrete part is altered.
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17. The system as recited in claim 15 , wherein the digital signing policy further defines a sub-set of a discrete part as protected such that the digital signature is invalidated when the sub-set of the discrete part is altered. 18. The system as recited in claim 17 , wherein the digital signature is applied to each discrete part of the sub-set based on the digital signing policy such that altering the discrete part invalidates the digital signature.
| 0.5 |
8,615,708 | 10 | 18 |
10. One or more non-transitory computer-readable storage media storing instructions that, when executed by one or more computing devices, causes the one or more computing devices to perform a method comprising: parsing a meta-language style sheet comprising at least one meta-language style sheet variable declaration and at least one meta-language style sheet rule definition referencing the at least one meta-language style sheet variable; generating, based on the parsing, an intermediate representation of the meta-language style sheet variable declaration and an intermediate representation of the meta-language style sheet rule definition; generating executable code based at least on both the intermediate representation of the meta-language style sheet variable declaration and the intermediate representation of the meta-language style sheet rule definition; executing the executable code to produce a web browser style sheet; and updating display of a web page using the web browser style sheet.
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10. One or more non-transitory computer-readable storage media storing instructions that, when executed by one or more computing devices, causes the one or more computing devices to perform a method comprising: parsing a meta-language style sheet comprising at least one meta-language style sheet variable declaration and at least one meta-language style sheet rule definition referencing the at least one meta-language style sheet variable; generating, based on the parsing, an intermediate representation of the meta-language style sheet variable declaration and an intermediate representation of the meta-language style sheet rule definition; generating executable code based at least on both the intermediate representation of the meta-language style sheet variable declaration and the intermediate representation of the meta-language style sheet rule definition; executing the executable code to produce a web browser style sheet; and updating display of a web page using the web browser style sheet. 18. The one or more non-transitory storage media of claim 10 , the method further comprising: obtaining a plurality of new values for the meta-language style sheet variable; and in response to obtaining each new value, performing the operations of: executing the executable code using the each new value to produce a web browser style sheet that reflects the each new value, and updating display of a web page using the web browser style sheet that reflects the each new value.
| 0.5 |
8,660,836 | 1 | 17 |
1. A method, comprising: optimizing one or more parameters of a natural language processing system so as to improve a measure of quality of an output of the natural language processing system for a first type of data processed by the natural language processing system while maintaining a given measure of quality of an output of the natural language processing system for a second type of data processed by the natural language processing system, wherein the optimizing comprises computing a conditional value at risk metric.
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1. A method, comprising: optimizing one or more parameters of a natural language processing system so as to improve a measure of quality of an output of the natural language processing system for a first type of data processed by the natural language processing system while maintaining a given measure of quality of an output of the natural language processing system for a second type of data processed by the natural language processing system, wherein the optimizing comprises computing a conditional value at risk metric. 17. The method of claim 1 , wherein the natural language processing system comprises a machine translation system, and the output is a translation of an input document into a different language.
| 0.780543 |
7,991,790 | 15 | 19 |
15. The method of claim 1 , further comprising: associating the document with one or more of a plurality of document types chosen from a list of document types, each document type describing one or more characteristics associated with the document.
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15. The method of claim 1 , further comprising: associating the document with one or more of a plurality of document types chosen from a list of document types, each document type describing one or more characteristics associated with the document. 19. The method of claim 15 , wherein a list of properties is stored in association with a document type, each property of the list of properties being a description of one or more characteristics associated with a particular document type.
| 0.523904 |
8,538,976 | 7 | 10 |
7. A non-transitory computer readable storage medium storing an application, which, when executed on a processor, performs an operation for integrating a physical query statement in a data abstraction model comprising a first plurality of logical fields used to expose an underlying physical database, the operation comprising: parsing the physical query statement to identify a plurality of output fields specified by the physical query statement; upon determining that a first output field of the identified plurality of output fields has a corresponding logical field, of the first plurality of logical fields, mapping the first output field of the physical query statement to the corresponding logical field provided by the data abstraction model; upon determining that a second output field of the identified plurality of output fields does not have any corresponding logical field, generating a second logical field mapping to the second output field, wherein the second logical field includes an access method mapping the second logical field to the second output field; upon determining that a naming conflict exists between the second output field and one of the plurality of logical fields: determining a second name to assign to the second logical field to resolve the determined naming conflict, wherein the second name is different from a first name; and adding the second logical field having the second name to the plurality of logical fields, wherein the naming conflict is resolved without having to replace any logical field in the data abstraction model; and upon determining that no naming conflict exists between the second output field and one of the plurality of logical fields: determining a first name to assign to the second logical field; and adding the second logical field having the first name to the plurality of logical fields.
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7. A non-transitory computer readable storage medium storing an application, which, when executed on a processor, performs an operation for integrating a physical query statement in a data abstraction model comprising a first plurality of logical fields used to expose an underlying physical database, the operation comprising: parsing the physical query statement to identify a plurality of output fields specified by the physical query statement; upon determining that a first output field of the identified plurality of output fields has a corresponding logical field, of the first plurality of logical fields, mapping the first output field of the physical query statement to the corresponding logical field provided by the data abstraction model; upon determining that a second output field of the identified plurality of output fields does not have any corresponding logical field, generating a second logical field mapping to the second output field, wherein the second logical field includes an access method mapping the second logical field to the second output field; upon determining that a naming conflict exists between the second output field and one of the plurality of logical fields: determining a second name to assign to the second logical field to resolve the determined naming conflict, wherein the second name is different from a first name; and adding the second logical field having the second name to the plurality of logical fields, wherein the naming conflict is resolved without having to replace any logical field in the data abstraction model; and upon determining that no naming conflict exists between the second output field and one of the plurality of logical fields: determining a first name to assign to the second logical field; and adding the second logical field having the first name to the plurality of logical fields. 10. The non-transitory computer readable storage medium of claim 7 , wherein the operation further comprises, providing a query interface to compose abstract queries, wherein the query interface allows a user to select between composing an abstract query from a data abstraction model comprising the first plurality of logical fields and a data abstraction model comprising the plurality of logical fields, the first logical field, and the second logical field.
| 0.5 |
9,177,084 | 19 | 22 |
19. A system comprising: one or more computers operable to perform operations comprising: receiving a conceptual representation of a building including one or more user-defined floor levels and multiple surfaces defining geometrical volumetric spaces; and responsive to a request to generate an analytical energy model, automatically generating the analytical energy model by: deriving geometric information from the conceptual representation; based on the geometric information, defining one or more mass volumes; algorithmically assigning one or more surface types to mass volume surfaces based, at least in part, on surface type definitions, a number of space adjacencies and the geometric information, associated with a corresponding mass volume surface, the surface type definitions specifying a material construction of a corresponding surface type; defining one or more thermal mass zones based on the determined one or more mass volumes and a corresponding number of user-defined floor levels; deriving, using a model generator, thermal properties of the one or more thermal mass zones; wherein the deriving is based on the geometrical columetric spaces, the one or more surface types assigned to the mass volume surfaces, and corresponding material construction; and combining the defined one or more thermal mass zones, the derived thermal properties, and predefined analytical energy model parameters to generate the analytical energy model.
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19. A system comprising: one or more computers operable to perform operations comprising: receiving a conceptual representation of a building including one or more user-defined floor levels and multiple surfaces defining geometrical volumetric spaces; and responsive to a request to generate an analytical energy model, automatically generating the analytical energy model by: deriving geometric information from the conceptual representation; based on the geometric information, defining one or more mass volumes; algorithmically assigning one or more surface types to mass volume surfaces based, at least in part, on surface type definitions, a number of space adjacencies and the geometric information, associated with a corresponding mass volume surface, the surface type definitions specifying a material construction of a corresponding surface type; defining one or more thermal mass zones based on the determined one or more mass volumes and a corresponding number of user-defined floor levels; deriving, using a model generator, thermal properties of the one or more thermal mass zones; wherein the deriving is based on the geometrical columetric spaces, the one or more surface types assigned to the mass volume surfaces, and corresponding material construction; and combining the defined one or more thermal mass zones, the derived thermal properties, and predefined analytical energy model parameters to generate the analytical energy model. 22. The system of claim 19 , the operations further comprising, for assigned surface types, associating the material construction of the surface type with a corresponding portion of an exterior surface in the conceptual representation.
| 0.729885 |
8,355,578 | 1 | 7 |
1. An image processing apparatus, comprising: an area division unit configured to divide an image of a page into a plurality of areas; an attribute information addition unit configured to add, to the plurality of divided areas, attribute information depending on an attribute determination of each of the areas so that when one of the areas is determined to be a caption area, caption attribute information is added to the caption area, when another of the areas is determined to be a body text area, body text attribute information is added to the body text area, and when another of the areas is determined to be an object area, object attribute information is added to the object area; a character recognition unit configured to perform a character recognition processing on a caption area and a body text area; and a metadata processing unit configured to associate metadata with an object area accompanied by a caption area, wherein the metadata processing unit comprises: a first extraction unit configured to extract, from the result of the character recognition processing on the caption area, an anchor expression composed of a predetermined character string and a caption expression composed of a character string other than the anchor expression; a first determination unit configured to determine whether there are a plurality of object areas accompanied by caption areas including an identical anchor expression; a second extraction unit configured to extract, from the result of the character recognition processing on the body text area, an explanatory text including the anchor expression; a first association unit configured to associate, in the case that the first determination unit determines that there is one object area accompanied by a caption area including the identical anchor expression, the determined one object area with metadata obtained from the explanatory text extracted by the second extraction unit; a similarity degree calculation unit configured to calculate, in the case that the first determination unit determines that there are a plurality of object areas accompanied by caption areas including the identical anchor expression, similarity degrees between caption expressions of the respective caption areas including the identical anchor expression and the explanatory text including the anchor expression extracted by the second extraction unit, respectively; and a second association unit configured to determine, based on the similarity degrees calculated by the similarity degree calculation unit, the explanatory texts that are optimal for the respective plurality of object areas accompanied by caption areas including the identical anchor expression and to associate metadata obtained from the determined optimal explanatory texts to the respective plurality of object areas accompanied by caption areas including the identical anchor expression.
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1. An image processing apparatus, comprising: an area division unit configured to divide an image of a page into a plurality of areas; an attribute information addition unit configured to add, to the plurality of divided areas, attribute information depending on an attribute determination of each of the areas so that when one of the areas is determined to be a caption area, caption attribute information is added to the caption area, when another of the areas is determined to be a body text area, body text attribute information is added to the body text area, and when another of the areas is determined to be an object area, object attribute information is added to the object area; a character recognition unit configured to perform a character recognition processing on a caption area and a body text area; and a metadata processing unit configured to associate metadata with an object area accompanied by a caption area, wherein the metadata processing unit comprises: a first extraction unit configured to extract, from the result of the character recognition processing on the caption area, an anchor expression composed of a predetermined character string and a caption expression composed of a character string other than the anchor expression; a first determination unit configured to determine whether there are a plurality of object areas accompanied by caption areas including an identical anchor expression; a second extraction unit configured to extract, from the result of the character recognition processing on the body text area, an explanatory text including the anchor expression; a first association unit configured to associate, in the case that the first determination unit determines that there is one object area accompanied by a caption area including the identical anchor expression, the determined one object area with metadata obtained from the explanatory text extracted by the second extraction unit; a similarity degree calculation unit configured to calculate, in the case that the first determination unit determines that there are a plurality of object areas accompanied by caption areas including the identical anchor expression, similarity degrees between caption expressions of the respective caption areas including the identical anchor expression and the explanatory text including the anchor expression extracted by the second extraction unit, respectively; and a second association unit configured to determine, based on the similarity degrees calculated by the similarity degree calculation unit, the explanatory texts that are optimal for the respective plurality of object areas accompanied by caption areas including the identical anchor expression and to associate metadata obtained from the determined optimal explanatory texts to the respective plurality of object areas accompanied by caption areas including the identical anchor expression. 7. The image processing apparatus according to claim 1 , wherein the image processing apparatus further comprises a third association unit configured to associate the caption expression extracted by the first extraction unit as metadata with an object area accompanied by a caption area including the caption expression.
| 0.855072 |
9,128,933 | 21 | 22 |
21. A computing device comprising: one or more processors; and one or more computer storage media having stored thereon multiple instructions that, responsive to execution by the one or more processors, cause the one or more processors to perform acts comprising: receiving a named entity input; identifying a target sense for which the named entity input is to be extracted from a set of documents; and generating, based at least in part on both the named entity input and the set of documents, an extraction complexity feature that indicates how difficult it is deemed to be to identify the named entity input for the target sense in the set of documents, the generating including building an undirected graph based on the named entity input and the set of documents and looking for contexts in the undirected graph that are related to the target sense, the undirected graph including multiple vertices and multiple edges.
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21. A computing device comprising: one or more processors; and one or more computer storage media having stored thereon multiple instructions that, responsive to execution by the one or more processors, cause the one or more processors to perform acts comprising: receiving a named entity input; identifying a target sense for which the named entity input is to be extracted from a set of documents; and generating, based at least in part on both the named entity input and the set of documents, an extraction complexity feature that indicates how difficult it is deemed to be to identify the named entity input for the target sense in the set of documents, the generating including building an undirected graph based on the named entity input and the set of documents and looking for contexts in the undirected graph that are related to the target sense, the undirected graph including multiple vertices and multiple edges. 22. A computing device as recited in claim 21 , the acts further comprising providing the extraction complexity feature to a named entity recognition module that identifies the named entity input in the set of documents based at least in part on the extraction complexity feature.
| 0.551282 |
9,786,281 | 4 | 10 |
4. A device comprising: a profile building component in communication with an electronic data store; a sensor configured to detect presence of a user independent of a direction of the user's gaze and without detecting physical contact between the user and the device; and a speech recognition component; wherein the profile building component is configured to: receive, from the sensor, an indication that presence of the user was detected; begin to listen for utterances from the user in response to receiving the indication; receive a first voice signal corresponding to a first utterance of a user; determine an identity of the user using the first voice signal; process the first voice signal to determine user information and a word sequence that indicates that a second utterance corresponding to a language characteristic is likely to be uttered by a second user different than the user at a time after a current time; store the user information in a user profile associated with the identity of the user; and select a second user acoustic model corresponding to the language characteristic for performing speech recognition.
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4. A device comprising: a profile building component in communication with an electronic data store; a sensor configured to detect presence of a user independent of a direction of the user's gaze and without detecting physical contact between the user and the device; and a speech recognition component; wherein the profile building component is configured to: receive, from the sensor, an indication that presence of the user was detected; begin to listen for utterances from the user in response to receiving the indication; receive a first voice signal corresponding to a first utterance of a user; determine an identity of the user using the first voice signal; process the first voice signal to determine user information and a word sequence that indicates that a second utterance corresponding to a language characteristic is likely to be uttered by a second user different than the user at a time after a current time; store the user information in a user profile associated with the identity of the user; and select a second user acoustic model corresponding to the language characteristic for performing speech recognition. 10. The device of claim 4 , wherein at least one of the profile building component or the speech recognition component is further configured to: perform speech recognition on the first voice signal to obtain speech recognition results; determine acoustic model information using at least one of the first voice signal and the user information; and determine language model information using at least one of the speech recognition results and the user information.
| 0.521694 |
9,886,946 | 1 | 5 |
1. A computer-implemented method comprising: receiving, by an automated speech recognizer (ASR) system that includes (i) a context selector, (ii) a language model biaser, (iii) an ASR, (iv) a particular language model, and (v) a previously biased language model, audio data corresponding to an utterance of a user; determining, by the context selector of the ASR system, that the user is likely no longer within a particular context that is associated the previously biased language model; in response to determining that the user is likely no longer within a particular context that is associated with the previously biased language model, selecting, by the language model biaser of the ASR system, the particular language model for use in transcribing utterances; after selecting the baseline language model, generating, by the ASR of the ASR system, a transcription of the utterance using the particular language model; and providing a representation of the transcription for output.
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1. A computer-implemented method comprising: receiving, by an automated speech recognizer (ASR) system that includes (i) a context selector, (ii) a language model biaser, (iii) an ASR, (iv) a particular language model, and (v) a previously biased language model, audio data corresponding to an utterance of a user; determining, by the context selector of the ASR system, that the user is likely no longer within a particular context that is associated the previously biased language model; in response to determining that the user is likely no longer within a particular context that is associated with the previously biased language model, selecting, by the language model biaser of the ASR system, the particular language model for use in transcribing utterances; after selecting the baseline language model, generating, by the ASR of the ASR system, a transcription of the utterance using the particular language model; and providing a representation of the transcription for output. 5. The method of claim 1 , wherein determining that the user is likely no longer within the particular context comprises determining that a confidence score associated with the user and the particular context does not satisfy a threshold.
| 0.5 |
8,001,519 | 1 | 4 |
1. A software development tool implemented as a program for controlling computing equipment, wherein said program is stored in a non-transitory storage medium, said software development tool comprising: a model development interface implemented in a program that controls computing equipment, wherein said program is stored in a non-transitory storage medium, wherein said model development interface is configured to permit a developer to graphically design at least one software model; an aspect design tool implemented as a program for controlling computing equipment, wherein said program is stored in a non-transitory storage medium, wherein said aspect design is for the model development interface configured to permit a user to specify at least one aspect to be applied to a model of the model development interface; a model transformation engine implemented as a program for controlling computing equipment, wherein said program is stored in a non-transitory storage medium, wherein said aspect design is configured to transform a model of the model development interface having at least one aspect defined via the aspect design tool into automatically generated aspect code integrated with base language code; and an invocation specification tool implemented as a program for controlling computing equipment, wherein said program is stored in a non-transitory storage medium, wherein said invocation specification tool is configured to graphically indicate when the aspect specified by the aspect design tool is to be invoked relative to when a model object to which the aspect is integrated is to be invoked, wherein the model transformation engine interweaves the base code and the aspect code based upon selections made via the invocation selection tool.
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1. A software development tool implemented as a program for controlling computing equipment, wherein said program is stored in a non-transitory storage medium, said software development tool comprising: a model development interface implemented in a program that controls computing equipment, wherein said program is stored in a non-transitory storage medium, wherein said model development interface is configured to permit a developer to graphically design at least one software model; an aspect design tool implemented as a program for controlling computing equipment, wherein said program is stored in a non-transitory storage medium, wherein said aspect design is for the model development interface configured to permit a user to specify at least one aspect to be applied to a model of the model development interface; a model transformation engine implemented as a program for controlling computing equipment, wherein said program is stored in a non-transitory storage medium, wherein said aspect design is configured to transform a model of the model development interface having at least one aspect defined via the aspect design tool into automatically generated aspect code integrated with base language code; and an invocation specification tool implemented as a program for controlling computing equipment, wherein said program is stored in a non-transitory storage medium, wherein said invocation specification tool is configured to graphically indicate when the aspect specified by the aspect design tool is to be invoked relative to when a model object to which the aspect is integrated is to be invoked, wherein the model transformation engine interweaves the base code and the aspect code based upon selections made via the invocation selection tool. 4. The software development tool of claim 1 , further comprising: an aspect library stored in a non-transitory storage medium, said aspect library comprising a plurality of stored, previously generated, project independent aspects, wherein said aspect design tool is able to select any of the plurality of stored aspects and integrate the selected aspect to the model.
| 0.505376 |
7,580,946 | 1 | 23 |
1. A method for automatically generating data-service-execution flows, based on metadata objects, for executing data services from heterogeneous data sources, the method comprising the steps of: (a) providing a smart integration engine, having at least one smart integration server with a solution resolver residing therein, configured to receive dynamic service schema (DSS) requests, said DSS requests each having a DSS metadata input and a DSS metadata output, for executing the data services from the heterogeneous data sources, wherein said solution resolver has access to data assets stored in a metadata repository; and (b) generating solution flows of said DSS requests based on metadata criteria and on said data assets, each said solution flow utilizes a plurality of nodes that are inter-related such that a node output of a preceding node serves as a node input of a subsequent node for producing said DSS metadata output, a portion of said plurality of nodes to be executed subsequent to said step of generating said solution flows according to an optimized node sequence determined by said solution resolver solely during said step of generating said solution flows.
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1. A method for automatically generating data-service-execution flows, based on metadata objects, for executing data services from heterogeneous data sources, the method comprising the steps of: (a) providing a smart integration engine, having at least one smart integration server with a solution resolver residing therein, configured to receive dynamic service schema (DSS) requests, said DSS requests each having a DSS metadata input and a DSS metadata output, for executing the data services from the heterogeneous data sources, wherein said solution resolver has access to data assets stored in a metadata repository; and (b) generating solution flows of said DSS requests based on metadata criteria and on said data assets, each said solution flow utilizes a plurality of nodes that are inter-related such that a node output of a preceding node serves as a node input of a subsequent node for producing said DSS metadata output, a portion of said plurality of nodes to be executed subsequent to said step of generating said solution flows according to an optimized node sequence determined by said solution resolver solely during said step of generating said solution flows. 23. The method of claim 1 , wherein said metadata repository includes technical metadata and business metadata, wherein said technical metadata provide data-source information for executing said DSS requests, and wherein said business metadata represent said technical metadata in business terms.
| 0.625316 |
9,443,249 | 1 | 7 |
1. A computer-implemented method comprising: selecting one or more users that are connected to a particular user by way of a social networking service or by a relationship described by a graph stored in a database, wherein each user interacts with one or more services; obtaining, for each of the selected users, interest data indicating past interactions of the selected user that are associated with a particular topic and that are of different interaction types; selecting a model that is used for generating the interest score of the particular user that reflects the particular user's predicted interest in the particular topic from a set of two or more models each corresponding to a different topic, wherein the interest score of the particular user is generated based at least on the interaction types of the past interactions indicated by the interest data of the selected users as being associated with the particular topic; applying the interest data of the selected users for the particular topic to the model to generate the interest score of the particular user for the particular topic; receiving a search query associated with the particular topic from the particular user; determining, for each search result that is responsive to the search query, a search query score that reflects a likelihood that the search result corresponds to the search query; ranking the search results based on the interest score of the particular user for the particular topic and the search query scores; and providing a search results page based on the ranking of the search results.
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1. A computer-implemented method comprising: selecting one or more users that are connected to a particular user by way of a social networking service or by a relationship described by a graph stored in a database, wherein each user interacts with one or more services; obtaining, for each of the selected users, interest data indicating past interactions of the selected user that are associated with a particular topic and that are of different interaction types; selecting a model that is used for generating the interest score of the particular user that reflects the particular user's predicted interest in the particular topic from a set of two or more models each corresponding to a different topic, wherein the interest score of the particular user is generated based at least on the interaction types of the past interactions indicated by the interest data of the selected users as being associated with the particular topic; applying the interest data of the selected users for the particular topic to the model to generate the interest score of the particular user for the particular topic; receiving a search query associated with the particular topic from the particular user; determining, for each search result that is responsive to the search query, a search query score that reflects a likelihood that the search result corresponds to the search query; ranking the search results based on the interest score of the particular user for the particular topic and the search query scores; and providing a search results page based on the ranking of the search results. 7. The method of claim 1 , further comprising: receiving one or more posts, each of the posts comprising digital content; adjusting a score associated with at least one of the one or more posts based on the interest score of the particular user; and providing the one or more posts to the particular user based on the respective scores of the one or more posts.
| 0.5 |
9,086,891 | 14 | 15 |
14. The non-transitory computer-readable medium of claim 9 , wherein the selecting comprises selecting a plurality of profiles.
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14. The non-transitory computer-readable medium of claim 9 , wherein the selecting comprises selecting a plurality of profiles. 15. The non-transitory computer-readable medium of claim 14 , wherein a priority of each one of the plurality of different profiles that is applied is based on an order that the each one of the plurality of different profiles is listed.
| 0.5 |
9,467,436 | 7 | 15 |
7. A computer system configured to validate CAPTCHAs, the computer system comprising: one or more hardware processors programmed, via executable code instructions, to implement: CAPTCHA generator module configured to: determine a phrase of words that, when perceived together, comprises one or more meanings associated with the phrase of words that assist human perception of the phrase of words, and further comprises a deviation from a correct presentation of at least one word, wherein the likelihood of human error is determined at least in part by adjusting a level of change to the deviation of the word; and generate a CAPTCHA user interface depicting: the phrase of words including the deviation from the correct presentation, wherein the deviation is configured for human perception as to the correct presentation of the deviation based on context of the deviation within the phrase of words, and at least two options associated with respective two or more correct presentations for the deviation, wherein at least one of the options is associated with the correct presentation of the deviation within the phrase of words and at least one of the options is associated with an incorrect presentation of the deviation within the phrase of words; a human validator module configured to: receive a selection of at least one of the options associated with the CAPTCHA user interface; determine whether the selected option is the option associated with the correct presentation of the deviation within the phrase of words; generate an indication of whether the selected option was provided by a human based on said determination; and transmit the generated indication.
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7. A computer system configured to validate CAPTCHAs, the computer system comprising: one or more hardware processors programmed, via executable code instructions, to implement: CAPTCHA generator module configured to: determine a phrase of words that, when perceived together, comprises one or more meanings associated with the phrase of words that assist human perception of the phrase of words, and further comprises a deviation from a correct presentation of at least one word, wherein the likelihood of human error is determined at least in part by adjusting a level of change to the deviation of the word; and generate a CAPTCHA user interface depicting: the phrase of words including the deviation from the correct presentation, wherein the deviation is configured for human perception as to the correct presentation of the deviation based on context of the deviation within the phrase of words, and at least two options associated with respective two or more correct presentations for the deviation, wherein at least one of the options is associated with the correct presentation of the deviation within the phrase of words and at least one of the options is associated with an incorrect presentation of the deviation within the phrase of words; a human validator module configured to: receive a selection of at least one of the options associated with the CAPTCHA user interface; determine whether the selected option is the option associated with the correct presentation of the deviation within the phrase of words; generate an indication of whether the selected option was provided by a human based on said determination; and transmit the generated indication. 15. The computer system of claim 7 , wherein adjusting the level of change comprises tying the CAPTCHA to one of linguistic, cultural or regional characteristics of intended end users.
| 0.610169 |
7,483,870 | 3 | 4 |
3. A method as described in claim 1 wherein said data change includes at least one changed attribute and all other attributes of said first data type.
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3. A method as described in claim 1 wherein said data change includes at least one changed attribute and all other attributes of said first data type. 4. A method as described in claim 3 wherein, if said additional attributes of said third data type are included within said all other attributes of said first data type, said join engine peer forms said modified attribute set directly from said data change.
| 0.5 |
7,660,793 | 16 | 17 |
16. A system for processing data, the system comprising: a main processor; a processing device other than the main processor; a data store of unstructured data in communication with the main processor and the processing device; a data store of structured data in communication with the main processor and the processing device, the structured data comprising metadata about at least a portion of the unstructured data; wherein the main processor is configured to (1) receive a query, the query comprising at least one term for searching within unstructured data, (2) process at least a portion of the query against the structured data in the data store of structured data to identify a subset of unstructured data in the data store of unstructured data, and (3) request that the subset of unstructured data be delivered to the processing device; and wherein the processing device is configured to (1) receive the subset of unstructured data and (2) search the received subset of unstructured data based on the at least one query term to determine whether any of the unstructured data within the received subset of unstructured data matches the at least one query term.
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16. A system for processing data, the system comprising: a main processor; a processing device other than the main processor; a data store of unstructured data in communication with the main processor and the processing device; a data store of structured data in communication with the main processor and the processing device, the structured data comprising metadata about at least a portion of the unstructured data; wherein the main processor is configured to (1) receive a query, the query comprising at least one term for searching within unstructured data, (2) process at least a portion of the query against the structured data in the data store of structured data to identify a subset of unstructured data in the data store of unstructured data, and (3) request that the subset of unstructured data be delivered to the processing device; and wherein the processing device is configured to (1) receive the subset of unstructured data and (2) search the received subset of unstructured data based on the at least one query term to determine whether any of the unstructured data within the received subset of unstructured data matches the at least one query term. 17. The system of claim 16 wherein the processing device comprises a coprocessor.
| 0.872642 |
9,710,786 | 1 | 4 |
1. A system for a knowledge management system comprising: a processor; and a memory that contains instructions that are readable by the processor and cause the processor to: receive a query that indicates at least one legal topic from a hierarchy of legal topics; provide a response to the query indicating each work-product document and each case law document that matches the at least one legal topic, wherein the processor is operable to, prior to providing the response: retrieve each work-product document that matches the at least one legal topic from a first database; and retrieve each case law document that matches the at least one legal topic from a second database; determine a validity status of at least one case cited within each work-product document, resulting in a validity indicator, the validity indicator for each work-product document indicating the validity status of the at least one case; indicate, in the response provided to the query, a reliability of each work-product document using the validity indicator and a rating indicator for each work-product document, the rating indicator for each work-product document indicating a user rating of each work-product document based on previous users of each work-product document; index each work-product document according to the hierarchy of legal topics based on at least one legal citation and a set of text; index each case law document according to the hierarchy of legal topics; receive a second query for a particular case law document; and provide a second response to the second query indicating each work-product document which includes at least one legal citation associated with the particular case law document according to a depth-of-treatment value, the depth-of-treatment value indicates a degree to which each work-product document evaluates the particular case law document.
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1. A system for a knowledge management system comprising: a processor; and a memory that contains instructions that are readable by the processor and cause the processor to: receive a query that indicates at least one legal topic from a hierarchy of legal topics; provide a response to the query indicating each work-product document and each case law document that matches the at least one legal topic, wherein the processor is operable to, prior to providing the response: retrieve each work-product document that matches the at least one legal topic from a first database; and retrieve each case law document that matches the at least one legal topic from a second database; determine a validity status of at least one case cited within each work-product document, resulting in a validity indicator, the validity indicator for each work-product document indicating the validity status of the at least one case; indicate, in the response provided to the query, a reliability of each work-product document using the validity indicator and a rating indicator for each work-product document, the rating indicator for each work-product document indicating a user rating of each work-product document based on previous users of each work-product document; index each work-product document according to the hierarchy of legal topics based on at least one legal citation and a set of text; index each case law document according to the hierarchy of legal topics; receive a second query for a particular case law document; and provide a second response to the second query indicating each work-product document which includes at least one legal citation associated with the particular case law document according to a depth-of-treatment value, the depth-of-treatment value indicates a degree to which each work-product document evaluates the particular case law document. 4. The system recited in claim 1 , wherein the degree to which each work-product document is evaluated is based on at least a count that each legal citation references the particular case law document.
| 0.711207 |
9,934,658 | 8 | 9 |
8. A building safety system, comprising: a safety control panel; and a plurality of building safety devices in communication with the safety control panel, the building safety system configured to: receive a voice input; receive voice data produced by a speech recognition process performed on the voice input; determine a location of an individual having transmitted the voice input; determine a response to the voice input based on the voice data; and produce the response, wherein the response is directional information, to a destination location, relative to the location of the individual having transmitted the voice input, and wherein the directional information is to a pull station.
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8. A building safety system, comprising: a safety control panel; and a plurality of building safety devices in communication with the safety control panel, the building safety system configured to: receive a voice input; receive voice data produced by a speech recognition process performed on the voice input; determine a location of an individual having transmitted the voice input; determine a response to the voice input based on the voice data; and produce the response, wherein the response is directional information, to a destination location, relative to the location of the individual having transmitted the voice input, and wherein the directional information is to a pull station. 9. The building safety system of claim 8 , wherein the building safety system stores a plurality of voice patterns and is further configured to determine whether the voice data corresponds to an authorized user based on the voice patterns, and wherein the building safety system produces the response when the voice data is determined to correspond to the authorized user.
| 0.541872 |
8,760,389 | 2 | 3 |
2. The method according to claim 1 , further comprising: switching a designation of the first recognition mode from active to inactive and a designation of the second recognition mode from inactive to active in response to the selected character candidate being one of the character candidates obtained in said second recognition mode.
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2. The method according to claim 1 , further comprising: switching a designation of the first recognition mode from active to inactive and a designation of the second recognition mode from inactive to active in response to the selected character candidate being one of the character candidates obtained in said second recognition mode. 3. The method according to claim 2 , further comprising: updating said displaying of said character candidates in response to said switching.
| 0.5 |
7,770,110 | 1 | 5 |
1. A computer-implemented method for transforming an XML file into an add-in function for use in a spreadsheet application comprising: scanning an add-in XML file for an instruction; determining an interface XML file to be exposed by the instruction; accepting the interface XML file from a COM server; determining if the instruction comprises a function qualifier; wherein the function qualifier modifies a function specification in the interface XML file; applying the function qualifier to the function specification; converting the function specification to an intermediate function; applying an implementation specifier to the intermediate function, wherein the implementation specifier overrides the default implementation of the interface XML file; converting the intermediate function to an add-in function; and transmitting the add-in function to the spreadsheet application for processing.
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1. A computer-implemented method for transforming an XML file into an add-in function for use in a spreadsheet application comprising: scanning an add-in XML file for an instruction; determining an interface XML file to be exposed by the instruction; accepting the interface XML file from a COM server; determining if the instruction comprises a function qualifier; wherein the function qualifier modifies a function specification in the interface XML file; applying the function qualifier to the function specification; converting the function specification to an intermediate function; applying an implementation specifier to the intermediate function, wherein the implementation specifier overrides the default implementation of the interface XML file; converting the intermediate function to an add-in function; and transmitting the add-in function to the spreadsheet application for processing. 5. The computer-implemented method of claim 1 , wherein applying the implementation specifier to the intermediate function further comprises the steps of: generating an empty form add-in function; transferring at least one attribute from the intermediate function to the form add-in function, wherein the attribute comprises all elements in the intermediate function other than an implementation and return value attribute of the intermediate function; determining if the instruction comprises an implementation specifier for the function specification; formatting implementation and return value attributes of the form add-in function based on the implementation specifier in the instruction; and converting the form add-in function to the add-in function.
| 0.545072 |
8,655,913 | 17 | 18 |
17. The system of claim 16 , wherein the relative location module is further configured to: if no exact match of at least one attribute to at least one element in the DOM tree structure is determined by the DOM attributes search module: perform a search of the DOM tree structure according to a prefix search query based on at least one attribute; perform a search of the DOM tree structure according to a suffix search query based on at least one attribute; and perform a search of the DOM tree structure according to a wildcard matching criteria based on at least one attribute.
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17. The system of claim 16 , wherein the relative location module is further configured to: if no exact match of at least one attribute to at least one element in the DOM tree structure is determined by the DOM attributes search module: perform a search of the DOM tree structure according to a prefix search query based on at least one attribute; perform a search of the DOM tree structure according to a suffix search query based on at least one attribute; and perform a search of the DOM tree structure according to a wildcard matching criteria based on at least one attribute. 18. The system of claim 17 , wherein the relative location module is further configured to: determine a relative location of an element in the DOM tree structure from at least one of the searches according to the prefix search query, the suffix search query, and the wildcard matching criteria.
| 0.5 |
7,877,343 | 49 | 50 |
49. The system of claim 47 , wherein the extractor processes the corpus of text to tag words included therein as a most probable part-of-speech and then employs a noun chunker to identify noun phrases from which the candidate tuples are extracted.
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49. The system of claim 47 , wherein the extractor processes the corpus of text to tag words included therein as a most probable part-of-speech and then employs a noun chunker to identify noun phrases from which the candidate tuples are extracted. 50. The system of claim 49 , wherein the noun chunker heuristically eliminates non-essential phrases when extracting the candidate tuples during the pass through the corpus of text.
| 0.5 |
8,687,210 | 1 | 5 |
1. A method, comprising: obtaining an electronic document conforming to one of a plurality of print formats; parsing the electronic document according to the one of the plurality of print formats to generate an intermediate data structure conforming to an intermediate format such that the electronic document is converted to the intermediate format, wherein the intermediate format is different from the plurality of print formats; applying one or more rules to obtain data for a plurality of regions of the electronic document from the intermediate data structure; and storing or providing the data for the plurality of regions of the electronic document that has been obtained from the intermediate data structure, thereby enabling a report to be generated using at least a portion of the data for the plurality of regions that has been stored or provided.
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1. A method, comprising: obtaining an electronic document conforming to one of a plurality of print formats; parsing the electronic document according to the one of the plurality of print formats to generate an intermediate data structure conforming to an intermediate format such that the electronic document is converted to the intermediate format, wherein the intermediate format is different from the plurality of print formats; applying one or more rules to obtain data for a plurality of regions of the electronic document from the intermediate data structure; and storing or providing the data for the plurality of regions of the electronic document that has been obtained from the intermediate data structure, thereby enabling a report to be generated using at least a portion of the data for the plurality of regions that has been stored or provided. 5. The method as recited in claim 1 , wherein at least one of the one or more rules includes a search pattern to be identified in the electronic document, and wherein the intermediate data structure includes the search pattern.
| 0.774802 |
9,864,645 | 1 | 8 |
1. A system comprising: wrapping code coupled to an error handler of a routine, in which the routine produces an error and the wrapping code wraps the error with relevant information to provide a wrapped exception instance, including to use an exception type hierarchy to preserve information in the wrapped exception instance including an exception type, and wherein the wrapped exception instance comprises a single exception instance transformed from a series of errors; and an exception manager that receives the wrapped exception instance and determines one or more actions to take based upon the exception type of the wrapped exception instance.
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1. A system comprising: wrapping code coupled to an error handler of a routine, in which the routine produces an error and the wrapping code wraps the error with relevant information to provide a wrapped exception instance, including to use an exception type hierarchy to preserve information in the wrapped exception instance including an exception type, and wherein the wrapped exception instance comprises a single exception instance transformed from a series of errors; and an exception manager that receives the wrapped exception instance and determines one or more actions to take based upon the exception type of the wrapped exception instance. 8. The system of claim 1 further comprising a logging mechanism that logs data corresponding to the wrapped exception instance.
| 0.84125 |
8,000,538 | 21 | 23 |
21. A method according to claim 20 , further comprising: evaluating each category-conditional likelihood of occurrence p(x n |c) as a latent conditionally independent distribution model expressed by the equation: p ( x n | c ) = ∑ k = 1 K p k ( c ) ∏ d = 1 D p k ( x nd | c ) where k is an index to an independent component, 0≦k ≦K; d denotes a dimension index, 1≦d ≦D; x nd denotes a value of the d th dimension of feature x n ; p k (c) denotes a category-conditional probability that a feature is generated from the k th independent component; p k (x n |c) denotes a category-and-latent conditional likelihood that a feature, x n , has x nd as a value of its d th dimension.
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21. A method according to claim 20 , further comprising: evaluating each category-conditional likelihood of occurrence p(x n |c) as a latent conditionally independent distribution model expressed by the equation: p ( x n | c ) = ∑ k = 1 K p k ( c ) ∏ d = 1 D p k ( x nd | c ) where k is an index to an independent component, 0≦k ≦K; d denotes a dimension index, 1≦d ≦D; x nd denotes a value of the d th dimension of feature x n ; p k (c) denotes a category-conditional probability that a feature is generated from the k th independent component; p k (x n |c) denotes a category-and-latent conditional likelihood that a feature, x n , has x nd as a value of its d th dimension. 23. A method according to claim 21 , wherein for the dimensions comprise discrete finite valued attributes and each category-and-latent conditional likelihood is modeled as a multinomial probability mass function for each such discrete dimension.
| 0.5 |
9,116,940 | 1 | 3 |
1. A method comprising: receiving an input column comprising a plurality of query values; receiving a search keyword; identifying a first potential table column; determining a coverage score for the first potential table column, wherein the coverage score is based on the number of query values in the input column also contained in at least a portion of the first potential table column; determining a refinity score for the first potential table column representing a similarity between the first potential table column and the input column, wherein the refinity score is based on an average number of occurrences of values from the input column within at least a portion of the first potential table column; determining a search keyword score for the first potential table column based on the search keyword; and determining a first total score corresponding to the first potential table column based on the coverage score, the refinity score, and the search keyword score.
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1. A method comprising: receiving an input column comprising a plurality of query values; receiving a search keyword; identifying a first potential table column; determining a coverage score for the first potential table column, wherein the coverage score is based on the number of query values in the input column also contained in at least a portion of the first potential table column; determining a refinity score for the first potential table column representing a similarity between the first potential table column and the input column, wherein the refinity score is based on an average number of occurrences of values from the input column within at least a portion of the first potential table column; determining a search keyword score for the first potential table column based on the search keyword; and determining a first total score corresponding to the first potential table column based on the coverage score, the refinity score, and the search keyword score. 3. The method of claim 1 , wherein the search keyword is input by a user.
| 0.912048 |
7,806,758 | 5 | 6 |
5. The method of claim 4 further comprising fluctuating an attribute score based upon environmental considerations within the game.
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5. The method of claim 4 further comprising fluctuating an attribute score based upon environmental considerations within the game. 6. The method of claim 5 wherein an environmental consideration is how frequently a player character uses a given attribute during the game.
| 0.5 |
9,778,922 | 1 | 2 |
1. A method comprising: defining, by a processor, a set of user-defined data types with an encoding; using the encoding and a code-generator utility to generate, by the processor, a first at least one class to implement each of the user-defined data types within the set of user-defined data types in a first software general-purpose language (GPL) as a first container; using the encoding and the code-generator utility to generate, by the processor, a second at least one class to implement each of the set of user-defined data types within the set of user-defined data types in a second software GPL as a second container; running a code-generator to generate, by the processor, software configured to marshal each of the set of user-defined data types within the set of user-defined data types in the first and second at least one classes; marshalling, by the processor, data directly between the first software language and the second software language utilizing a Matlab executable (MEX) interface; and de-marshalling, by the processor, the marshalled data directly into the second software language utilizing the MEX interface.
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1. A method comprising: defining, by a processor, a set of user-defined data types with an encoding; using the encoding and a code-generator utility to generate, by the processor, a first at least one class to implement each of the user-defined data types within the set of user-defined data types in a first software general-purpose language (GPL) as a first container; using the encoding and the code-generator utility to generate, by the processor, a second at least one class to implement each of the set of user-defined data types within the set of user-defined data types in a second software GPL as a second container; running a code-generator to generate, by the processor, software configured to marshal each of the set of user-defined data types within the set of user-defined data types in the first and second at least one classes; marshalling, by the processor, data directly between the first software language and the second software language utilizing a Matlab executable (MEX) interface; and de-marshalling, by the processor, the marshalled data directly into the second software language utilizing the MEX interface. 2. The method of claim 1 further comprising: using the encoding to generate utilities in the first software language and to generate utilities in the second software language.
| 0.801136 |
7,809,705 | 5 | 6 |
5. A computer-implemented method for classifying a web page, comprising: accessing, by one or more computing devices, local web page information of and global web graph information about a plurality of authoritative web pages, local web page information of and global web graph information about a plurality of non-authoritative web pages, and local web page information of and global web graph information about the web page, wherein: each authoritative web page of the plurality of authoritative web pages is a web page of known high quality, each non-authoritative web page of the plurality of non-authoritative web pages is a web page of known low quality, the local web page information of the web pages comprises text, clicking, domain, or time stamp information concerning the web pages, and the global web graph information about the web pages comprises hyperlink or co-citation relationships among the web pages; determining, by the one or more computing devices, a quality of the web page using collective inference by applying collective inference for binary classification of the web page using the local web page information of the web page and the global web graph information about the web page, the local web page information of the plurality of authoritative web pages and the global web graph information about the plurality of authoritative web pages, and the local web page information of the plurality of non-authoritative web pages and the global web graph information about the plurality of non-authoritative web pages, comprising finding a minimum value of a regularized convex dual of a logistic regression loss function for a node of a graph; and outputting, by the one or more computing devices, an indication of the quality of the web page.
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5. A computer-implemented method for classifying a web page, comprising: accessing, by one or more computing devices, local web page information of and global web graph information about a plurality of authoritative web pages, local web page information of and global web graph information about a plurality of non-authoritative web pages, and local web page information of and global web graph information about the web page, wherein: each authoritative web page of the plurality of authoritative web pages is a web page of known high quality, each non-authoritative web page of the plurality of non-authoritative web pages is a web page of known low quality, the local web page information of the web pages comprises text, clicking, domain, or time stamp information concerning the web pages, and the global web graph information about the web pages comprises hyperlink or co-citation relationships among the web pages; determining, by the one or more computing devices, a quality of the web page using collective inference by applying collective inference for binary classification of the web page using the local web page information of the web page and the global web graph information about the web page, the local web page information of the plurality of authoritative web pages and the global web graph information about the plurality of authoritative web pages, and the local web page information of the plurality of non-authoritative web pages and the global web graph information about the plurality of non-authoritative web pages, comprising finding a minimum value of a regularized convex dual of a logistic regression loss function for a node of a graph; and outputting, by the one or more computing devices, an indication of the quality of the web page. 6. The method of claim 5 further comprising receiving the local web page information of and the global web graph information about the plurality of the authoritative web pages.
| 0.881402 |
7,676,680 | 1 | 3 |
1. A computer assisted method of providing a private placement document to a potential investor in a private placement, the method comprising: generating the private placement document in an encrypted electronic format with a computer system comprising at least one processor and operatively associated memory, wherein generating the private placement document includes labeling the private placement document with a unique identifier and wherein the private placement document comprises a subscription document; providing the private placement document to the potential investor electronically with the computer system, wherein the subscription document is programmed to: (i) prompt the potential investor to enter information relating to the potential investor into the subscription document; (ii) conditioned upon the potential investor declining to enter the information relating to the potential investor into the subscription document, rendering the private placement document unreadable by the potential investor; (iii) conditioned upon the information relating to the potential investor failing to meet a pre-determined qualification standard, rendering the private placement document unreadable by the potential investor; and (iv) conditioned upon the potential investor failing to enter the information relating to the potential investor into the subscription document within a predetermined amount of time, rendering the private placement document unreadable by the potential investor; recording the unique identifier at a database in communication with the computer system, wherein the unique identifier is recorded at the database in association with the potential investor; electronically receiving the subscription document from the potential investor with the computer system, wherein the subscription document, when received from the potential investor, comprises the information relating to the potential investor; and verifying with the computer system that the information relating to the potential investor is correctly entered into the subscription document.
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1. A computer assisted method of providing a private placement document to a potential investor in a private placement, the method comprising: generating the private placement document in an encrypted electronic format with a computer system comprising at least one processor and operatively associated memory, wherein generating the private placement document includes labeling the private placement document with a unique identifier and wherein the private placement document comprises a subscription document; providing the private placement document to the potential investor electronically with the computer system, wherein the subscription document is programmed to: (i) prompt the potential investor to enter information relating to the potential investor into the subscription document; (ii) conditioned upon the potential investor declining to enter the information relating to the potential investor into the subscription document, rendering the private placement document unreadable by the potential investor; (iii) conditioned upon the information relating to the potential investor failing to meet a pre-determined qualification standard, rendering the private placement document unreadable by the potential investor; and (iv) conditioned upon the potential investor failing to enter the information relating to the potential investor into the subscription document within a predetermined amount of time, rendering the private placement document unreadable by the potential investor; recording the unique identifier at a database in communication with the computer system, wherein the unique identifier is recorded at the database in association with the potential investor; electronically receiving the subscription document from the potential investor with the computer system, wherein the subscription document, when received from the potential investor, comprises the information relating to the potential investor; and verifying with the computer system that the information relating to the potential investor is correctly entered into the subscription document. 3. The method of claim 1 , wherein the generating includes incorporating into the private placement document information related to the location of the potential investor.
| 0.778497 |
8,381,299 | 74 | 79 |
74. A system for outputting a dataset based upon anomaly detection, the system comprising: a digital processing, device that: receives a first training dataset having a plurality of n-grams that includes a first plurality of distinct training n-grams, wherein each of the first plurality of distinct training n-grams is a first size; receives a second training dataset having a plurality of n-grams that includes a second plurality of distinct training n-grams, wherein each of the second plurality of distinct training n-grams is the first size; computes a first plurality of appearance frequencies, wherein each of the first plurality of appearance frequencies corresponds to one of the first plurality of distinct training n-grams; computes a first plurality of uniformities of distribution, wherein each of the first plurality of uniformities of distribution corresponds to one of the first plurality of distinct training n-grams; computes a second plurality of uniformities of distribution, wherein each of the second plurality of uniformities of distribution corresponds to one of the second plurality of distinct training n-grams; determines a first plurality of most-heavily weighted n-grams from the first plurality of distinct training n-grams using at least one of: the first-plurality of appearance frequencies; the first plurality of uniformities of distribution; and the second plurality of uniformities of distribution; selects a subset of the first plurality of most-heavily weighted n-grams, wherein the subset includes in n-grams and at least one of the n-grams in the subset is outside of the top m of the first plurality of most-heavily weighted n-grams; receives an input dataset including first input n-grams, wherein each of the plurality of first input n-grams is the first size; obtains a subset of a second plurality of most-heavily weighted n-grams from the first input n-grams that correspond to the subset of the first plurality of distinct training n-grams; classifies the input dataset as containing an anomaly using the subset of the first plurality of most-heavily weighted n-grams and the subset of the second plurality of most-heavily weighted n-grams; and outputs a dataset based upon the classifying of the input dataset.
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74. A system for outputting a dataset based upon anomaly detection, the system comprising: a digital processing, device that: receives a first training dataset having a plurality of n-grams that includes a first plurality of distinct training n-grams, wherein each of the first plurality of distinct training n-grams is a first size; receives a second training dataset having a plurality of n-grams that includes a second plurality of distinct training n-grams, wherein each of the second plurality of distinct training n-grams is the first size; computes a first plurality of appearance frequencies, wherein each of the first plurality of appearance frequencies corresponds to one of the first plurality of distinct training n-grams; computes a first plurality of uniformities of distribution, wherein each of the first plurality of uniformities of distribution corresponds to one of the first plurality of distinct training n-grams; computes a second plurality of uniformities of distribution, wherein each of the second plurality of uniformities of distribution corresponds to one of the second plurality of distinct training n-grams; determines a first plurality of most-heavily weighted n-grams from the first plurality of distinct training n-grams using at least one of: the first-plurality of appearance frequencies; the first plurality of uniformities of distribution; and the second plurality of uniformities of distribution; selects a subset of the first plurality of most-heavily weighted n-grams, wherein the subset includes in n-grams and at least one of the n-grams in the subset is outside of the top m of the first plurality of most-heavily weighted n-grams; receives an input dataset including first input n-grams, wherein each of the plurality of first input n-grams is the first size; obtains a subset of a second plurality of most-heavily weighted n-grams from the first input n-grams that correspond to the subset of the first plurality of distinct training n-grams; classifies the input dataset as containing an anomaly using the subset of the first plurality of most-heavily weighted n-grams and the subset of the second plurality of most-heavily weighted n-grams; and outputs a dataset based upon the classifying of the input dataset. 79. The system of claim 74 , wherein the second training dataset comprises a dataset containing at least one known instance of malicious code.
| 0.957022 |
5,412,714 | 19 | 21 |
19. The method of claim 17 wherein: the step of defining comprises the step of defining the network numbering plan such that the symbol strings of individual types have variable lengths in terms of numbers of symbols that make up individual symbol strings of the individual type.
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19. The method of claim 17 wherein: the step of defining comprises the step of defining the network numbering plan such that the symbol strings of individual types have variable lengths in terms of numbers of symbols that make up individual symbol strings of the individual type. 21. The method of claim 19 wherein: the step of defining comprises the step of storing definitions of individual symbol strings of the network numbering plan, each definition including an identification of the string type of the defined string.
| 0.5 |
7,809,564 | 13 | 19 |
13. A computer program product for matching voice based keywords to keyword indexed search items, the computer program product comprising: a non-transitory computer readable medium storing computer usable program code tangibly embodied thereon, the computer usable program code comprising: computer usable program code for identifying, in response to receiving a spoken search request from a caller, keywords within the spoken search request; computer usable program code for creating a list of candidates comprising a match to at least one of the keywords, wherein each candidate in the list is assigned a level of confidence in the match; computer usable program code for locating keyword indexed search items having at least one of the keywords as an index and an original matching score; computer usable program code for weighting the original matching score of each keyword indexed search item with the level of confidence in the list of candidates to form weighted matching scores; computer usable program code for sorting the keyword indexed search items based on the weighted matching scores; and computer usable program code for creating a list of the sorted keyword indexed search items.
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13. A computer program product for matching voice based keywords to keyword indexed search items, the computer program product comprising: a non-transitory computer readable medium storing computer usable program code tangibly embodied thereon, the computer usable program code comprising: computer usable program code for identifying, in response to receiving a spoken search request from a caller, keywords within the spoken search request; computer usable program code for creating a list of candidates comprising a match to at least one of the keywords, wherein each candidate in the list is assigned a level of confidence in the match; computer usable program code for locating keyword indexed search items having at least one of the keywords as an index and an original matching score; computer usable program code for weighting the original matching score of each keyword indexed search item with the level of confidence in the list of candidates to form weighted matching scores; computer usable program code for sorting the keyword indexed search items based on the weighted matching scores; and computer usable program code for creating a list of the sorted keyword indexed search items. 19. The computer program product of claim 13 , wherein the computer usable program code for locating keyword indexed search items, weighting the original matching score of each keyword indexed search item, sorting the keyword indexed search items, and creating the list of the sorted keyword indexed search items is executed by a search engine.
| 0.532609 |
8,874,588 | 7 | 10 |
7. An apparatus comprising: one or more processors; memory; an acquisition unit stored in the memory and executable by the one or more processors, used for obtaining search keywords used by users within a predetermined time period; a statistics unit stored in the memory and executable by the one or more processors, used for counting the search keywords to obtain a primary keyword, related keywords, co-search frequencies of the primary keyword and the related keywords being searched together, and a search frequency of the primary keyword being searched alone; a correlation computing sub-unit stored in the memory and executable by the one or more processors, used for computing correlation levels based at least in part on the co-search frequencies of the primary keyword and the related keywords being searched together; a first computation unit stored in the memory and executable by the one or more processors, used for computing a first feature value based at least in part on the search frequency of the primary keyword being searched alone; and a second computation unit stored in the memory and executable by the one or more processors, used for computing second feature values based at least in part on the first feature value, the correlation levels and the co-search frequencies of the primary keyword and the related keywords being searched together, wherein a second feature value serves as a parameter for determining whether a corresponding related keyword of the related keywords is to be displayed constantly or in a rotating manner.
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7. An apparatus comprising: one or more processors; memory; an acquisition unit stored in the memory and executable by the one or more processors, used for obtaining search keywords used by users within a predetermined time period; a statistics unit stored in the memory and executable by the one or more processors, used for counting the search keywords to obtain a primary keyword, related keywords, co-search frequencies of the primary keyword and the related keywords being searched together, and a search frequency of the primary keyword being searched alone; a correlation computing sub-unit stored in the memory and executable by the one or more processors, used for computing correlation levels based at least in part on the co-search frequencies of the primary keyword and the related keywords being searched together; a first computation unit stored in the memory and executable by the one or more processors, used for computing a first feature value based at least in part on the search frequency of the primary keyword being searched alone; and a second computation unit stored in the memory and executable by the one or more processors, used for computing second feature values based at least in part on the first feature value, the correlation levels and the co-search frequencies of the primary keyword and the related keywords being searched together, wherein a second feature value serves as a parameter for determining whether a corresponding related keyword of the related keywords is to be displayed constantly or in a rotating manner. 10. The apparatus as recited in claim 7 , the apparatus further comprising: a filtering unit connected with the statistics unit and used for filtering out one or more search keywords that satisfy a filtering rule.
| 0.515909 |
9,836,538 | 19 | 20 |
19. A method of responding to a search query, the method comprising: using a processor to perform acts comprising: receiving a query; calculating scores for a plurality of documents obtained with respect to the received query by comparing terms in said query with terms in said documents; calling a same first function implemented by each of a plurality of domain-based scorers of different types, to determine, without utilizing one or more documents of the plurality of documents, which of said domain-based scorers will contribute and which will not contribute to scoring of said documents in response to the calculation of said scores for the plurality of documents, wherein the same first function is used to determine whether the received query is too vague and will not be scored or is not too vague and will be scored, and wherein determining whether the received query is too vague or not too vague is based upon each domain-based scorer using its own set of first criteria for determining whether the received query is too vague or not too vague, each of said domain-based scorers calculating a domain-based score based on features of said documents or of said query that are specific to a substantive field of knowledge after the calculation of the scores for the plurality of documents, said each of said plurality of domain-based scorers implementing its own version of a same second function to calculate the domain-based score of said documents without obtaining said documents again with respect to the received query, wherein the same second function includes receiving document identifiers to identify said documents in a database and returning scores for said documents and using the returned scores as input into an aggregation formula, wherein each domain-based scorer uses its own set of second criteria within the aggregation formula, wherein said same second function of each of the plurality of domain-based scorers utilizes said documents which have already received scores based on the terms in said query to calculate the domain-based scores of said documents; including, on a list, those domain-based scorers that indicate, through said same first function, that they will contribute to scoring of said documents; using a configurable parameter selected based on a different scoring scheme by those ones of said domain-based scorers that are on said list to adjust said scores, whereby adjusted scores of said documents are created by combining the contributions from all of the said domain-based scorers; creating a set of search results based on the adjusted scores of said documents; and presenting said search results to a user.
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19. A method of responding to a search query, the method comprising: using a processor to perform acts comprising: receiving a query; calculating scores for a plurality of documents obtained with respect to the received query by comparing terms in said query with terms in said documents; calling a same first function implemented by each of a plurality of domain-based scorers of different types, to determine, without utilizing one or more documents of the plurality of documents, which of said domain-based scorers will contribute and which will not contribute to scoring of said documents in response to the calculation of said scores for the plurality of documents, wherein the same first function is used to determine whether the received query is too vague and will not be scored or is not too vague and will be scored, and wherein determining whether the received query is too vague or not too vague is based upon each domain-based scorer using its own set of first criteria for determining whether the received query is too vague or not too vague, each of said domain-based scorers calculating a domain-based score based on features of said documents or of said query that are specific to a substantive field of knowledge after the calculation of the scores for the plurality of documents, said each of said plurality of domain-based scorers implementing its own version of a same second function to calculate the domain-based score of said documents without obtaining said documents again with respect to the received query, wherein the same second function includes receiving document identifiers to identify said documents in a database and returning scores for said documents and using the returned scores as input into an aggregation formula, wherein each domain-based scorer uses its own set of second criteria within the aggregation formula, wherein said same second function of each of the plurality of domain-based scorers utilizes said documents which have already received scores based on the terms in said query to calculate the domain-based scores of said documents; including, on a list, those domain-based scorers that indicate, through said same first function, that they will contribute to scoring of said documents; using a configurable parameter selected based on a different scoring scheme by those ones of said domain-based scorers that are on said list to adjust said scores, whereby adjusted scores of said documents are created by combining the contributions from all of the said domain-based scorers; creating a set of search results based on the adjusted scores of said documents; and presenting said search results to a user. 20. The method of claim 19 , wherein each of the domain-based scorers that are on said list contributes a score for each of said documents, and wherein said acts further comprise: calculating said adjusted score for each document by calculating a product of: (a) a score for that document that is calculated by comparing terms in said query with terms in the document, and (b) the domain-based scores contributed by each of the domain-based scorers that are on said list.
| 0.5 |
8,972,423 | 9 | 16 |
9. A computer readable medium for storing executable instructions to perform a method of parsing a schema across a plurality of disparate vendors having interoperability of at least one web service, comprising: instructions for communicating a plurality of data in a data defining mark-up language file by a transport protocol stack; instructions for parsing said data defining mark-up language to determine at least one opaque schema element by a deep copy mechanism comprising: instructions for calling a deep copy helper to extract a plurality of opaque data corresponding to input type; instructions for filling a plurality of objects with said opaque data in a recursive manner; and instructions for returning said objects to convert to an opaque string; and instructions for translating said at least one opaque schema element to a mark-up language string element.
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9. A computer readable medium for storing executable instructions to perform a method of parsing a schema across a plurality of disparate vendors having interoperability of at least one web service, comprising: instructions for communicating a plurality of data in a data defining mark-up language file by a transport protocol stack; instructions for parsing said data defining mark-up language to determine at least one opaque schema element by a deep copy mechanism comprising: instructions for calling a deep copy helper to extract a plurality of opaque data corresponding to input type; instructions for filling a plurality of objects with said opaque data in a recursive manner; and instructions for returning said objects to convert to an opaque string; and instructions for translating said at least one opaque schema element to a mark-up language string element. 16. The computer readable medium of claim 9 , wherein said transport protocol stack is SOAP.
| 0.72619 |
6,070,133 | 1 | 6 |
1. A method for automatically determining a semantic structure of an electronically formatted natural language based document consisting essentially of words, the method comprising the steps of: a) providing a numerical representation as a digital signal of the words within the document wherein said numerical representation contains some information relating the semantic content of the word to the semantic content of the document b) performing a wavelet transform on said signal, thereby determining the semantic structure.
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1. A method for automatically determining a semantic structure of an electronically formatted natural language based document consisting essentially of words, the method comprising the steps of: a) providing a numerical representation as a digital signal of the words within the document wherein said numerical representation contains some information relating the semantic content of the word to the semantic content of the document b) performing a wavelet transform on said signal, thereby determining the semantic structure. 6. The method of claim 1 further comprising the step of utilizing the output of the wavelet transform to partition the document.
| 0.890411 |
9,749,762 | 7 | 12 |
7. A non-transitory computer-readable storage medium storing instructions that when executed by a computer cause the computer to perform a sound-recognition operation, the method comprising: recognizing a sequence of sound primitives in an audio stream, wherein a sound primitive is associated with a semantic label comprising one or more words that describe a sound characterized by the sound primitive, wherein recognizing the sequence of sound primitives comprises, performing a feature-detection operation on a sequence of sound samples from the audio stream to detect a set of sound features, wherein each sound feature comprises a measurable characteristic for a time window of consecutive sound samples, and wherein detecting the sound feature involves generating a coefficient indicating a likelihood that the sound feature is present in the time window, creating a set of feature vectors from coefficients generated by the feature-detection operation, wherein each feature vector comprises a set of coefficients for sound features in the set of sound features, and identifying the sequence of sound primitives from the sequence of feature vectors; feeding the sequence of sound primitives into a finite-state automaton that recognizes events associated with sequences of sound primitives; and feeding the recognized events into an output system that generates an output associated with the recognized events to be displayed to a user.
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7. A non-transitory computer-readable storage medium storing instructions that when executed by a computer cause the computer to perform a sound-recognition operation, the method comprising: recognizing a sequence of sound primitives in an audio stream, wherein a sound primitive is associated with a semantic label comprising one or more words that describe a sound characterized by the sound primitive, wherein recognizing the sequence of sound primitives comprises, performing a feature-detection operation on a sequence of sound samples from the audio stream to detect a set of sound features, wherein each sound feature comprises a measurable characteristic for a time window of consecutive sound samples, and wherein detecting the sound feature involves generating a coefficient indicating a likelihood that the sound feature is present in the time window, creating a set of feature vectors from coefficients generated by the feature-detection operation, wherein each feature vector comprises a set of coefficients for sound features in the set of sound features, and identifying the sequence of sound primitives from the sequence of feature vectors; feeding the sequence of sound primitives into a finite-state automaton that recognizes events associated with sequences of sound primitives; and feeding the recognized events into an output system that generates an output associated with the recognized events to be displayed to a user. 12. The non-transitory computer-readable storage medium of claim 7 , wherein the output system triggers an alert when a probability that a tracked event is occurring exceeds a threshold value.
| 0.861472 |
8,983,827 | 7 | 8 |
7. A method for linguistical analytic consolidation, the method comprising: displaying a user interface on a mobile device; receiving source text content to display in the user interface; scanning the source text content for a specific element; generating a mobility score for the source text content, wherein the mobility score describes a compatibility of the source text content for display on a device; and flagging the specific element of the source text content to be modified according to a set of linguistic rules, wherein modifying the specific element according to the set of linguistic rules results in a consolidated form of the source text content.
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7. A method for linguistical analytic consolidation, the method comprising: displaying a user interface on a mobile device; receiving source text content to display in the user interface; scanning the source text content for a specific element; generating a mobility score for the source text content, wherein the mobility score describes a compatibility of the source text content for display on a device; and flagging the specific element of the source text content to be modified according to a set of linguistic rules, wherein modifying the specific element according to the set of linguistic rules results in a consolidated form of the source text content. 8. The method of claim 7 , wherein the set of linguistic rules comprises a rule to modify the specific element by replacing the specific element with at least one of: a best choice for a similar element; an identified synonym; and an application widget.
| 0.611963 |
9,552,130 | 12 | 13 |
12. The method of claim 1 , wherein the hosted application is run within a virtualized computing environment of a virtualization platform, and wherein the remote computing platform accesses the virtualized computing environment via a receiver application executed on the remote computing platform.
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12. The method of claim 1 , wherein the hosted application is run within a virtualized computing environment of a virtualization platform, and wherein the remote computing platform accesses the virtualized computing environment via a receiver application executed on the remote computing platform. 13. The method of claim 12 , wherein one or more of the hosted application and the receiver application comprises at least one of a web browser or a web browser plugin, and wherein identifying the plurality of UI elements comprises making at least one call to a browser helper object (BHO) of the at least one of the web browser or the web browser plugin.
| 0.5 |
7,801,899 | 1 | 13 |
1. A machine-implemented method comprising: receiving a request for keyword suggestions, the request including a seed keyword with which the keyword suggestions are to be generated; accepting, from two or more keyword suggestion tools, at least two heterogeneous sets of keyword suggestions for an online advertisement, wherein each set of keyword suggestions includes targeting keyword suggestions that are ranked and scored by a keyword suggestion tool that suggested the set of keyword suggestions, and wherein targeting keyword suggestions in each set of targeting keyword suggestions have been generated based on the seed keyword; for each heterogeneous sets of keyword suggestions accepted from the at least two or more keyword suggestion tools, determining, by one or more processors, a new normalized score for each of the targeting keyword suggestions in the heterogeneous set of keyword suggestions, wherein the new normalized score is computed based on a cardinal aspect of the targeting keyword suggestion and an ordinal aspect of the targeting keyword suggestion in the heterogeneous set of keyword suggestions, the cardinal aspect representing an absolute score corresponding to the targeting keyword suggestion and the ordinal aspect representing a rank of the targeting keyword suggestion in the heterogeneous set of keyword suggestions, and wherein the new normalized score for each targeting keyword suggestion in a particular set of heterogeneous keyword suggestions is defined as a sum of a first weight multiplied by the cardinal aspect and a second weight multiplied by the ordinal aspect; generating, by the one or more processors, an adjusted new score for each targeting keyword suggestion based on a result of a function of a new normalized score corresponding to the targeting keyword suggestion and trust factor of a keyword suggestion tool from which the targeting keyword was accepted, the trust factor representing a measure of reliability of the keyword suggestion tool; combining, by the one or more processors, the targeting keyword suggestions scored by a first keyword suggestion tool selected from the at least two or more keyword suggestion tools and the targeting keyword suggestions scored by a second suggestion tool selected from the at least two or more keyword suggestion tools using the new scores to generate a combined set of ordered and scored suggestions according to the adjusted new score for each targeting keyword suggestion; and providing the combined set of keyword suggestions to a user device.
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1. A machine-implemented method comprising: receiving a request for keyword suggestions, the request including a seed keyword with which the keyword suggestions are to be generated; accepting, from two or more keyword suggestion tools, at least two heterogeneous sets of keyword suggestions for an online advertisement, wherein each set of keyword suggestions includes targeting keyword suggestions that are ranked and scored by a keyword suggestion tool that suggested the set of keyword suggestions, and wherein targeting keyword suggestions in each set of targeting keyword suggestions have been generated based on the seed keyword; for each heterogeneous sets of keyword suggestions accepted from the at least two or more keyword suggestion tools, determining, by one or more processors, a new normalized score for each of the targeting keyword suggestions in the heterogeneous set of keyword suggestions, wherein the new normalized score is computed based on a cardinal aspect of the targeting keyword suggestion and an ordinal aspect of the targeting keyword suggestion in the heterogeneous set of keyword suggestions, the cardinal aspect representing an absolute score corresponding to the targeting keyword suggestion and the ordinal aspect representing a rank of the targeting keyword suggestion in the heterogeneous set of keyword suggestions, and wherein the new normalized score for each targeting keyword suggestion in a particular set of heterogeneous keyword suggestions is defined as a sum of a first weight multiplied by the cardinal aspect and a second weight multiplied by the ordinal aspect; generating, by the one or more processors, an adjusted new score for each targeting keyword suggestion based on a result of a function of a new normalized score corresponding to the targeting keyword suggestion and trust factor of a keyword suggestion tool from which the targeting keyword was accepted, the trust factor representing a measure of reliability of the keyword suggestion tool; combining, by the one or more processors, the targeting keyword suggestions scored by a first keyword suggestion tool selected from the at least two or more keyword suggestion tools and the targeting keyword suggestions scored by a second suggestion tool selected from the at least two or more keyword suggestion tools using the new scores to generate a combined set of ordered and scored suggestions according to the adjusted new score for each targeting keyword suggestion; and providing the combined set of keyword suggestions to a user device. 13. The machine-implemented method of claim 1 further comprising: for each of the at least two heterogeneous sets of keyword suggestions, and for each new normalized score for each of the keyword suggestions of the heterogeneous set of keyword suggestions, adjusting the new normalized score to generate an adjusted new score so that a sum of the adjusted new scores for each of the sets equals the same value.
| 0.5 |
8,260,839 | 1 | 5 |
1. A method comprising: receiving a message at a client, the message including a message body; parsing the message body into parts of the message body using a natural language processor, wherein a first part of the message body is associated with a second part of the message body; comparing the parts of the parsed message body with a parameter to determine whether information provided in the parts is sufficient to identify a service and a backend system to process the message body, wherein the parameter includes a condition and a field for the identification of the service and the backend system; requesting additional information to identify the service and the backend system included in an additional message body if the information provided in the parts of the message body is not sufficient to identify the service and the backend system, the additional information requested in a conversation mode and provided with a second parameter; interpreting the parts of the message body; identifying the service and the backend system to process the message body based on the interpreted parts of the message body; creating a model based on the information, the additional information, the identified service, and the identified backend system; and invoking the service to process the message body from the backend system based on the information and the additional information from the created model.
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1. A method comprising: receiving a message at a client, the message including a message body; parsing the message body into parts of the message body using a natural language processor, wherein a first part of the message body is associated with a second part of the message body; comparing the parts of the parsed message body with a parameter to determine whether information provided in the parts is sufficient to identify a service and a backend system to process the message body, wherein the parameter includes a condition and a field for the identification of the service and the backend system; requesting additional information to identify the service and the backend system included in an additional message body if the information provided in the parts of the message body is not sufficient to identify the service and the backend system, the additional information requested in a conversation mode and provided with a second parameter; interpreting the parts of the message body; identifying the service and the backend system to process the message body based on the interpreted parts of the message body; creating a model based on the information, the additional information, the identified service, and the identified backend system; and invoking the service to process the message body from the backend system based on the information and the additional information from the created model. 5. The method of claim 1 , further comprising: sending the message using a messenger to a messenger server; checking the client at the messenger server for the message; and routing the message to the client.
| 0.795858 |
8,666,935 | 15 | 16 |
15. A document processing method for a medical office, comprising: receiving, at a server, at least one electronic document from a medical office, the server being hosted on a document services grid accessible through a network interface and including a software application adapted to recognize an expected class of each electronic documents corresponding to patient records, office expenses, and government compliance at the medical office; extracting data from the each electronic document received from the medical office through the network interface based on the recognized class; automatically mapping the extracted data to a data repository on the hosted server; monitoring a process maturity indicator of the medical office based on access to the mapped data of at least two documents; and electronically generating at least one report based on at least one of the mapped data and the monitored process maturity indicator, the at least one report corresponding to at least one process simplification to improve process maturity of a medical office setting, and the report being made accessible via the network interface; providing the medical office with access to the mapped data for receiving one of a verification and a correction to train the software application based on one of the verification and the correction; and, automatically classifying a subsequently processed electronic document that is substantially similar a previously verified electronic document to train the software application in accordance with the class of the previously recognized electronic document.
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15. A document processing method for a medical office, comprising: receiving, at a server, at least one electronic document from a medical office, the server being hosted on a document services grid accessible through a network interface and including a software application adapted to recognize an expected class of each electronic documents corresponding to patient records, office expenses, and government compliance at the medical office; extracting data from the each electronic document received from the medical office through the network interface based on the recognized class; automatically mapping the extracted data to a data repository on the hosted server; monitoring a process maturity indicator of the medical office based on access to the mapped data of at least two documents; and electronically generating at least one report based on at least one of the mapped data and the monitored process maturity indicator, the at least one report corresponding to at least one process simplification to improve process maturity of a medical office setting, and the report being made accessible via the network interface; providing the medical office with access to the mapped data for receiving one of a verification and a correction to train the software application based on one of the verification and the correction; and, automatically classifying a subsequently processed electronic document that is substantially similar a previously verified electronic document to train the software application in accordance with the class of the previously recognized electronic document. 16. A method according to claim 15 , wherein the at least one report is accessible to the medical office via iconic access through the network interface.
| 0.728723 |
8,370,812 | 2 | 3 |
2. The method of claim 1 , wherein each of the plurality of component descriptions includes: a graph pattern that semantically describes the objects that must be included in the pre-inclusion state; and a graph pattern that semantically describes the objects that must be in the post-inclusion state.
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2. The method of claim 1 , wherein each of the plurality of component descriptions includes: a graph pattern that semantically describes the objects that must be included in the pre-inclusion state; and a graph pattern that semantically describes the objects that must be in the post-inclusion state. 3. The method of claim 2 , wherein assembling each of the plurality of processing graphs comprises: matching a post-inclusion state obtained after adding a first component to a processing graph to an applicability condition of a second component if the post-inclusion state obtained after adding the first component to the processing graph includes the objects that must be included in a pre-inclusion state applicable to the second component, and if the graph that semantically describes the objects in the post-inclusion state of the first component satisfies the graph pattern that semantically describes the objects that must be included in the pre-inclusion state applicable to the second component.
| 0.5 |
8,386,252 | 19 | 20 |
19. The system of claim 12 , wherein one or more recommendations on how to improve understandability are provided.
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19. The system of claim 12 , wherein one or more recommendations on how to improve understandability are provided. 20. The system of claim 19 , wherein the one or more recommendations are provided via one or more of a whisper channel, a graphical user interface, a display and audibly.
| 0.5 |
8,881,104 | 1 | 18 |
1. A method for component discovery from source code, the method comprising: receiving source code; determining business classes by excluding packages and classes in the source code identified at least one of as belonging to a presentation layer, as belonging to a data access layer, as models and as utilities; extracting features from the business classes; estimating similarity for business class pairs based on the extracted features; clustering, by a processor, the business classes based on the similarity, wherein clusters generated by the clustering represent components of the source code; and determining interfaces for the components based on the clustering.
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1. A method for component discovery from source code, the method comprising: receiving source code; determining business classes by excluding packages and classes in the source code identified at least one of as belonging to a presentation layer, as belonging to a data access layer, as models and as utilities; extracting features from the business classes; estimating similarity for business class pairs based on the extracted features; clustering, by a processor, the business classes based on the similarity, wherein clusters generated by the clustering represent components of the source code; and determining interfaces for the components based on the clustering. 18. The method of claim 1 , further comprising: automatically labeling clusters by extracting dominant terms using class-names, textual vectors, and public method identifiers.
| 0.88079 |
7,716,022 | 14 | 15 |
14. The method of claim 1 , further comprising: performing outlier detection with respect to each of the candidate models; for a detected outlier, creating dummy regressors for use in forecasting the time series data.
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14. The method of claim 1 , further comprising: performing outlier detection with respect to each of the candidate models; for a detected outlier, creating dummy regressors for use in forecasting the time series data. 15. The method of claim 14 , wherein detected outliers are selected from the group consisting of additive outliers, level shift outliers and combinations thereof.
| 0.5 |
8,229,753 | 17 | 18 |
17. The computer readable storage medium of claim 11 wherein one of the second set of attributes for one of the controls provides instructions related to generating audible output.
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17. The computer readable storage medium of claim 11 wherein one of the second set of attributes for one of the controls provides instructions related to generating audible output. 18. The computer readable storage medium of claim 17 wherein the instructions comprise text and the attribute relates to converting the text to audible output.
| 0.5 |
9,436,951 | 22 | 24 |
22. A non-transitory computer-readable medium whose contents configure one or more computing systems to perform a method of presenting additional content for a term presented by a first mobile communication device, the method comprising: receiving, by the first mobile communication device, a first utterance; transmitting a first identifier of the first mobile communication device and the first utterance from the first mobile communication device to a computing device; receiving, by the first mobile communication device from the computing device, text representing a transcription of the first utterance; receiving, by the first mobile communication device from the computing device, an indicator that first additional content is available for a term identified within the text by the indicator, wherein the term is associated at the computing device with the first identifier of the first mobile communication device and a second identifier of a second mobile communication device, and wherein the first additional content for the term is associated with the first identifier and the second identifier; presenting, on the first mobile communications device, the text with an emphasis on the term identified by the indicator; after presenting the text on the first mobile communication device, receiving, by the first mobile communication device, a second utterance that includes the term; transmitting, by the first mobile communication device, the first identifier and the second utterance to the computing device; receiving, by the first mobile communication device from the computing device, in response to transmitting the second utterance and the first identifier, the first additional content; presenting, on the first mobile communication device, the first additional content for the term; transmitting, by the first mobile communication device, the second identifier to the computing device, the computing device configured to send the text as well as the indicator that first additional content is available for the term to the second mobile communication device using the second identifier; and receiving, by the first mobile communication device from the computing device, a message including a transcribed third utterance received by the second communication device in response to the text.
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22. A non-transitory computer-readable medium whose contents configure one or more computing systems to perform a method of presenting additional content for a term presented by a first mobile communication device, the method comprising: receiving, by the first mobile communication device, a first utterance; transmitting a first identifier of the first mobile communication device and the first utterance from the first mobile communication device to a computing device; receiving, by the first mobile communication device from the computing device, text representing a transcription of the first utterance; receiving, by the first mobile communication device from the computing device, an indicator that first additional content is available for a term identified within the text by the indicator, wherein the term is associated at the computing device with the first identifier of the first mobile communication device and a second identifier of a second mobile communication device, and wherein the first additional content for the term is associated with the first identifier and the second identifier; presenting, on the first mobile communications device, the text with an emphasis on the term identified by the indicator; after presenting the text on the first mobile communication device, receiving, by the first mobile communication device, a second utterance that includes the term; transmitting, by the first mobile communication device, the first identifier and the second utterance to the computing device; receiving, by the first mobile communication device from the computing device, in response to transmitting the second utterance and the first identifier, the first additional content; presenting, on the first mobile communication device, the first additional content for the term; transmitting, by the first mobile communication device, the second identifier to the computing device, the computing device configured to send the text as well as the indicator that first additional content is available for the term to the second mobile communication device using the second identifier; and receiving, by the first mobile communication device from the computing device, a message including a transcribed third utterance received by the second communication device in response to the text. 24. The non-transitory computer-readable medium of claim 22 , wherein presenting the text on the first mobile communication device with an emphasis on the term identified by the indicator comprises playing audio of the text on the first mobile communication device, wherein the audio includes one or more of pronunciation emphasis for the term or aural cueing for the term.
| 0.621704 |
9,436,287 | 8 | 9 |
8. The system of claim 1 , wherein each of the one or more touchless gestures corresponds to a respective mode of a plurality of modes, and wherein the one or more processors are configured to selectively process an audio waveform detected by the microphone in one mode of the plurality of modes when: a time stamp of the detected audio waveform is between a time stamp corresponding to a start of one touchless gesture of the one or more touchless gestures corresponding to the one mode detected by the gesture detection sensor and a time stamp corresponding to an end of the one touchless gesture; or a time stamp of the detected audio waveform is between the time stamp corresponding to the start of the one touchless gesture and a time stamp corresponding to a start of a next detected touchless gesture.
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8. The system of claim 1 , wherein each of the one or more touchless gestures corresponds to a respective mode of a plurality of modes, and wherein the one or more processors are configured to selectively process an audio waveform detected by the microphone in one mode of the plurality of modes when: a time stamp of the detected audio waveform is between a time stamp corresponding to a start of one touchless gesture of the one or more touchless gestures corresponding to the one mode detected by the gesture detection sensor and a time stamp corresponding to an end of the one touchless gesture; or a time stamp of the detected audio waveform is between the time stamp corresponding to the start of the one touchless gesture and a time stamp corresponding to a start of a next detected touchless gesture. 9. The system of claim 8 , wherein the plurality of modes includes at least one of a correction mode, a command mode, or a translation mode.
| 0.5 |
6,151,608 | 7 | 18 |
7. The method as claimed in claim 6 further comprising the step of creating templates for transforming or translating the data from the at least one source to obtain the transformed data.
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7. The method as claimed in claim 6 further comprising the step of creating templates for transforming or translating the data from the at least one source to obtain the transformed data. 18. The method as claimed in claim 7 wherein the set of instructions are generated based on the templates and the schema.
| 0.735808 |
9,317,201 | 19 | 20 |
19. A computing device comprising: one or more processors; and at least one module operable by the one or more processors to: receive an indication of at least two contacts at a region of a presence-sensitive screen that outputs a virtual keyboard, the at least two contacts constituting a sequence of contacts and being associated with a predicted word and a probability for the predicted word; receive an indication of a third contact at the region of the presence-sensitive screen; apply a probabilistic model based on a spatial location of the third contact and the predicted word, wherein the spatial location is based on a distance of the third contact from a location within the virtual spacebar key, the probabilistic model configured to interpret the third contact as at least one of (i) a selection of the predicted word, wherein the predicted word has a same number of characters as a number of contacts in the sequence of contacts, (ii) a selection of the predicted word, wherein the predicted word has a greater number of characters than the number of contacts in the sequence of contacts, and (iii) a user input of a non-space character; and update an input buffer based on an interpretation of the third contact, the interpretation being based on the probabilistic model.
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19. A computing device comprising: one or more processors; and at least one module operable by the one or more processors to: receive an indication of at least two contacts at a region of a presence-sensitive screen that outputs a virtual keyboard, the at least two contacts constituting a sequence of contacts and being associated with a predicted word and a probability for the predicted word; receive an indication of a third contact at the region of the presence-sensitive screen; apply a probabilistic model based on a spatial location of the third contact and the predicted word, wherein the spatial location is based on a distance of the third contact from a location within the virtual spacebar key, the probabilistic model configured to interpret the third contact as at least one of (i) a selection of the predicted word, wherein the predicted word has a same number of characters as a number of contacts in the sequence of contacts, (ii) a selection of the predicted word, wherein the predicted word has a greater number of characters than the number of contacts in the sequence of contacts, and (iii) a user input of a non-space character; and update an input buffer based on an interpretation of the third contact, the interpretation being based on the probabilistic model. 20. The computing device of claim 19 , wherein the at least one module is operable by the one or more processors to: output at least a portion of the updated input buffer for display at the presence-sensitive screen.
| 0.642384 |
8,447,751 | 16 | 17 |
16. The non-transitory computer readable medium of claim 14 , wherein the computer readable instructions, when executed, further cause the apparatus to: determine an improvement for raising the search engine score of the network document by analyzing at least one of: a missing meta title, a missing meta description, a missing meta keyword, a duplicate meta title, a duplicate meta description, a duplicate meta keyword, and a broken link; and display the improvement.
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16. The non-transitory computer readable medium of claim 14 , wherein the computer readable instructions, when executed, further cause the apparatus to: determine an improvement for raising the search engine score of the network document by analyzing at least one of: a missing meta title, a missing meta description, a missing meta keyword, a duplicate meta title, a duplicate meta description, a duplicate meta keyword, and a broken link; and display the improvement. 17. The non-transitory computer readable medium of claim 16 , wherein the computer readable instructions, when executed, further cause the apparatus to: receive a request to re-analyze the network document upon the improvement being made to the network document; and re-analyze the network document including the improvement.
| 0.5 |
9,251,289 | 15 | 17 |
15. A computer storage device comprising instructions that when executed perform a method, comprising: matching a first target term, comprised in a target string, to a first known term in an index tree, the first known term associated with a known string identifier (ID); matching a second target term, comprised in the target string, to a second known term in the index tree, the second known term associated with the known string ID; and responsive to determining that a threshold number of target terms, comprising the first target term and the second target term, comprised in the target string are respectively matched with a known term associated with the known string ID, matching the target string to a known string associated with the known string ID.
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15. A computer storage device comprising instructions that when executed perform a method, comprising: matching a first target term, comprised in a target string, to a first known term in an index tree, the first known term associated with a known string identifier (ID); matching a second target term, comprised in the target string, to a second known term in the index tree, the second known term associated with the known string ID; and responsive to determining that a threshold number of target terms, comprising the first target term and the second target term, comprised in the target string are respectively matched with a known term associated with the known string ID, matching the target string to a known string associated with the known string ID. 17. The computer storage device of claim 15 , the method comprising populating a string database with a plurality of known strings, including the known string, respective known strings in the string database associated with known string IDs.
| 0.5 |
4,348,553 | 3 | 4 |
3. A system as recited in claim 1, further comprising a word prototype controller at each local decision module for providing, to said accumulator memory means, prototype speech information which is specialized for its respective module.
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3. A system as recited in claim 1, further comprising a word prototype controller at each local decision module for providing, to said accumulator memory means, prototype speech information which is specialized for its respective module. 4. A system as recited in claim 3, further comprising, in each local decision module, a partial results memory connected to the output of said accumulator memory means for receiving, for each observation of a speech segment, both the result of the base input-transition probabilities from other modules and the current local observation from said accumulator memory means, said partial results memory providing its accumulated results to the other local decision modules.
| 0.5 |
8,412,771 | 1 | 7 |
1. One or more non-transitory storage media storing instructions which, when executed by one or more computing devices, cause the one or more computing devices to perform: accessing a plurality of public posts of user-generated textual content; wherein the plurality of public posts comprise a set of two of more posts from a same author; for each public post of the plurality of public posts of user-generated textual content, based at least in part on a word or phrase in the textual content of the public post, determining a degree to which the public post is associated with an entity; in response to a user's request for information about the entity, performing the steps of: selecting a set of public posts from the plurality of public posts that are predicted to be associated with the entity; and causing concurrent display, to a user other than the entity, of the selected set of public posts and information retrieved about the entity.
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1. One or more non-transitory storage media storing instructions which, when executed by one or more computing devices, cause the one or more computing devices to perform: accessing a plurality of public posts of user-generated textual content; wherein the plurality of public posts comprise a set of two of more posts from a same author; for each public post of the plurality of public posts of user-generated textual content, based at least in part on a word or phrase in the textual content of the public post, determining a degree to which the public post is associated with an entity; in response to a user's request for information about the entity, performing the steps of: selecting a set of public posts from the plurality of public posts that are predicted to be associated with the entity; and causing concurrent display, to a user other than the entity, of the selected set of public posts and information retrieved about the entity. 7. One or more non-transitory storage media as recited in claim 1 , wherein, for a particular public post of the plurality of public posts, determining the degree to which the particular public post is associated the entity is based at least in part on one or more other public posts generated by a same author as the particular public post.
| 0.670213 |
8,554,541 | 12 | 13 |
12. A method of chatting with virtual pet, applied to a device comprising a processor coupled to a memory storing instructions for execution by the processor, the method comprising: receiving, in the device, a sentence in natural language and an ID of a pet owner; processing, in the device, the sentence through natural language comprehension, obtaining language characteristics of the pet owner from a pet owner language information base according to the ID of the pet owner, and generating an answer in natural language based on reasoning knowledge, a result of natural language comprehension , and the language characteristics of the pet owner; wherein the language characteristics of the pet owner include language tips and expression manners.
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12. A method of chatting with virtual pet, applied to a device comprising a processor coupled to a memory storing instructions for execution by the processor, the method comprising: receiving, in the device, a sentence in natural language and an ID of a pet owner; processing, in the device, the sentence through natural language comprehension, obtaining language characteristics of the pet owner from a pet owner language information base according to the ID of the pet owner, and generating an answer in natural language based on reasoning knowledge, a result of natural language comprehension , and the language characteristics of the pet owner; wherein the language characteristics of the pet owner include language tips and expression manners. 13. The method of claim 12 , further comprising: before generating the answer in natural language, receiving, in the device, information of the pet to be chatted with, and obtaining language characteristics of a pet owner according to the information of the pet; wherein generating the answer in natural language comprises, generating the answer in natural language based on the result of natural language comprehension, the reasoning knowledge and the language characteristics of the pet owner.
| 0.672185 |
5,384,702 | 10 | 11 |
10. The method of claim 1, wherein a grammar marker of said plurality of grammar markers includes a progressive mode marker.
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10. The method of claim 1, wherein a grammar marker of said plurality of grammar markers includes a progressive mode marker. 11. The method of claim 10, wherein said first database includes present participle conversion rules.
| 0.5 |
8,429,605 | 1 | 3 |
1. A computer implemented system for developing an application program having functionality that corresponds to a finite state machine (FSM) model, including: a first plurality of non-transitory machine readable instructions adapted to be stored on a first computer comprising an action library including a plurality of dynamic link library (DLL) files operable to execute a plurality of functions comprising one or more standard actions associated with a plurality of potential FSM models; a second plurality of non-transitory machine readable instructions adapted to be stored in a second computer system operable to generate a visual interface that generates a graphical environment on a display associated with said second computer system, the graphic environment including a workspace for creating and displaying an FSM model representing functionality of an application program, the FSM model including a plurality of elements including state elements, said standard actions, and transition elements connecting the state elements, wherein said visual interface further is adapted to output a first data file that is adapted to be output from said second computer and stored in said first computer comprising a third plurality of non-transitory machine readable instructions comprising one or more specifications of a generated said FSM model which includes markup language descriptions comprising one or more identifiers for said plurality of functions associated with said one or more standard actions within said DLL files; a fourth plurality of non-transitory machine readable instructions adapted to be stored in said first computer system comprising a dynamic state machine processor (DSMP) that uses the first data file storing said FSM model elements and said action library to generate the application program executed at run-time, each of the FSM elements is referenced in said first data file including at least one of said markup language descriptions defining functionality of a respective one of said FSM elements, at least some of the markup language descriptions including function calls to said standard actions comprising one or more said identifiers to one or more said standard actions stored in said DLLs within said action library corresponding to basic software functions associated with a control system; and a fifth plurality of non-transitory machine readable instructions comprising an extensible graphic user interface (GUIX) adapted to be stored in said first computer system that provides an interactive control system interface including the end-user interface features to the end-user as generated during run-time by the DSMP based on the action library and the first data file comprising said FSM model elements, wherein said GUIX is operable to generate a plurality of interactive graphical user interface displays based on said first data file, said DSMP, and said action library, where the DSMP performs a lookup of said standard actions stored in said DLL files that are specified in said first data file and generates said plurality of interactive graphical user interfaces based at least in part on data stored in said first data file and retrieved from said action library; wherein the visual interface includes a plurality of editor buttons, activation of which cause the visual interface to display editor windows that permit a technician to build said FSMs within said visual interface by defining or selecting said FSM elements including said state elements, said standard actions associated with said DLL files stored in said action library, and said transition elements as well as define or modify functionality of the FSM elements, the markup language descriptions of the functionality being stored in a database in said second computer comprising at least one said first data file; wherein the visual interface includes a controller, a state machine GUI and a state machine layout system, the state machine GUI and the state machine layout system being configured to generate a graphic representation of the FSM model on the workspace according to a current state of the FSM model provided by the controller.
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1. A computer implemented system for developing an application program having functionality that corresponds to a finite state machine (FSM) model, including: a first plurality of non-transitory machine readable instructions adapted to be stored on a first computer comprising an action library including a plurality of dynamic link library (DLL) files operable to execute a plurality of functions comprising one or more standard actions associated with a plurality of potential FSM models; a second plurality of non-transitory machine readable instructions adapted to be stored in a second computer system operable to generate a visual interface that generates a graphical environment on a display associated with said second computer system, the graphic environment including a workspace for creating and displaying an FSM model representing functionality of an application program, the FSM model including a plurality of elements including state elements, said standard actions, and transition elements connecting the state elements, wherein said visual interface further is adapted to output a first data file that is adapted to be output from said second computer and stored in said first computer comprising a third plurality of non-transitory machine readable instructions comprising one or more specifications of a generated said FSM model which includes markup language descriptions comprising one or more identifiers for said plurality of functions associated with said one or more standard actions within said DLL files; a fourth plurality of non-transitory machine readable instructions adapted to be stored in said first computer system comprising a dynamic state machine processor (DSMP) that uses the first data file storing said FSM model elements and said action library to generate the application program executed at run-time, each of the FSM elements is referenced in said first data file including at least one of said markup language descriptions defining functionality of a respective one of said FSM elements, at least some of the markup language descriptions including function calls to said standard actions comprising one or more said identifiers to one or more said standard actions stored in said DLLs within said action library corresponding to basic software functions associated with a control system; and a fifth plurality of non-transitory machine readable instructions comprising an extensible graphic user interface (GUIX) adapted to be stored in said first computer system that provides an interactive control system interface including the end-user interface features to the end-user as generated during run-time by the DSMP based on the action library and the first data file comprising said FSM model elements, wherein said GUIX is operable to generate a plurality of interactive graphical user interface displays based on said first data file, said DSMP, and said action library, where the DSMP performs a lookup of said standard actions stored in said DLL files that are specified in said first data file and generates said plurality of interactive graphical user interfaces based at least in part on data stored in said first data file and retrieved from said action library; wherein the visual interface includes a plurality of editor buttons, activation of which cause the visual interface to display editor windows that permit a technician to build said FSMs within said visual interface by defining or selecting said FSM elements including said state elements, said standard actions associated with said DLL files stored in said action library, and said transition elements as well as define or modify functionality of the FSM elements, the markup language descriptions of the functionality being stored in a database in said second computer comprising at least one said first data file; wherein the visual interface includes a controller, a state machine GUI and a state machine layout system, the state machine GUI and the state machine layout system being configured to generate a graphic representation of the FSM model on the workspace according to a current state of the FSM model provided by the controller. 3. The system of claim 1 wherein the DSMP generates instructions for the GUIX and posts the messages in a storage location that is accessible by the GUIX during run-time.
| 0.774536 |
8,756,229 | 1 | 17 |
1. An apparatus for information retrieval, comprising: a computer system including a computer processor being programmed to receive a query from a remotely located user system via a network, the query specifying one or more numerical data constraints, and contextual constraints; said computer system including a memory storing a computer-searchable electronic index, the index comprising a plurality of entries, each of the index entries representing an item of numerical data extracted from at least one of a plurality of electronic source documents including one or more natural language documents, wherein the item of numerical data comprises a numerical value, a prefix corresponding to a degree of significant digits, and a unit of measure; said computer system processor being further programmed to determine the relevancy of the query to each of one or more of the index entries based at least partly on a comparison between the numerical data constraint and the index entry's item of numerical data, at least partly on a comparison between the contextual constraint and contextual information extracted from the corresponding source document from which the index entry's item of numerical data was extracted, and at least partly on an evaluation of at least one positional relationship between the index entry's item of numerical data and the contextual information within a given source document, and generate a response to the query based on the relevancy.
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1. An apparatus for information retrieval, comprising: a computer system including a computer processor being programmed to receive a query from a remotely located user system via a network, the query specifying one or more numerical data constraints, and contextual constraints; said computer system including a memory storing a computer-searchable electronic index, the index comprising a plurality of entries, each of the index entries representing an item of numerical data extracted from at least one of a plurality of electronic source documents including one or more natural language documents, wherein the item of numerical data comprises a numerical value, a prefix corresponding to a degree of significant digits, and a unit of measure; said computer system processor being further programmed to determine the relevancy of the query to each of one or more of the index entries based at least partly on a comparison between the numerical data constraint and the index entry's item of numerical data, at least partly on a comparison between the contextual constraint and contextual information extracted from the corresponding source document from which the index entry's item of numerical data was extracted, and at least partly on an evaluation of at least one positional relationship between the index entry's item of numerical data and the contextual information within a given source document, and generate a response to the query based on the relevancy. 17. The information retrieval apparatus of claim 1 , wherein the contextual constraint in the query comprises one or more keywords.
| 0.855727 |
8,601,370 | 15 | 28 |
15. A non-transitory computer readable storage medium comprising computer readable instructions for moving an icon on a display of a computing device between a plurality of folder views, each said plurality of folder views displaying the contents of a respective folder on said display, said computer readable medium comprising instructions for: providing one or more application icons on said display in a current folder view, and at least one other icon being either a folder icon configured to enable movement into a corresponding folder view or an escape icon configured to enable movement out of said current folder view; enabling a focus to be placed on a first icon in said current folder view using a positioning device, said first icon being one of said plurality of icons; upon receiving a first input for selecting said first icon, displaying a menu within said current folder view and enabling selection of a move option from said menu; upon receiving a second input selecting said move option from said menu, returning to said current folder view by removing said menu from said display, providing a visual cue associated with said first icon to indicate that said move option has been selected for said first icon, and then enabling movement of said first icon on said display within said current folder view using said positioning device; upon the first icon overlaying a second icon, said second icon being one of said at least one other icon, visually distinguishing from a move relative to said one or more application icons by changing said visual cue to indicate that a third input will cause said first icon to be moved into or out of said current folder view; and upon receiving said third input: if said second icon is said folder icon, moving said first icon into said corresponding folder view, and updating said display to show the contents of said corresponding folder view while continuing to enable said first icon to be moved within said corresponding folder view to a desired location; and if said second icon is said escape icon, moving said first icon out of said current folder view, and updating said display to show the contents of said corresponding folder view while continuing to enable said first icon to be moved within said corresponding folder view to a desired location.
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15. A non-transitory computer readable storage medium comprising computer readable instructions for moving an icon on a display of a computing device between a plurality of folder views, each said plurality of folder views displaying the contents of a respective folder on said display, said computer readable medium comprising instructions for: providing one or more application icons on said display in a current folder view, and at least one other icon being either a folder icon configured to enable movement into a corresponding folder view or an escape icon configured to enable movement out of said current folder view; enabling a focus to be placed on a first icon in said current folder view using a positioning device, said first icon being one of said plurality of icons; upon receiving a first input for selecting said first icon, displaying a menu within said current folder view and enabling selection of a move option from said menu; upon receiving a second input selecting said move option from said menu, returning to said current folder view by removing said menu from said display, providing a visual cue associated with said first icon to indicate that said move option has been selected for said first icon, and then enabling movement of said first icon on said display within said current folder view using said positioning device; upon the first icon overlaying a second icon, said second icon being one of said at least one other icon, visually distinguishing from a move relative to said one or more application icons by changing said visual cue to indicate that a third input will cause said first icon to be moved into or out of said current folder view; and upon receiving said third input: if said second icon is said folder icon, moving said first icon into said corresponding folder view, and updating said display to show the contents of said corresponding folder view while continuing to enable said first icon to be moved within said corresponding folder view to a desired location; and if said second icon is said escape icon, moving said first icon out of said current folder view, and updating said display to show the contents of said corresponding folder view while continuing to enable said first icon to be moved within said corresponding folder view to a desired location. 28. The non-transitory computer readable storage medium according to claim 15 wherein if said second icon is said folder icon, said computer readable storage medium executes instructions for overlaying an addition symbol on said folder icon.
| 0.681217 |
9,055,509 | 17 | 19 |
17. A method of processing text messages in a mobile environment, the method comprising: processing user text messages in a user messaging session with a mobile messaging application; characterizing a user cognitive load with a user state model based upon situational parameters, including vehicle sensor information for a vehicle driven by a user, wherein the situational parameters are dependent upon user action, wherein the situational parameters include passenger compartment environment and vehicle speed, determining a plurality of distraction levels from the situational parameters, wherein each of the plurality of distraction levels corresponds to the cognitive load of the user; wherein a first one of the distraction levels is based upon a first one of the situational parameters corresponding to the passenger compartment environment and a second one of the distraction levels is based upon the vehicle speed; and adjusting functional performance of the mobile messaging application based on the distraction levels, such that a first one of the plurality of distraction levels corresponds to no message playback at all and a second one of the plurality of distraction levels corresponds to not playing back a message having a low priority.
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17. A method of processing text messages in a mobile environment, the method comprising: processing user text messages in a user messaging session with a mobile messaging application; characterizing a user cognitive load with a user state model based upon situational parameters, including vehicle sensor information for a vehicle driven by a user, wherein the situational parameters are dependent upon user action, wherein the situational parameters include passenger compartment environment and vehicle speed, determining a plurality of distraction levels from the situational parameters, wherein each of the plurality of distraction levels corresponds to the cognitive load of the user; wherein a first one of the distraction levels is based upon a first one of the situational parameters corresponding to the passenger compartment environment and a second one of the distraction levels is based upon the vehicle speed; and adjusting functional performance of the mobile messaging application based on the distraction levels, such that a first one of the plurality of distraction levels corresponds to no message playback at all and a second one of the plurality of distraction levels corresponds to not playing back a message having a low priority. 19. A method according to claim 17 , wherein the mobile environment is the passenger compartment of an automobile.
| 0.733645 |
9,645,999 | 1 | 2 |
1. A method of modifying semantic similarity graphs representative of pair-wise similarity between documents in a corpus, the method comprising: obtaining, with one or more processors, a semantic similarity graph that comprises more than 500 nodes and more than 1000 weighted edges, each node representing a document of a corpus, and each edge weight indicating an amount of similarity between a pair of documents corresponding to the respective nodes connected by the respective edge; after obtaining the semantic similarity graph, obtaining, with one or more processors, a n-gram indicating a request that edge weights affected by the n-gram are to be increased or decreased; expanding, with one or more processors, the n-gram to produce a set of expansion n-grams, wherein expanding the n-gram comprises: determining which documents in at least part of the corpus contain the n-gram to form a first set of documents; determining which documents in at least part of the corpus do not contain the n-gram to form a second set of documents, the first set of documents and the second set of documents each including more than 20 documents; selecting a set of candidate n-grams from the first set of documents, the set of candidate n-grams having more than five n-grams; determining an amount of times each candidate n-gram occurs in the first set of documents to form a first amount; determining an amount of times each candidate n-gram occurs in the second set of documents to form a second amount; determining, for each of the candidate n-grams, a candidate n-gram score based on the first amount and the second amount, wherein the candidate n-gram scores tends to increase or decrease as a ratio of the first amount to the second amount increases or decreases; and selecting expansion n-grams based on the candidate n-gram scores, the expansion n-grams and n-gram collectively forming an adjustment n-gram set; adjusting, with one or more processors, edge weights of the semantic similarity graph of edges between pairs of documents in which members of the adjustment n-gram set co-occur in response to determining that the respective documents contain a member of the adjustment n-gram set, wherein the expansion n-grams are inferred to be conceptually related to the obtained n-gram indicating the request, and wherein the expansion n-grams cause the adjustment of edge weights to be a more comprehensive response to the request than an adjustment based solely on the obtained n-gram indicating the request; and storing the adjusted weights in memory.
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1. A method of modifying semantic similarity graphs representative of pair-wise similarity between documents in a corpus, the method comprising: obtaining, with one or more processors, a semantic similarity graph that comprises more than 500 nodes and more than 1000 weighted edges, each node representing a document of a corpus, and each edge weight indicating an amount of similarity between a pair of documents corresponding to the respective nodes connected by the respective edge; after obtaining the semantic similarity graph, obtaining, with one or more processors, a n-gram indicating a request that edge weights affected by the n-gram are to be increased or decreased; expanding, with one or more processors, the n-gram to produce a set of expansion n-grams, wherein expanding the n-gram comprises: determining which documents in at least part of the corpus contain the n-gram to form a first set of documents; determining which documents in at least part of the corpus do not contain the n-gram to form a second set of documents, the first set of documents and the second set of documents each including more than 20 documents; selecting a set of candidate n-grams from the first set of documents, the set of candidate n-grams having more than five n-grams; determining an amount of times each candidate n-gram occurs in the first set of documents to form a first amount; determining an amount of times each candidate n-gram occurs in the second set of documents to form a second amount; determining, for each of the candidate n-grams, a candidate n-gram score based on the first amount and the second amount, wherein the candidate n-gram scores tends to increase or decrease as a ratio of the first amount to the second amount increases or decreases; and selecting expansion n-grams based on the candidate n-gram scores, the expansion n-grams and n-gram collectively forming an adjustment n-gram set; adjusting, with one or more processors, edge weights of the semantic similarity graph of edges between pairs of documents in which members of the adjustment n-gram set co-occur in response to determining that the respective documents contain a member of the adjustment n-gram set, wherein the expansion n-grams are inferred to be conceptually related to the obtained n-gram indicating the request, and wherein the expansion n-grams cause the adjustment of edge weights to be a more comprehensive response to the request than an adjustment based solely on the obtained n-gram indicating the request; and storing the adjusted weights in memory. 2. The method of claim 1 , where adjusting comprises: influencing the semantic similarity graph based on user-supplied n-grams that indicate aspects of the semantic similarity graph for which the user requests modification.
| 0.897045 |
9,922,645 | 1 | 4 |
1. A computer-implemented method comprising: receiving, by a computing device that includes (i) a text-to-speech engine, (ii) an automated speech recognizer, and (iii) a barge-in detection model that is trained to output an indication of whether given audio data comprises synthesized speech, an audio signal corresponding to a user's utterance that is spoken while the computing device is outputting synthesized speech; processing, using the barge-in detection model that is trained to output an indication of whether given audio data comprises synthesized speech, particular audio data that comprises data corresponding to the audio signal and data corresponding to the synthesized speech; in response to receiving an indication from the barge-in model that the particular audio data comprises synthesized speech, suppressing a further output of the text-to-speech engine; and outputting, by the automated speech recognizer, a transcription of the user's utterance without the synthesized speech.
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1. A computer-implemented method comprising: receiving, by a computing device that includes (i) a text-to-speech engine, (ii) an automated speech recognizer, and (iii) a barge-in detection model that is trained to output an indication of whether given audio data comprises synthesized speech, an audio signal corresponding to a user's utterance that is spoken while the computing device is outputting synthesized speech; processing, using the barge-in detection model that is trained to output an indication of whether given audio data comprises synthesized speech, particular audio data that comprises data corresponding to the audio signal and data corresponding to the synthesized speech; in response to receiving an indication from the barge-in model that the particular audio data comprises synthesized speech, suppressing a further output of the text-to-speech engine; and outputting, by the automated speech recognizer, a transcription of the user's utterance without the synthesized speech. 4. The method of claim 1 , wherein suppressing the further output of the text-to-speech engine comprises initiating a reduction in an audio output level of the text-to-speech engine.
| 0.814286 |
10,042,884 | 1 | 20 |
1. A computer-implemented method comprising: receiving an expression in a query language, the expression having a query language construct representing an algebraic data type, wherein the expression specifies two or more alternative subtypes; generating, for each of the alternative subtypes, a respective domain relation having domain tuples that satisfy a definition of the alternative subtype within the expression; generating a respective domain id relation for each of the domain relations of the alternative subtypes, wherein the domain id relation for a corresponding domain relation of an alternative subtype has domain id tuples that each assign a respective unique domain identifier to each of the domain tuples belonging to the corresponding domain relation of the alternative subtype; generating a union relation for the algebraic data type, wherein the union relation assigns a respective branch identifier to each of the two or more alternative subtypes and, for each of the domain id relations, defines union tuples that each have i) a respective unique domain identifier of a domain id tuple of the corresponding domain id relation and ii) a branch identifier for the alternative subtype to which the domain id relation belongs; assigning unique union identifiers to each of the union tuples belonging to the union relation; generating a respective injector relation for each of the alternative subtypes, wherein each injector relation for an alternative subtype has injector tuples, each injector tuple having i) a first element from a particular domain tuple of the domain relation for the alternative subtype and ii) a union identifier assigned to a union tuple having (a) a unique domain identifier of the particular domain tuple according to the domain id relation for the alternative subtype and (b) a branch identifier for the alternative subtype; receiving a query referencing a variable having the algebraic data type, the algebraic data type having the two or more alternative subtypes; computing query results for the query including identifying one or more injector tuples that satisfy the query, each injector tuple satisfying the query belonging to one of the injector relations generated for the two or more alternative subtypes of the algebraic data type referenced by the query; and providing the computed query results in response to receiving the query.
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1. A computer-implemented method comprising: receiving an expression in a query language, the expression having a query language construct representing an algebraic data type, wherein the expression specifies two or more alternative subtypes; generating, for each of the alternative subtypes, a respective domain relation having domain tuples that satisfy a definition of the alternative subtype within the expression; generating a respective domain id relation for each of the domain relations of the alternative subtypes, wherein the domain id relation for a corresponding domain relation of an alternative subtype has domain id tuples that each assign a respective unique domain identifier to each of the domain tuples belonging to the corresponding domain relation of the alternative subtype; generating a union relation for the algebraic data type, wherein the union relation assigns a respective branch identifier to each of the two or more alternative subtypes and, for each of the domain id relations, defines union tuples that each have i) a respective unique domain identifier of a domain id tuple of the corresponding domain id relation and ii) a branch identifier for the alternative subtype to which the domain id relation belongs; assigning unique union identifiers to each of the union tuples belonging to the union relation; generating a respective injector relation for each of the alternative subtypes, wherein each injector relation for an alternative subtype has injector tuples, each injector tuple having i) a first element from a particular domain tuple of the domain relation for the alternative subtype and ii) a union identifier assigned to a union tuple having (a) a unique domain identifier of the particular domain tuple according to the domain id relation for the alternative subtype and (b) a branch identifier for the alternative subtype; receiving a query referencing a variable having the algebraic data type, the algebraic data type having the two or more alternative subtypes; computing query results for the query including identifying one or more injector tuples that satisfy the query, each injector tuple satisfying the query belonging to one of the injector relations generated for the two or more alternative subtypes of the algebraic data type referenced by the query; and providing the computed query results in response to receiving the query. 20. The method of claim 1 , further comprising: receiving a segment of source code having an argument variable of the algebraic data type, the segment comprising one or more statements in the query language, and wherein the segment includes a first statement that references the argument variable using a first injector relation for a first alternative subtype of the two or more alternative subtypes and a second statement that references the variable using a second injector relation for a second alternative subtype of the two or more alternative subtypes; and evaluating the segment of source code including assigning, to the argument variable, injector tuples belonging to the first injector relation or the second injector relation.
| 0.5 |
7,870,612 | 1 | 10 |
1. An antivirus protection system for computers, comprising: a Process Behavior-Evaluating Unit for identifying programs existing in a user's computer and classifying the programs as normal programs or suspect programs; a Program-Monitoring Unit for monitoring and recording actions and/or behaviors of the programs; a Correlation-Analyzing Unit for creating correlative trees and analyzing correlations of actions and/or behaviors of programs, the correlative trees comprising a process tree and a file tree, wherein each node in said process tree represents a process, and stores action and/or behavior information of the respective process during running and index information of the process in the file tree, and further each node has a parent node corresponding to the parent process of the process corresponding the node, and wherein, in the file tree, each node represents a program, and stores information when the program file is created and index information in the process tree, and further each node has a parent node corresponding to the parent process of the process corresponding the node; a Virus-Identifying Knowledge Base, comprising a Program-Behavior Knowledge Base and a Database of Attack-Identifying Rules, wherein the Program-Behavior Knowledge Base stores correlation behaviors of the normal programs and the Database of Attack-Identifying Rules stores correlation behaviors of the suspect programs; and a Virus-Identifying Unit for receiving program actions and/or behaviors captured by the Program-Monitoring Unit, when the program actions and/or behaviors are dangerous actions, calling the correlation-Analyzing Unit to create correlation behavior according to the process tree and the file tree, if the program is a normal program according to the Process Behavior-Evaluating Unit, comparing the captured actions and/or behaviors to information stored in the Program-Behavior Knowledge Base, and if the program is a suspect program, comparing the captured actions and/or behaviors to information stored in the Database of Attack-Identifying Rules to determine whether the program is a virus in dependence on the comparison.
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1. An antivirus protection system for computers, comprising: a Process Behavior-Evaluating Unit for identifying programs existing in a user's computer and classifying the programs as normal programs or suspect programs; a Program-Monitoring Unit for monitoring and recording actions and/or behaviors of the programs; a Correlation-Analyzing Unit for creating correlative trees and analyzing correlations of actions and/or behaviors of programs, the correlative trees comprising a process tree and a file tree, wherein each node in said process tree represents a process, and stores action and/or behavior information of the respective process during running and index information of the process in the file tree, and further each node has a parent node corresponding to the parent process of the process corresponding the node, and wherein, in the file tree, each node represents a program, and stores information when the program file is created and index information in the process tree, and further each node has a parent node corresponding to the parent process of the process corresponding the node; a Virus-Identifying Knowledge Base, comprising a Program-Behavior Knowledge Base and a Database of Attack-Identifying Rules, wherein the Program-Behavior Knowledge Base stores correlation behaviors of the normal programs and the Database of Attack-Identifying Rules stores correlation behaviors of the suspect programs; and a Virus-Identifying Unit for receiving program actions and/or behaviors captured by the Program-Monitoring Unit, when the program actions and/or behaviors are dangerous actions, calling the correlation-Analyzing Unit to create correlation behavior according to the process tree and the file tree, if the program is a normal program according to the Process Behavior-Evaluating Unit, comparing the captured actions and/or behaviors to information stored in the Program-Behavior Knowledge Base, and if the program is a suspect program, comparing the captured actions and/or behaviors to information stored in the Database of Attack-Identifying Rules to determine whether the program is a virus in dependence on the comparison. 10. The system of claim 1 , wherein the Program-Behavior Knowledge Base is a database configured to analyze and list actions and/or behaviors executed by each of the known programs by hooking the computer's system API functions, and is further configured to store the analysis and list therein; and further wherein the Database of Attack-Identifying Rules is a database configured to record the attacking behavior features of computer viruses, worms, and/or other harmful programs, each record in the Database of Attack-Identifying Rules corresponding to a type of virus, each type of viruses corresponding to an action collection which comprises a series of actions and the correlations between the actions.
| 0.799774 |
7,526,424 | 66 | 68 |
66. The system of claim 65 wherein the global movement component is configured to determine whether each child node is to be moved to depend from a different ancestor node and, if so, re-ordering the child node to depend from the different ancestor node.
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66. The system of claim 65 wherein the global movement component is configured to determine whether each child node is to be moved to depend from a different ancestor node and, if so, re-ordering the child node to depend from the different ancestor node. 68. The system of claim 66 wherein the global movement component is configured to identify raising verbs and raise subjects of the identified raising verbs.
| 0.795276 |
7,917,528 | 11 | 12 |
11. The system of claim 10 , wherein the refinement engine reorders or filters the retrieved one or more refinements based on the context.
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11. The system of claim 10 , wherein the refinement engine reorders or filters the retrieved one or more refinements based on the context. 12. The system of claim 11 , wherein the one or more refinements are reordered based on quality of results associated with the retrieved refinements, respectively.
| 0.528902 |
8,620,658 | 17 | 18 |
17. An information processing apparatus, comprising: a recognition word dictionary generating unit that acquires, from a search server, a search keyword list containing the search keywords searched by the search server and rank information associated with the search keyword list to generate a recognition word dictionary containing words for use in speech recognition; a broadcast audio information receiving unit that receives broadcast audio information transmitted from a broadcasting station; a speech recognition unit that performs speech recognition on the broadcast audio information by referencing a recognition database containing the recognition word dictionary; a keyword detection unit that detects predetermined keywords from the result of the speech recognition on the broadcast audio information; and an external display device connection control unit that performs connection control with an external display device and outputs the keywords detected from the broadcast audio information to the external display device, wherein the search server represents a website that provides a keyword search service and a directory search service so that a user uses the search server to search for information available through Internet.
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17. An information processing apparatus, comprising: a recognition word dictionary generating unit that acquires, from a search server, a search keyword list containing the search keywords searched by the search server and rank information associated with the search keyword list to generate a recognition word dictionary containing words for use in speech recognition; a broadcast audio information receiving unit that receives broadcast audio information transmitted from a broadcasting station; a speech recognition unit that performs speech recognition on the broadcast audio information by referencing a recognition database containing the recognition word dictionary; a keyword detection unit that detects predetermined keywords from the result of the speech recognition on the broadcast audio information; and an external display device connection control unit that performs connection control with an external display device and outputs the keywords detected from the broadcast audio information to the external display device, wherein the search server represents a website that provides a keyword search service and a directory search service so that a user uses the search server to search for information available through Internet. 18. The information processing apparatus according to claim 17 , wherein the broadcast audio information receiving unit acquires reception channel information concerning a broadcast channel through which the external display device is receiving and the broadcast audio information corresponding to the broadcast channel from the external display device connected to the information processing apparatus.
| 0.546171 |
9,576,495 | 1 | 11 |
1. A computerized teaching system for providing an in-class assessment for evaluating one or more students to determine whether the one or more students are learning STEM principles being taught by a teacher in a class, the system comprising: a communications network; at least one teacher computer; and at least one student computer; wherein each of the at least one teacher computer and the at least one student computer includes an input device and a touch sensitive screen for receiving handwritten input via the input device; wherein the at least one student computer is operably connected to the at least one teacher computer via the communications network; wherein the at least one teacher computer includes a computer-readable storage medium containing program instructions for implementing a teacher administered assessment application comprising one or more program instructions for performing the steps of: receiving at least one question description handwritten by the teacher in math notation on the screen of the at least one teacher computer; storing the at least one question description; receiving at least one correct answer corresponding to the at least one question description, the at least one correct answer being handwritten by the teacher in math notation on the screen of the at least one teacher computer; storing the at least one correct answer; receiving at least one student response from the at least one student computer via the communications network, the at least one student response being input by the student by handwriting the at least one student response in math notation on the screen of the at least one student computer; reading and interpreting the at least one student response; comparing the at least one student response to the at least one correct answer corresponding to the at least one question description, the comparing step including the sub-step of automatically evaluating whether the at least one student response handwritten in math notation is algebraically equivalent to the at least one correct answer handwritten in math notation; and if the at least one student response includes a plurality of student responses, determining and displaying the number of student responses of the plurality of student responses which are correct on the screen of the at least one teacher computer.
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1. A computerized teaching system for providing an in-class assessment for evaluating one or more students to determine whether the one or more students are learning STEM principles being taught by a teacher in a class, the system comprising: a communications network; at least one teacher computer; and at least one student computer; wherein each of the at least one teacher computer and the at least one student computer includes an input device and a touch sensitive screen for receiving handwritten input via the input device; wherein the at least one student computer is operably connected to the at least one teacher computer via the communications network; wherein the at least one teacher computer includes a computer-readable storage medium containing program instructions for implementing a teacher administered assessment application comprising one or more program instructions for performing the steps of: receiving at least one question description handwritten by the teacher in math notation on the screen of the at least one teacher computer; storing the at least one question description; receiving at least one correct answer corresponding to the at least one question description, the at least one correct answer being handwritten by the teacher in math notation on the screen of the at least one teacher computer; storing the at least one correct answer; receiving at least one student response from the at least one student computer via the communications network, the at least one student response being input by the student by handwriting the at least one student response in math notation on the screen of the at least one student computer; reading and interpreting the at least one student response; comparing the at least one student response to the at least one correct answer corresponding to the at least one question description, the comparing step including the sub-step of automatically evaluating whether the at least one student response handwritten in math notation is algebraically equivalent to the at least one correct answer handwritten in math notation; and if the at least one student response includes a plurality of student responses, determining and displaying the number of student responses of the plurality of student responses which are correct on the screen of the at least one teacher computer. 11. The system according to claim 1 , wherein the at least one teacher computer and the at least one student computer are situated in separate locations.
| 0.747525 |
7,853,577 | 12 | 18 |
12. A system, comprising: a processor; a memory coupled to the processor for storing context data; a context module to receive from a client, context data associated with a context and a user, the context data including information indicative of a category of offerings in a network-based marketplace, the context data identifying at least one category of products or services, the context module further to automatically discover context attributes associated with the context, the context attributes being automatically discovered by processing attribute data received from a plurality of other users, the attribute data being related to the at least one category of products or services, and the context module to associate the context data and the context attributes with a user identifier corresponding to the user; a filtering module to retrieve data associated with the context and to filter the data according to the context data and the context attributes, the filtering module being further configured to filter the data according to one or more ratings associated with products or services included in the result data; and a results module to create result data relevant to the user identified by the user identifier and to communicate the result data to the client, the context module, the filtering module, and the results module being executable by the processor.
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12. A system, comprising: a processor; a memory coupled to the processor for storing context data; a context module to receive from a client, context data associated with a context and a user, the context data including information indicative of a category of offerings in a network-based marketplace, the context data identifying at least one category of products or services, the context module further to automatically discover context attributes associated with the context, the context attributes being automatically discovered by processing attribute data received from a plurality of other users, the attribute data being related to the at least one category of products or services, and the context module to associate the context data and the context attributes with a user identifier corresponding to the user; a filtering module to retrieve data associated with the context and to filter the data according to the context data and the context attributes, the filtering module being further configured to filter the data according to one or more ratings associated with products or services included in the result data; and a results module to create result data relevant to the user identified by the user identifier and to communicate the result data to the client, the context module, the filtering module, and the results module being executable by the processor. 18. The system of claim 12 , wherein the results module is to associate an advertisement from a third party pertaining to a context and to provide the advertisement to a user interface of the user.
| 0.571739 |
9,208,509 | 8 | 9 |
8. The computer program of claim 1 , further including storing the size of the working vocabulary of the user in the profile of the user.
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8. The computer program of claim 1 , further including storing the size of the working vocabulary of the user in the profile of the user. 9. The computer program of claim 8 , wherein the content is personalized by identifying the size of the working vocabulary of the user from the profile of the user.
| 0.5 |
9,055,147 | 12 | 13 |
12. The method of claim 1 , wherein the generic prompt is defined for a plurality of prompt suites.
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12. The method of claim 1 , wherein the generic prompt is defined for a plurality of prompt suites. 13. The method of claim 12 , wherein the specific prompt is defined for a corresponding particular prompt suite of the plurality of prompt suites.
| 0.5 |
8,656,276 | 9 | 12 |
9. An image forming apparatus, comprising: an accepting unit that accepts a copying instruction to copy a first medium, the first medium comprising a first page of the first medium having printed thereon an image of a first page of an electronic document and a second page of the first medium having printed thereon an image of a second page of the electronic document; an image reading unit that reads the image of the first page of the electronic document and the second page of the electronic document from the first page and the second page of the first medium in compliance with the copying instruction; a layout acquisition unit that acquires layout information when the image of the first page of the electronic document and the image of a second page of the electronic document are to be formed on a second medium, the layout information indicating an n-up arrangement in which the first page of the electronic document is to be printed on a single page of the second medium and the second page of the electronic document is to be printed on the single page of the second medium; a print unit that forms the image of the first page of the electronic document and the image of the second page of the electronic document on the single page of the second medium in the n-up arrangement on the basis of the layout information; an information generation unit that generates correspondent information comprising a first coordinate position on the second medium at which the image of the first page of the electronic document is to be printed and a second coordinate position on the second medium at which the image of the second page of the electronic document is to be printed, on the basis of the n-up arrangement of the first page of the electronic document and the second page of the electronic document on the single page of medium indicated by layout information; and a management unit that receives a request from a pen device to modify the electronic document, the request comprising a position of the pen device on the single page of the second medium having the first page of the electronic document and the second page of the electronic document printed thereon at which an annotation is added to the single page of the second medium, the annotation comprising a character or a pattern recorded on the single page of medium by the pen device, determines a position on one of the first page of the electronic document and the second page of the electronic document at which the annotation is added based on the position on the single page of the second medium and the correspondent information, and modifies the electronic document to include the annotation at the position on the one of the first page of the electronic document and the second page of the electronic document.
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9. An image forming apparatus, comprising: an accepting unit that accepts a copying instruction to copy a first medium, the first medium comprising a first page of the first medium having printed thereon an image of a first page of an electronic document and a second page of the first medium having printed thereon an image of a second page of the electronic document; an image reading unit that reads the image of the first page of the electronic document and the second page of the electronic document from the first page and the second page of the first medium in compliance with the copying instruction; a layout acquisition unit that acquires layout information when the image of the first page of the electronic document and the image of a second page of the electronic document are to be formed on a second medium, the layout information indicating an n-up arrangement in which the first page of the electronic document is to be printed on a single page of the second medium and the second page of the electronic document is to be printed on the single page of the second medium; a print unit that forms the image of the first page of the electronic document and the image of the second page of the electronic document on the single page of the second medium in the n-up arrangement on the basis of the layout information; an information generation unit that generates correspondent information comprising a first coordinate position on the second medium at which the image of the first page of the electronic document is to be printed and a second coordinate position on the second medium at which the image of the second page of the electronic document is to be printed, on the basis of the n-up arrangement of the first page of the electronic document and the second page of the electronic document on the single page of medium indicated by layout information; and a management unit that receives a request from a pen device to modify the electronic document, the request comprising a position of the pen device on the single page of the second medium having the first page of the electronic document and the second page of the electronic document printed thereon at which an annotation is added to the single page of the second medium, the annotation comprising a character or a pattern recorded on the single page of medium by the pen device, determines a position on one of the first page of the electronic document and the second page of the electronic document at which the annotation is added based on the position on the single page of the second medium and the correspondent information, and modifies the electronic document to include the annotation at the position on the one of the first page of the electronic document and the second page of the electronic document. 12. The image forming apparatus as defined in claim 9 , wherein the layout information is an angle of rotation to which the image of the first page of the electronic document is subjected when the image of the first page of the electronic document is formed on the single page of the second medium.
| 0.5 |
8,488,886 | 1 | 3 |
1. A method, comprising: receiving, by at least one computing device, a glyph; reducing, by the at least one computing device, the received glyph to a predefined format; normalizing, by the at least one computing device, the reduced glyph; comparing, by the at least one computing device, the normalized glyph to a plurality of image prototypes; and outputting, by the at least one computing device, at least one of the plurality of image prototypes based on the comparison of the normalized glyph to the plurality of image prototypes, wherein comparing the normalized glyph to the plurality of image prototypes includes: determining a number of rows in the normalized glyph and a number of rows in a selected one of the plurality of image prototypes; for the lesser of the number of rows in the normalized glyph and the number of rows in the selected one of the plurality of image prototypes, exclusive-or'ing (xor'ing) pixels of the normalized glyph with corresponding pixels of the selected one of the plurality of image prototypes; accumulating a result of the xor'ing of the pixels of the normalized glyph with the corresponding pixels of the selected one of the plurality of image prototypes; for each row of the normalized glyph and the selected one of the plurality of image prototypes that was not xor'ed, adding to the result a number corresponding to the number of pixels ‘on’ in the normalized glyph or the selected one of the plurality of image prototypes; and saving the added result.
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1. A method, comprising: receiving, by at least one computing device, a glyph; reducing, by the at least one computing device, the received glyph to a predefined format; normalizing, by the at least one computing device, the reduced glyph; comparing, by the at least one computing device, the normalized glyph to a plurality of image prototypes; and outputting, by the at least one computing device, at least one of the plurality of image prototypes based on the comparison of the normalized glyph to the plurality of image prototypes, wherein comparing the normalized glyph to the plurality of image prototypes includes: determining a number of rows in the normalized glyph and a number of rows in a selected one of the plurality of image prototypes; for the lesser of the number of rows in the normalized glyph and the number of rows in the selected one of the plurality of image prototypes, exclusive-or'ing (xor'ing) pixels of the normalized glyph with corresponding pixels of the selected one of the plurality of image prototypes; accumulating a result of the xor'ing of the pixels of the normalized glyph with the corresponding pixels of the selected one of the plurality of image prototypes; for each row of the normalized glyph and the selected one of the plurality of image prototypes that was not xor'ed, adding to the result a number corresponding to the number of pixels ‘on’ in the normalized glyph or the selected one of the plurality of image prototypes; and saving the added result. 3. The method of claim 1 , wherein normalizing the reduced glyph comprises normalizing the reduced glyph to a predefined width and a proportional height.
| 0.934949 |
8,768,057 | 1 | 10 |
1. A method of classifying marking types on images of a document, the method comprising: supplying the document containing the images to a segmenter; segmenting the images received by the segmenter including identifying neatly written or printed text by grouping selected feature points along predetermined orientations, the feature points including local extrema of bounding contours of connected components, and subtracting enclosing boundary boxes of text lines from remaining document material to fragment connected components that are part of the text lines and part of extraneous markings; supplying the fragments to a classifier, the classifier providing a category score to each fragment, wherein the classifier is trained from groundtruth images whose pixels are labeled according to known marking types; and assigning a same label to all pixels in a fragment when the fragment is classified by the classifier.
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1. A method of classifying marking types on images of a document, the method comprising: supplying the document containing the images to a segmenter; segmenting the images received by the segmenter including identifying neatly written or printed text by grouping selected feature points along predetermined orientations, the feature points including local extrema of bounding contours of connected components, and subtracting enclosing boundary boxes of text lines from remaining document material to fragment connected components that are part of the text lines and part of extraneous markings; supplying the fragments to a classifier, the classifier providing a category score to each fragment, wherein the classifier is trained from groundtruth images whose pixels are labeled according to known marking types; and assigning a same label to all pixels in a fragment when the fragment is classified by the classifier. 10. The method according to claim 1 , wherein the segmenting includes: grouping the selected feature points into strips; fitting lines to the strips; and forming the enclosing bounding boxes from pairs of fitted lines.
| 0.610714 |
8,347,231 | 6 | 8 |
6. A data processing system that displays tag words for selection by a user engaged in social tagging of content accessible via a communications network, comprising: a display; and a processor in communication with the display that displays a graphical user interface within the display, the graphical user interface comprising: a tag cloud, wherein the tag cloud is a visual representation of an inventory of the tag words, wherein each tag word is a metadata keyword that can be selected and associated with the content by the user, wherein the tag words are displayed alphabetically, and wherein ones of the tag words with higher popularity are displayed in a larger font than ones of the tag words with lesser popularity; a tag word selection field adjacent to the tag cloud, wherein the tag word selection field displays tag words selected by the user from the tag cloud; a long tail tag word inventory curve adjacent to the tag cloud, wherein the long tail tag word inventory curve is a graphical representation of the tag words in the inventory by popularity, wherein the long tail tag word inventory curve includes a head portion, a body portion, and a long tail portion, and wherein the head portion represents an upper percentile of tag word popularity, the body portion represents an intermediate percentile of tag word popularity, and the long tail portion represents a lower percentile of tag word popularity; and a slider control displayed adjacent to the long tail tag word inventory curve, wherein the slider control is operably associated with the tag cloud and with the long tail tag word inventory curve and is responsive to user movement, and wherein movement of the slider control changes a number of the tag words from the inventory displayed in the tag cloud.
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6. A data processing system that displays tag words for selection by a user engaged in social tagging of content accessible via a communications network, comprising: a display; and a processor in communication with the display that displays a graphical user interface within the display, the graphical user interface comprising: a tag cloud, wherein the tag cloud is a visual representation of an inventory of the tag words, wherein each tag word is a metadata keyword that can be selected and associated with the content by the user, wherein the tag words are displayed alphabetically, and wherein ones of the tag words with higher popularity are displayed in a larger font than ones of the tag words with lesser popularity; a tag word selection field adjacent to the tag cloud, wherein the tag word selection field displays tag words selected by the user from the tag cloud; a long tail tag word inventory curve adjacent to the tag cloud, wherein the long tail tag word inventory curve is a graphical representation of the tag words in the inventory by popularity, wherein the long tail tag word inventory curve includes a head portion, a body portion, and a long tail portion, and wherein the head portion represents an upper percentile of tag word popularity, the body portion represents an intermediate percentile of tag word popularity, and the long tail portion represents a lower percentile of tag word popularity; and a slider control displayed adjacent to the long tail tag word inventory curve, wherein the slider control is operably associated with the tag cloud and with the long tail tag word inventory curve and is responsive to user movement, and wherein movement of the slider control changes a number of the tag words from the inventory displayed in the tag cloud. 8. The data processing system of claim 6 , wherein the graphical user interface comprises an additional slider control displayed adjacent to the long tail tag word inventory curve, wherein the additional slider control is operably associated with the tag cloud and with the long tail tag word inventory curve and is responsive to user movement, and wherein movement of the additional slider control changes the number of the tag words displayed in the tag cloud.
| 0.5 |
8,056,128 | 56 | 74 |
56. A system, comprising: a processing unit to: identify a document, from a corpus of ranked documents hosted on one or more servers, as being suspect based on whether the document requests personal or private information from a user, where documents in the corpus of ranked documents that are more well known are ranked higher than documents that are less well known, analyze data or attributes associated with the suspect document by analyzing a ranking of the suspect document relative to other documents from the corpus of ranked documents, assign a fraud score, based on the analyzed data or attributes, to the suspect document that indicates whether the suspect document is potentially fraudulent, and assign a trustworthiness value, based on the fraud score, to the suspect document that indicates a trustworthiness of the suspect document; and a data repository to store, for the suspect document in the corpus of documents: a document identifier, the fraud score, and the trustworthiness value.
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56. A system, comprising: a processing unit to: identify a document, from a corpus of ranked documents hosted on one or more servers, as being suspect based on whether the document requests personal or private information from a user, where documents in the corpus of ranked documents that are more well known are ranked higher than documents that are less well known, analyze data or attributes associated with the suspect document by analyzing a ranking of the suspect document relative to other documents from the corpus of ranked documents, assign a fraud score, based on the analyzed data or attributes, to the suspect document that indicates whether the suspect document is potentially fraudulent, and assign a trustworthiness value, based on the fraud score, to the suspect document that indicates a trustworthiness of the suspect document; and a data repository to store, for the suspect document in the corpus of documents: a document identifier, the fraud score, and the trustworthiness value. 74. The system of claim 56 , where the suspect document is associated with a received electronic message and where, when analyzing data or attributes associated with the suspect document, the processing unit is further to: compare the received electronic message with a content, structure, or appearance of other verified authentic electronic messages.
| 0.5 |
9,400,639 | 1 | 20 |
1. A method for generating a program, comprising: detecting a plurality of steps for performing a task on a computing device and actual input data for the task; detecting an example relating to each of the plurality of steps, wherein the example comprises input data and corresponding output data relating to the step; and for each example, determining a plurality of rules that transform the input data to the corresponding output data based on cues comprising textual features within the input data and cues comprising textual features within the corresponding output data; for each example, ranking the plurality of rules according to a probability that each rule explains a transformation from the input data to the corresponding output data; for each example, specifying a rule to be used for performing a step represented by the example based on the ranking of the plurality of rules; and generating a program for performing the task based on the specified rules.
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1. A method for generating a program, comprising: detecting a plurality of steps for performing a task on a computing device and actual input data for the task; detecting an example relating to each of the plurality of steps, wherein the example comprises input data and corresponding output data relating to the step; and for each example, determining a plurality of rules that transform the input data to the corresponding output data based on cues comprising textual features within the input data and cues comprising textual features within the corresponding output data; for each example, ranking the plurality of rules according to a probability that each rule explains a transformation from the input data to the corresponding output data; for each example, specifying a rule to be used for performing a step represented by the example based on the ranking of the plurality of rules; and generating a program for performing the task based on the specified rules. 20. The method of claim 1 , wherein generating the program comprises enumerating combinations of the rules.
| 0.778926 |
9,875,741 | 1 | 4 |
1. A method for speech recognition in a chat information system (CIS), the method comprising: receiving, by a processor operatively coupled to a memory, an audio input; separating, by the processor, the audio input into a plurality of parts having at least a first part of the audio input and a second part of the audio input; selecting, from a plurality of speech recognizers, a specific first speech recognizer to recognize the first part of the audio input, wherein selecting of the specific first speech recognizer to recognize the first part of the audio input is by the processor and is based on predetermined criteria, wherein each of the plurality of speech recognizers, from which the specific first speech recognizer is selected to recognize the first part of the audio input, is configured to generate, based on a corresponding audio input, a plurality of outputs provided with corresponding confidence levels; recognizing, by the specific first speech recognizer of a plurality of speech recognizers, the first part of the audio input to generate a first recognized input; analyzing, by the processor, the first recognized input associated with the first part of the audio input to identify at least one first trigger in the first recognized input; predicting, by the processor, a type of the second part of the audio input based at least in part on the at least one first trigger; based on the prediction of the type of the second part of the audio input, selecting, by the processor, a specific second speech recognizer from the plurality of speech recognizers; recognizing, by the specific second speech recognizer, the second part of the audio input to generate a second recognized input; analyzing, by the processor, the second recognized input to identify at least one second trigger in the second recognized input; predicting, by the processor, types of further parts of the audio input based at least in part on triggers identified in recognized inputs; selecting, from the plurality of speech recognizers, further specific speech recognizers based on the predicted types of the further parts of the audio input, the further specific speech recognizers being in addition to the first speech recognizer and the second speech recognizer; and recognizing, by the further specific speech recognizers, the further parts of the audio input until all parts of the audio input are recognized.
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1. A method for speech recognition in a chat information system (CIS), the method comprising: receiving, by a processor operatively coupled to a memory, an audio input; separating, by the processor, the audio input into a plurality of parts having at least a first part of the audio input and a second part of the audio input; selecting, from a plurality of speech recognizers, a specific first speech recognizer to recognize the first part of the audio input, wherein selecting of the specific first speech recognizer to recognize the first part of the audio input is by the processor and is based on predetermined criteria, wherein each of the plurality of speech recognizers, from which the specific first speech recognizer is selected to recognize the first part of the audio input, is configured to generate, based on a corresponding audio input, a plurality of outputs provided with corresponding confidence levels; recognizing, by the specific first speech recognizer of a plurality of speech recognizers, the first part of the audio input to generate a first recognized input; analyzing, by the processor, the first recognized input associated with the first part of the audio input to identify at least one first trigger in the first recognized input; predicting, by the processor, a type of the second part of the audio input based at least in part on the at least one first trigger; based on the prediction of the type of the second part of the audio input, selecting, by the processor, a specific second speech recognizer from the plurality of speech recognizers; recognizing, by the specific second speech recognizer, the second part of the audio input to generate a second recognized input; analyzing, by the processor, the second recognized input to identify at least one second trigger in the second recognized input; predicting, by the processor, types of further parts of the audio input based at least in part on triggers identified in recognized inputs; selecting, from the plurality of speech recognizers, further specific speech recognizers based on the predicted types of the further parts of the audio input, the further specific speech recognizers being in addition to the first speech recognizer and the second speech recognizer; and recognizing, by the further specific speech recognizers, the further parts of the audio input until all parts of the audio input are recognized. 4. The method of claim 1 , wherein the at least one first trigger includes a type of the audio input identified based at least in part on the first recognized input.
| 0.616279 |
9,633,116 | 20 | 33 |
20. A non-transitory computer storage medium encoded with instructions that, when executed by one or more computers, cause the one or more computers to perform operations comprising: receiving information characterizing explicit relationships between a first member, a second member, and a third member in a member network; receiving a first search query submitted by the first member; responding to the first search query with a) first links to a collection of articles in a result set responsive to the first search query, and b) one or more second links for receiving input characterizing the first member's ratings of local product or service providers identified in the result set responsive to the first search query; receiving the first member's selection of one of the second links; storing first endorsement information characterizing the first member's rating of an article that corresponds with the selected one of the second links; receiving a third search query submitted by the third member; responding to the third search query with a) third links to a collection of articles in a result set responsive to the third search query, and b) one or more fourth links for receiving input characterizing the third member's ratings of local product or service providers identified in the result set responsive to the third search query; receiving the third member's selection of one of the fourth links; storing second endorsement information characterizing the third member's rating of an article that corresponds with the selected one of the fourth links; receiving, from a second member in the member network, a local search query comprising information identifying one or more items to be found and for a particular geographic locale; determining a result set responsive to the local search query; identifying that there is an association between the first member and the second member, and a second association between the second member and the third member, wherein each of the associations comprises (i) an explicit relationship between the respective two members or (ii) a common membership of the respective two members in a community of the member network; ranking items responsive to the local search query using a type of the association between the second member and the first member in the member network and on a type of the association between the second member and the third member in the member network; and responding to the local search query with information describing a result set responsive to the local search query, the response set including the ranked items, the identity of the first member, the availability of the first endorsement information, the identity of the third member, and the availability of the second endorsement information.
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20. A non-transitory computer storage medium encoded with instructions that, when executed by one or more computers, cause the one or more computers to perform operations comprising: receiving information characterizing explicit relationships between a first member, a second member, and a third member in a member network; receiving a first search query submitted by the first member; responding to the first search query with a) first links to a collection of articles in a result set responsive to the first search query, and b) one or more second links for receiving input characterizing the first member's ratings of local product or service providers identified in the result set responsive to the first search query; receiving the first member's selection of one of the second links; storing first endorsement information characterizing the first member's rating of an article that corresponds with the selected one of the second links; receiving a third search query submitted by the third member; responding to the third search query with a) third links to a collection of articles in a result set responsive to the third search query, and b) one or more fourth links for receiving input characterizing the third member's ratings of local product or service providers identified in the result set responsive to the third search query; receiving the third member's selection of one of the fourth links; storing second endorsement information characterizing the third member's rating of an article that corresponds with the selected one of the fourth links; receiving, from a second member in the member network, a local search query comprising information identifying one or more items to be found and for a particular geographic locale; determining a result set responsive to the local search query; identifying that there is an association between the first member and the second member, and a second association between the second member and the third member, wherein each of the associations comprises (i) an explicit relationship between the respective two members or (ii) a common membership of the respective two members in a community of the member network; ranking items responsive to the local search query using a type of the association between the second member and the first member in the member network and on a type of the association between the second member and the third member in the member network; and responding to the local search query with information describing a result set responsive to the local search query, the response set including the ranked items, the identity of the first member, the availability of the first endorsement information, the identity of the third member, and the availability of the second endorsement information. 33. The computer storage medium of claim 20 , wherein the first member's rating of a first local product or service provider comprises a scaled grade.
| 0.902597 |
8,812,540 | 37 | 40 |
37. A computer system comprising: a client computing device, comprising one or more processors coupled to one or more memories, the one or more processors configured to: based on first content that has been opened within a content presentation application executing on the client computing device, the client computing device automatically selecting context information to submit to a server; responsive to automatically selecting the context information for submission to the server, the client computing device automatically sending the context information from the client computing device to the server; responsive to sending the context information to the server, the client computing device receiving a first search result from the server; responsive to activation input activating a search interface, displaying the search interface; after receiving the activation input, and prior to receiving any user input of a query term via the activated search interface, displaying the first search result within a preview section of the search interface; subsequent to displaying the first search result in the preview section, receiving user input entering one or more query terms via the search interface, the one or more query terms including at least one term that is not found in the context information; sending the one or more query terms to the server; responsive to sending the one or more query terms to the server, the client computing device receiving a second search result from the server; displaying the second search result in the search interface at the client computing device.
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37. A computer system comprising: a client computing device, comprising one or more processors coupled to one or more memories, the one or more processors configured to: based on first content that has been opened within a content presentation application executing on the client computing device, the client computing device automatically selecting context information to submit to a server; responsive to automatically selecting the context information for submission to the server, the client computing device automatically sending the context information from the client computing device to the server; responsive to sending the context information to the server, the client computing device receiving a first search result from the server; responsive to activation input activating a search interface, displaying the search interface; after receiving the activation input, and prior to receiving any user input of a query term via the activated search interface, displaying the first search result within a preview section of the search interface; subsequent to displaying the first search result in the preview section, receiving user input entering one or more query terms via the search interface, the one or more query terms including at least one term that is not found in the context information; sending the one or more query terms to the server; responsive to sending the one or more query terms to the server, the client computing device receiving a second search result from the server; displaying the second search result in the search interface at the client computing device. 40. The system of claim 37 , wherein the context information includes an identifier of a location that contains the first content.
| 0.842233 |
9,721,010 | 1 | 4 |
1. A method of annotating content based upon user reaction data, comprising: detecting first user reaction data associated with a first portion of the content, the detecting including firstly detecting a presence of metadata of the content that specifies a probability of a user reaction to the first portion of the content, secondly, after the detecting, determining whether the probability of a user reaction to the first portion of that content exceeds a threshold, and thirdly, after the detecting and a result of the determining is affirmative, utilizing a first sensor to detect the first user reaction data, so that the first sensor is used to detect the first user reaction data only after a result of the determining is affirmative; and annotating the first portion of the content with a first reaction annotation based upon the first user reaction data.
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1. A method of annotating content based upon user reaction data, comprising: detecting first user reaction data associated with a first portion of the content, the detecting including firstly detecting a presence of metadata of the content that specifies a probability of a user reaction to the first portion of the content, secondly, after the detecting, determining whether the probability of a user reaction to the first portion of that content exceeds a threshold, and thirdly, after the detecting and a result of the determining is affirmative, utilizing a first sensor to detect the first user reaction data, so that the first sensor is used to detect the first user reaction data only after a result of the determining is affirmative; and annotating the first portion of the content with a first reaction annotation based upon the first user reaction data. 4. The method of claim 1 , further comprising: detecting second user reaction data associated with a second portion of the content; and annotating the second portion of the content with a second reaction annotation based upon the second user reaction data.
| 0.651226 |
9,922,643 | 1 | 11 |
1. A method for adapting a phonetic dictionary for peculiarities of a speech of at least one speaker, the method comprising: a. receiving a search term in text form; b. searching for the search term in the phonetic dictionary, wherein if the search term or a portion thereof is included in the phonetic dictionary, obtaining from the phonetic dictionary pronunciation elements corresponding to phonetic elements of the search term or a portion thereof, for serving as search pronunciations of the search term or portion thereof, and if the search term or portion thereof is not included in the phonetic dictionary, generating pronunciation elements corresponding to phonetic elements of the search term or portion thereof with a text to phoneme model (TTP); and concatenating all the obtained and generated pronunciation elements of the search term to form a search pronunciation of the search term; c. searching by the formed search pronunciation for a matching phonetic transcription in an indexed transcriptions database, wherein the indexed transcriptions database stores phonetic transcriptions of a corresponding audio database of recorded human speech; wherein the searching yields a found pronunciation; d. retrieving an audio section corresponding to the matching phonetic transcription of the found pronunciation from the audio database; e. audibly presenting to a person the audio section and tagging the audio section according to its acceptability for pronouncing of the search term to obtain a tagged search result; f. calculating a value of acceptability efficiency level for the found pronunciation, as obtained from the indexed transcriptions database, wherein the value of acceptability determined by the tagging; and g. in case the calculated value of acceptability exceeds a certain threshold value and the found pronunciation, as obtained from the indexed transcriptions database, is not already included in the phonetic dictionary, adding the found pronunciation to the phonetic dictionary; wherein the method is performed on an at least one computerized apparatus configured to perform the method.
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1. A method for adapting a phonetic dictionary for peculiarities of a speech of at least one speaker, the method comprising: a. receiving a search term in text form; b. searching for the search term in the phonetic dictionary, wherein if the search term or a portion thereof is included in the phonetic dictionary, obtaining from the phonetic dictionary pronunciation elements corresponding to phonetic elements of the search term or a portion thereof, for serving as search pronunciations of the search term or portion thereof, and if the search term or portion thereof is not included in the phonetic dictionary, generating pronunciation elements corresponding to phonetic elements of the search term or portion thereof with a text to phoneme model (TTP); and concatenating all the obtained and generated pronunciation elements of the search term to form a search pronunciation of the search term; c. searching by the formed search pronunciation for a matching phonetic transcription in an indexed transcriptions database, wherein the indexed transcriptions database stores phonetic transcriptions of a corresponding audio database of recorded human speech; wherein the searching yields a found pronunciation; d. retrieving an audio section corresponding to the matching phonetic transcription of the found pronunciation from the audio database; e. audibly presenting to a person the audio section and tagging the audio section according to its acceptability for pronouncing of the search term to obtain a tagged search result; f. calculating a value of acceptability efficiency level for the found pronunciation, as obtained from the indexed transcriptions database, wherein the value of acceptability determined by the tagging; and g. in case the calculated value of acceptability exceeds a certain threshold value and the found pronunciation, as obtained from the indexed transcriptions database, is not already included in the phonetic dictionary, adding the found pronunciation to the phonetic dictionary; wherein the method is performed on an at least one computerized apparatus configured to perform the method. 11. The method according to claim 1 , further comprising obtaining or generating multiple search pronunciations for the search term, wherein the number of search pronunciations for the search term is equal to or exceeds a threshold number of pronunciations.
| 0.691106 |
7,849,113 | 11 | 12 |
11. The method of claim 10 , where the query statistics data structure is to store elements comprising an entry to identify a query and an entry to identify a query processing time associated with the query, and where updating the query statistics data structure includes one or more of, adding an element to the query statistics data structure, removing an element from the query statistics data structure, and manipulating an entry identifying a query processing time associated with a query.
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11. The method of claim 10 , where the query statistics data structure is to store elements comprising an entry to identify a query and an entry to identify a query processing time associated with the query, and where updating the query statistics data structure includes one or more of, adding an element to the query statistics data structure, removing an element from the query statistics data structure, and manipulating an entry identifying a query processing time associated with a query. 12. The method of claim 11 , where the query statistics data structure has N elements, N being a pre-determined, configurable number of elements, N being less than three hundred.
| 0.5 |
10,140,456 | 1 | 6 |
1. A computer program product comprising a program stored on a non-transitory computer-readable medium containing an executable set of instructions for detecting a vulnerability in a software application in a database system, the set of instructions operable to: store defined vulnerabilities that identify operations in the software application vulnerable to the security risk and are each associated with one or more input tags and one or more sanitization tags; receive by the software application in the database system a request from a user system; at runtime of the application, assign one or more of the input tags to one or more objects associated with the request, wherein the input tags identify the request as potentially malicious and carrying a security risk; at runtime of the application, assign one or more of the sanitization tags to the one or more objects associated with the request to indicate security checks performed on the objects; at runtime of the application, compare the input tags assigned to the objects with any of the sanitization tags assigned to the objects; and at runtime of the application, identify at least one of the defined vulnerabilities as a vulnerability in a part of the software application when the assigned input tag for an identified one of the objects matches the input tag associated with an identified one of the defined vulnerabilities, and one or more of the sanitization tags associated with the identified one of the defined vulnerabilities is not an assigned sanitization tag for the identified one of the objects; and generating a report identifying the vulnerability in a part of the software application.
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1. A computer program product comprising a program stored on a non-transitory computer-readable medium containing an executable set of instructions for detecting a vulnerability in a software application in a database system, the set of instructions operable to: store defined vulnerabilities that identify operations in the software application vulnerable to the security risk and are each associated with one or more input tags and one or more sanitization tags; receive by the software application in the database system a request from a user system; at runtime of the application, assign one or more of the input tags to one or more objects associated with the request, wherein the input tags identify the request as potentially malicious and carrying a security risk; at runtime of the application, assign one or more of the sanitization tags to the one or more objects associated with the request to indicate security checks performed on the objects; at runtime of the application, compare the input tags assigned to the objects with any of the sanitization tags assigned to the objects; and at runtime of the application, identify at least one of the defined vulnerabilities as a vulnerability in a part of the software application when the assigned input tag for an identified one of the objects matches the input tag associated with an identified one of the defined vulnerabilities, and one or more of the sanitization tags associated with the identified one of the defined vulnerabilities is not an assigned sanitization tag for the identified one of the objects; and generating a report identifying the vulnerability in a part of the software application. 6. The computer program product of claim 1 , further comprising instructions operable to assign the input tags to the objects based on types of input methods receiving the request.
| 0.776119 |
10,162,812 | 16 | 18 |
16. One or more non-transitory computer-readable media storing instructions that, when executed by a computing platform comprising at least one processor, memory, and a communication interface, cause the computing platform to: receive, by the at least one processor, via the communication interface, and from a first user device, mobile application feedback information comprising text feedback associated with feedback of a mobile application; identify, based on the text feedback, one or more nouns associated with the text feedback; identify, based on a comparison between the one or more nouns with a plurality of mobile application topics associated with the mobile application, one or more text feedback topics; generate, based on the one or more text feedback topics, one or more commands directing a sentiment analysis server to determine one or more sentiments for the one or more text feedback topics, wherein the generating the one or more commands directing the sentiment analysis server to determine the one or more text feedback topics comprises: determining, based on performing sentiment analysis on a part of the text feedback associated with the one or more text feedback topics, the one or more sentiments for the one or more text feedback topics, wherein determining the one or more sentiments for the one or more text feedback topics comprises: receiving a sentiment analysis model comprising past recorded user feedback data, and determining, based on a comparison between the sentiment analysis model and the part of the text feedback associated with the one or more text feedback topics, the one or more sentiments and one or more score probabilities associated with the one or more sentiments, and transmitting the one or more sentiments for the one or more text feedback topics; transmit, via the communication interface and to the sentiment analysis server, the one or more commands directing the sentiment analysis server to determine the one or more sentiments; receive, via the communication interface and from the sentiment analysis server, the one or more sentiments; and transmit, via the communication interface and to a summarization server, the one or more text feedback topics and the one or more sentiments.
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16. One or more non-transitory computer-readable media storing instructions that, when executed by a computing platform comprising at least one processor, memory, and a communication interface, cause the computing platform to: receive, by the at least one processor, via the communication interface, and from a first user device, mobile application feedback information comprising text feedback associated with feedback of a mobile application; identify, based on the text feedback, one or more nouns associated with the text feedback; identify, based on a comparison between the one or more nouns with a plurality of mobile application topics associated with the mobile application, one or more text feedback topics; generate, based on the one or more text feedback topics, one or more commands directing a sentiment analysis server to determine one or more sentiments for the one or more text feedback topics, wherein the generating the one or more commands directing the sentiment analysis server to determine the one or more text feedback topics comprises: determining, based on performing sentiment analysis on a part of the text feedback associated with the one or more text feedback topics, the one or more sentiments for the one or more text feedback topics, wherein determining the one or more sentiments for the one or more text feedback topics comprises: receiving a sentiment analysis model comprising past recorded user feedback data, and determining, based on a comparison between the sentiment analysis model and the part of the text feedback associated with the one or more text feedback topics, the one or more sentiments and one or more score probabilities associated with the one or more sentiments, and transmitting the one or more sentiments for the one or more text feedback topics; transmit, via the communication interface and to the sentiment analysis server, the one or more commands directing the sentiment analysis server to determine the one or more sentiments; receive, via the communication interface and from the sentiment analysis server, the one or more sentiments; and transmit, via the communication interface and to a summarization server, the one or more text feedback topics and the one or more sentiments. 18. The one or more non-transitory computer-readable media of claim 16 , wherein the memory stores additional computer-readable instructions that, when executed by the at least one processor, cause the computing platform to: receive, via the communication interface and from a mobile application dictionary server, the plurality of mobile application topics associated with the mobile application; and wherein the identifying the one or more text feedback topics is based on the one or more nouns matching one or more mobile application topics from the plurality of mobile application topics.
| 0.5 |
7,849,066 | 1 | 9 |
1. A computer system for determining applicability of information retrieving processes, comprising: a first computer storage for storing keywords indicating necessary information for an information retrieving process; a second computer storage for storing past retrieval case data including expressions extracted from voice data associated with an operation of the information retrieving process that matches the stored keywords in the first computer storage, an identification of a document selected in the operation of the information retrieving process, an order of the selected document by the operation of the information retrieving process that represents a highest place in ranking among retrieval results of operations of the information retrieving processes performed in a certain period, and a set of retrieval keys used in the operation of the information retrieving process in which the selected document was retrieved with a best order; a third computer storage for storing the voice data associated with the operation of the information retrieving process recorded in a conversation between a customer and an operator, wherein the stored voice data includes information necessary for performing the operation of the information retrieving process; a fourth computer storage for storing retrieval history information from the operation of the information retrieving process, wherein the stored retrieval history information includes an identification of the operator performing the operation of the information retrieving process, a set of retrieval keys actually used in the operation of the information retrieving process, an identification of a document selected by the operator among retrieval results of the operation of the information retrieving process, and an order of the selected document representing a place of the selected document in ranking of retrieval results of the operation of the information retrieving process; a retrieval history information acquirer for acquiring the stored retrieval history information of the operation of the information retrieving process performed by the operator from the fourth computer storage; a voice data acquirer for acquiring the stored voice data from the third computer storage associated with the acquired stored retrieval history information; an extractor for extracting one or more expressions matching the stored keywords in the first computer storage from the acquired stored voice data; a retrieval applicability determiner for extracting the stored past retrieval case data from the second computer storage having expressions that partially correspond to the extracted one or more expressions; comparing the set of retrieval keys and the order of the selected document in the acquired stored retrieval history information to a set of best retrieval keys and a best order of the selected document in the extracted stored past retrieval case data; determining an applicability of the operation of the information retrieving process based on the comparing; and obtaining and outputting the determined applicability of the operation of the information retrieving process as an information retrieval skill of the operator.
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1. A computer system for determining applicability of information retrieving processes, comprising: a first computer storage for storing keywords indicating necessary information for an information retrieving process; a second computer storage for storing past retrieval case data including expressions extracted from voice data associated with an operation of the information retrieving process that matches the stored keywords in the first computer storage, an identification of a document selected in the operation of the information retrieving process, an order of the selected document by the operation of the information retrieving process that represents a highest place in ranking among retrieval results of operations of the information retrieving processes performed in a certain period, and a set of retrieval keys used in the operation of the information retrieving process in which the selected document was retrieved with a best order; a third computer storage for storing the voice data associated with the operation of the information retrieving process recorded in a conversation between a customer and an operator, wherein the stored voice data includes information necessary for performing the operation of the information retrieving process; a fourth computer storage for storing retrieval history information from the operation of the information retrieving process, wherein the stored retrieval history information includes an identification of the operator performing the operation of the information retrieving process, a set of retrieval keys actually used in the operation of the information retrieving process, an identification of a document selected by the operator among retrieval results of the operation of the information retrieving process, and an order of the selected document representing a place of the selected document in ranking of retrieval results of the operation of the information retrieving process; a retrieval history information acquirer for acquiring the stored retrieval history information of the operation of the information retrieving process performed by the operator from the fourth computer storage; a voice data acquirer for acquiring the stored voice data from the third computer storage associated with the acquired stored retrieval history information; an extractor for extracting one or more expressions matching the stored keywords in the first computer storage from the acquired stored voice data; a retrieval applicability determiner for extracting the stored past retrieval case data from the second computer storage having expressions that partially correspond to the extracted one or more expressions; comparing the set of retrieval keys and the order of the selected document in the acquired stored retrieval history information to a set of best retrieval keys and a best order of the selected document in the extracted stored past retrieval case data; determining an applicability of the operation of the information retrieving process based on the comparing; and obtaining and outputting the determined applicability of the operation of the information retrieving process as an information retrieval skill of the operator. 9. The computer system according to claim 1 , further comprising: a second extractor for extracting an expression corresponding to one of the stored keywords in the first computer storage from the voice data associated with the operation of the information retrieving process recorded in the conversation and acquired in real-time; a best case retriever for extracting all the extracted stored past retrieval case data that has expressions corresponding to the extracted one or more expressions from the second computer storage; and a best retrieval key candidate presenter for generating retrieval key candidate information including the best retrieval keys, the identification of the document selected and the best order of the selected document which are extracted from the extracted stored past retrieval case data, and displaying the generated retrieval key candidate information.
| 0.5 |
5,590,322 | 1 | 2 |
1. Apparatus for the modeling and query of an information system on a programmable computer including memory, data entry means, data display means, a graphical user interface, the computer having a repository implemented thereon, the apparatus using natural language-like constructs for specifying and querying the information system and further comprising: drag-and-drop information system specification means, utilizing a computer language having both textual and graphical forms for translating the natural language-like constructs into object-role modeling symbology, the specification means further for entering text onto the display means utilizing the textual form of the computer language, for parsing the text into at least one of object, fact and constraint into the repository, for forming a conceptual schema diagram representing the information system on the display means utilizing rile graphical form of the computer language, and for mapping the conceptual schema to a database; and query mapping means for generating a fact tree representing a query; and query generation means for generating the query represented by the fact tree to the database.
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1. Apparatus for the modeling and query of an information system on a programmable computer including memory, data entry means, data display means, a graphical user interface, the computer having a repository implemented thereon, the apparatus using natural language-like constructs for specifying and querying the information system and further comprising: drag-and-drop information system specification means, utilizing a computer language having both textual and graphical forms for translating the natural language-like constructs into object-role modeling symbology, the specification means further for entering text onto the display means utilizing the textual form of the computer language, for parsing the text into at least one of object, fact and constraint into the repository, for forming a conceptual schema diagram representing the information system on the display means utilizing rile graphical form of the computer language, and for mapping the conceptual schema to a database; and query mapping means for generating a fact tree representing a query; and query generation means for generating the query represented by the fact tree to the database. 2. The apparatus of claim 1 further comprising means for constructing a natural language description of the fact tree.
| 0.682796 |
4,553,657 | 8 | 18 |
8. In the token system of claim 7, said slide being operative between a first position wherein said first magnetic means is positioned at said upper station and said second magnetic means is positioned at said lower station and a second position wherein neither of said first or second magnetic means is in communication with either of said upper or lower stations, said counterfeit and valid tokens being removed from said upper and lower stations, respectively, and being guided to said first and second outlet slots, respectively, upon movement of said slide to said second position thereof.
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8. In the token system of claim 7, said slide being operative between a first position wherein said first magnetic means is positioned at said upper station and said second magnetic means is positioned at said lower station and a second position wherein neither of said first or second magnetic means is in communication with either of said upper or lower stations, said counterfeit and valid tokens being removed from said upper and lower stations, respectively, and being guided to said first and second outlet slots, respectively, upon movement of said slide to said second position thereof. 18. In the device of claim 8, said inlet slot communicating with said first outlet slot when said slide is in either of said first or second positions thereof to permit the passage of a nonmagnetic counterfeit token through said inlet slot and into said first outlet slot.
| 0.751825 |
9,547,647 | 1 | 16 |
1. A method for searching for media items using a voice-based digital assistant, comprising: at an electronic device with a processor and memory storing instructions for execution by the processor: providing multiple media items wherein at least some of the media items are each associated with a respective tag comprising at least one of a time tag, a date tag, or a geo-code tag; providing a natural language text string corresponding to a search query for one or more media items, wherein the search query includes one or more query terms; searching at least one information source to identify at least one parameter associated with at least one of the one or more query terms, wherein the at least one parameter comprises at least one of a time parameter, a date parameter, or a geo-code parameter, wherein the at least one information source comprises user-specific descriptive information, and wherein the at least one parameter is not provided in the search query; comparing the respective tags to the at least one parameter to identify at least one media item whose tag matches the identified parameter; and facilitating the presentation of the at least one media item to a user.
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1. A method for searching for media items using a voice-based digital assistant, comprising: at an electronic device with a processor and memory storing instructions for execution by the processor: providing multiple media items wherein at least some of the media items are each associated with a respective tag comprising at least one of a time tag, a date tag, or a geo-code tag; providing a natural language text string corresponding to a search query for one or more media items, wherein the search query includes one or more query terms; searching at least one information source to identify at least one parameter associated with at least one of the one or more query terms, wherein the at least one parameter comprises at least one of a time parameter, a date parameter, or a geo-code parameter, wherein the at least one information source comprises user-specific descriptive information, and wherein the at least one parameter is not provided in the search query; comparing the respective tags to the at least one parameter to identify at least one media item whose tag matches the identified parameter; and facilitating the presentation of the at least one media item to a user. 16. The method of claim 1 , wherein the geo-code parameter comprises a range of geocodes associated with a location specified in the one or more query terms.
| 0.807125 |
8,566,076 | 20 | 22 |
20. A method for speech translation, comprising: receiving an original output from a first component; transforming the original output into a new output that is more easily translated by a second component based on an expected comfortability analysis and that is phonetically similar to the original hypothesis wherein the transforming includes: integrating a plurality of features in a log-linear transformation model; and hypotheses searching using one or more transformation features which are applied to the original hypothesis to transform the original hypothesis into a new hypothesis for processing by the second component.
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20. A method for speech translation, comprising: receiving an original output from a first component; transforming the original output into a new output that is more easily translated by a second component based on an expected comfortability analysis and that is phonetically similar to the original hypothesis wherein the transforming includes: integrating a plurality of features in a log-linear transformation model; and hypotheses searching using one or more transformation features which are applied to the original hypothesis to transform the original hypothesis into a new hypothesis for processing by the second component. 22. The system as recited in claim 20 , wherein the one or more transformation features includes at least one of a language model and a phrase paraphrase inventory to provide a grammatically correct and semantically meaningful hypotheses that is understandable to the second component.
| 0.5 |
9,355,092 | 1 | 26 |
1. A method of emulating human-like responses, the method comprising: storing a library comprising one or more different subject matter data structures, each data structure comprising a plurality of output instructions related to the subject matter of the data structure, each output instruction producing a human-like response and being associated with a received input stimulus, wherein the received input stimuli comprise human inputs and system inputs, the system inputs received via at least one sensor; associating each event with a tag; using the tag to determine whether an event corresponds to an important event or a non-important event; looking up output instructions in each data structure that are associated with the received input stimulus; outputting, via a human output API, one or more responses to the received stimulus according to a found output instruction when the event corresponds to an important event, wherein the one or more responses are ordered according to a priority rating; placing non-important events in an event queue; applying logical rules to the non-important events to determine whether a plurality of non-important events are collectively indicative of an important event; and outputting, via a human output API, one or more responses when the logical rules determine that the plurality of non-important events are collectively indicative of an important event, wherein the one or more responses are ordered according to a priority rating; wherein the one or more different subject matter data structures are arranged such that the output instructions which produce the human-like response are grouped hierarchically according to their respective associated stimuli.
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1. A method of emulating human-like responses, the method comprising: storing a library comprising one or more different subject matter data structures, each data structure comprising a plurality of output instructions related to the subject matter of the data structure, each output instruction producing a human-like response and being associated with a received input stimulus, wherein the received input stimuli comprise human inputs and system inputs, the system inputs received via at least one sensor; associating each event with a tag; using the tag to determine whether an event corresponds to an important event or a non-important event; looking up output instructions in each data structure that are associated with the received input stimulus; outputting, via a human output API, one or more responses to the received stimulus according to a found output instruction when the event corresponds to an important event, wherein the one or more responses are ordered according to a priority rating; placing non-important events in an event queue; applying logical rules to the non-important events to determine whether a plurality of non-important events are collectively indicative of an important event; and outputting, via a human output API, one or more responses when the logical rules determine that the plurality of non-important events are collectively indicative of an important event, wherein the one or more responses are ordered according to a priority rating; wherein the one or more different subject matter data structures are arranged such that the output instructions which produce the human-like response are grouped hierarchically according to their respective associated stimuli. 26. A method as claimed in claim 1 , wherein the library comprises selected response instructions that are constructed to document events reflected by the input stimulus.
| 0.772118 |
7,708,429 | 1 | 2 |
1. An illuminated document display system comprising: a partially transparent sleeve configured to house a document, wherein the partially transparent sleeve is at least partially flexible, and wherein the partially transparent sleeve includes four sides, a front surface, and a rear surface, and wherein the front surface further includes a transparent member; and a receptacle flexibly coupled to a particular side of the partially transparent sleeve, wherein the receptacle is configured to releasably house an illumination device which produces a light output, and wherein the receptacle includes an opening and a cover, wherein the opening enables the light output to transmit substantially toward the front surface via the particular side of the partially transparent sleeve, and wherein the cover blocks light output transmission in radial directions other than toward the front surface via the particular side.
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1. An illuminated document display system comprising: a partially transparent sleeve configured to house a document, wherein the partially transparent sleeve is at least partially flexible, and wherein the partially transparent sleeve includes four sides, a front surface, and a rear surface, and wherein the front surface further includes a transparent member; and a receptacle flexibly coupled to a particular side of the partially transparent sleeve, wherein the receptacle is configured to releasably house an illumination device which produces a light output, and wherein the receptacle includes an opening and a cover, wherein the opening enables the light output to transmit substantially toward the front surface via the particular side of the partially transparent sleeve, and wherein the cover blocks light output transmission in radial directions other than toward the front surface via the particular side. 2. The system of claim 1 , further including at least one other partially transparent sleeve configured to house additional documents, wherein the at least one other partially transparent sleeve is at least partially flexible, wherein the at least one other partially transparent sleeves are flexibly coupled to the particular side in a manner that does not obstruct the light output from transmitting substantially toward the front surface when the at least one other partially transparent sleeves are folded away from the partially transparent sleeve.
| 0.5 |
8,983,955 | 2 | 4 |
2. The computer readable medium according to claim 1 , wherein searching of the recording medium is allowed.
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2. The computer readable medium according to claim 1 , wherein searching of the recording medium is allowed. 4. The computer readable medium according to claim 2 , wherein said searching is based on at least one of (i) one or more of the said plurality of predefined portions of text-based data, (ii) said at least one modified predefined portion of text-based data, and (iii) a word or phrase within at least one or more of the said plurality of predefined portions of text-based data or said at least one modified predefined portion of text-based data.
| 0.5 |
7,865,825 | 16 | 17 |
16. The system of claim 15 , further comprising: an entity builder for generating an entity key required to publish the block of text, wherein the entity builder is linked to a publishing entity table for storing the business entities.
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16. The system of claim 15 , further comprising: an entity builder for generating an entity key required to publish the block of text, wherein the entity builder is linked to a publishing entity table for storing the business entities. 17. The system of claim 16 , wherein the system for generating an entity key comprises: a system for providing a choice list for each business entity to which the block of text pertains, wherein each choice list comprises at least one specific instance of the corresponding business entity; a system for selecting an instance of each business entity from each choice list; a system for building the entity key based on the selected instance of each business entity; and a published standard text table for storing the entity key.
| 0.5 |
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