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10,157,201 | 1 | 3 | 1. A method of searching for and providing information about a natural language query, the method comprising: generating, using a processor, a mashup query language based on at least one query entity included in a natural language query language via a semantic analysis of the natural language query language, the mashup query language having a tree structure in a plurality of levels, each of the plurality of levels being formed by a query entity, wherein the query entity provides a search target for deriving a search result through a knowledge database, wherein said generating the mashup query language extracts the query entity for each level and assigns at least one attribute to the query entity, the attribute including attribute information; determining, using the processor, whether the plurality of levels are linked through the query entity forming the mashup query language of each of the plurality of levels based on the attribute information of the mashup query language assigned to the query entities; searching, using the processor, for physical data in the knowledge database corresponding to the query entity forming the mashup query language of each of the plurality of levels from a knowledge database based on a result of the determining, and deriving main information and at least one piece of entity information corresponding to the natural language query language from the searched data, wherein the main information comprises final result data for the natural language query derived from said searching, and the entity information comprises physical data linked to the query entity for one or more of the plurality of levels that is searched during said searching, the entity information being used to derive the main information; and laying out, using the processor, a search result screen on a display comprising the main information and the at least one piece of entity information on separate regions of the display. | 1. A method of searching for and providing information about a natural language query, the method comprising: generating, using a processor, a mashup query language based on at least one query entity included in a natural language query language via a semantic analysis of the natural language query language, the mashup query language having a tree structure in a plurality of levels, each of the plurality of levels being formed by a query entity, wherein the query entity provides a search target for deriving a search result through a knowledge database, wherein said generating the mashup query language extracts the query entity for each level and assigns at least one attribute to the query entity, the attribute including attribute information; determining, using the processor, whether the plurality of levels are linked through the query entity forming the mashup query language of each of the plurality of levels based on the attribute information of the mashup query language assigned to the query entities; searching, using the processor, for physical data in the knowledge database corresponding to the query entity forming the mashup query language of each of the plurality of levels from a knowledge database based on a result of the determining, and deriving main information and at least one piece of entity information corresponding to the natural language query language from the searched data, wherein the main information comprises final result data for the natural language query derived from said searching, and the entity information comprises physical data linked to the query entity for one or more of the plurality of levels that is searched during said searching, the entity information being used to derive the main information; and laying out, using the processor, a search result screen on a display comprising the main information and the at least one piece of entity information on separate regions of the display. 3. The method of claim 1 , wherein generating the mashup query language further comprises assigning domain information relating to a query domain of each query entity, wherein the query domain comprises a semantic category of the search target or the attribute; and wherein the determining of whether the plurality of levels are linked comprises: analyzing the attribute information of the mashup query language and domain information of the mashup query language; selecting search environment information corresponding to the mashup query language according to a result of the analyzing; and normalizing the mashup query language by using the selected search environment information. | 0.732185 |
9,183,020 | 17 | 23 | 17. A computer for generating an application, comprising: a transceiver for communicating over the network; a memory for storing at least instructions; and a processor device that executes instructions performing actions, including: responsive to encountering a multi-size type during compilation of an intermediate language version of the application into a machine code version of the application, performing actions, including: determining architecture information of a target computer, wherein the architecture information includes at least a word size of the target computer; determining at least one data type associated with the target computer that corresponds to the multi-sized type based on the architecture information; determining one or more native codes call that perform actions associated with an intermediate language code call, wherein parameters to the one or more native codes call match the one or more data types; generating a machine code version of the intermediate language code call that at least corresponds to the one or more determined native code calls and also corresponds to the architecture information; when the target computer enables just-in-time compiling, executing the generated machine code version of the intermediate language code call with one or more values correspondent to the multi-size type and the one or more data types by executing the one or more determined native code calls using the one or more determined data types that correspond to the architecture information; and when the target computer disables just-in-time compiling, inserting the generated machine code version of the intermediate language code call in the machine code version of the application with the one or more values correspondent to the multi-size type and the one or more data types, wherein the generated machine code version includes instructions to execute the one or more determined native code calls. | 17. A computer for generating an application, comprising: a transceiver for communicating over the network; a memory for storing at least instructions; and a processor device that executes instructions performing actions, including: responsive to encountering a multi-size type during compilation of an intermediate language version of the application into a machine code version of the application, performing actions, including: determining architecture information of a target computer, wherein the architecture information includes at least a word size of the target computer; determining at least one data type associated with the target computer that corresponds to the multi-sized type based on the architecture information; determining one or more native codes call that perform actions associated with an intermediate language code call, wherein parameters to the one or more native codes call match the one or more data types; generating a machine code version of the intermediate language code call that at least corresponds to the one or more determined native code calls and also corresponds to the architecture information; when the target computer enables just-in-time compiling, executing the generated machine code version of the intermediate language code call with one or more values correspondent to the multi-size type and the one or more data types by executing the one or more determined native code calls using the one or more determined data types that correspond to the architecture information; and when the target computer disables just-in-time compiling, inserting the generated machine code version of the intermediate language code call in the machine code version of the application with the one or more values correspondent to the multi-size type and the one or more data types, wherein the generated machine code version includes instructions to execute the one or more determined native code calls. 23. The computer of claim 17 , wherein compiling the intermediate language version of the application into the machine code version of the application, further comprises, generating the machine code version using a runtime engine that is executing on the target computer, wherein the runtime engine enables just-in-time compilation of the machine code version of the application. | 0.72576 |
9,203,924 | 1 | 6 | 1. A method executed on one or more hardware computing devices for recommending audio files to a member of a social network, the method comprising: receiving, at the one or more hardware computing devices, a representation of a first set of audio files associated with the member; receiving a representation of a set of social networking contacts associated with the member; receiving a representation of one or more second sets of audio files, wherein each second set of audio files is associated with at least one social networking contact in the set of social networking contacts associated with the member; determining, using the one or more hardware computing devices, a first set of characteristics based on the representation of the first set of audio files; determining, using the one or more hardware computing devices, a second set of characteristics based on the representation of the one or more second sets of audio files; generating, using the one or more hardware computing devices, a recommendation for at least one new audio file based on the first set of characteristics and the second set of characteristics, wherein the at least one new audio file is not in the first set of audio files; and providing an indication of the recommendation for the at least one new audio file, wherein the set of social networking contacts associated with the member comprises one or more predefined collections of social networking contacts associated with the member in a social networking service, and wherein the set of social networking contacts associated with the member comprises users of the social networking service having at least one personal characteristic common to that of the member, the at least one personal characteristic corresponding to user registration information within the social networking service. | 1. A method executed on one or more hardware computing devices for recommending audio files to a member of a social network, the method comprising: receiving, at the one or more hardware computing devices, a representation of a first set of audio files associated with the member; receiving a representation of a set of social networking contacts associated with the member; receiving a representation of one or more second sets of audio files, wherein each second set of audio files is associated with at least one social networking contact in the set of social networking contacts associated with the member; determining, using the one or more hardware computing devices, a first set of characteristics based on the representation of the first set of audio files; determining, using the one or more hardware computing devices, a second set of characteristics based on the representation of the one or more second sets of audio files; generating, using the one or more hardware computing devices, a recommendation for at least one new audio file based on the first set of characteristics and the second set of characteristics, wherein the at least one new audio file is not in the first set of audio files; and providing an indication of the recommendation for the at least one new audio file, wherein the set of social networking contacts associated with the member comprises one or more predefined collections of social networking contacts associated with the member in a social networking service, and wherein the set of social networking contacts associated with the member comprises users of the social networking service having at least one personal characteristic common to that of the member, the at least one personal characteristic corresponding to user registration information within the social networking service. 6. The method of claim 1 , further comprising: adding the at least one new audio file to the first set of audio files. | 0.914493 |
5,452,442 | 6 | 7 | 6. A method as set forth in claim 5 wherein for uni-grams (n=1), the estimated probability is given by the recorded frequency divided by the total number of uni-grams; and for n-grams (n.gtoreq.2) the estimated probability is given by a weighted average of the recorded frequency and a probability determined by combining together shorter n-grams. | 6. A method as set forth in claim 5 wherein for uni-grams (n=1), the estimated probability is given by the recorded frequency divided by the total number of uni-grams; and for n-grams (n.gtoreq.2) the estimated probability is given by a weighted average of the recorded frequency and a probability determined by combining together shorter n-grams. 7. A method as set forth in claim 6 wherein two (n-1)-gram probabilities and an (n-2)-gram probability are combined to form an n-gram probability (p) in accordance with the expression: ##EQU5## where B.sub.1 to B.sub.n are sequentially occurring bytes. | 0.959355 |
7,835,998 | 1 | 7 | 1. A user-interface method of selecting and presenting a collection of content items of a first content system in which the presentation is ordered at least in part based on content preferences of the user learned from the user selecting content of a second content system, the method comprising: receiving incremental input entered by the user for incrementally identifying desired content items of the second content system, each content item having at least one associated descriptive term to describe the content item; in response to the incremental input entered by the user, presenting a subset of content items of the second content system; receiving selection actions of content items of the subset from the user; determining a user preference signature by analyzing the descriptive terms of the selected content items to learn the content preferences of the user for the content of the second content system; determining a relationship between the content items of the first content system and the content items of the second content system, the relationship defining which learned user content preferences of the user preference signature are relevant to the content items of the first content system; and in response to receiving subsequent incremental input entered by the user for incrementally identifying desired content items of the first content system, selecting and ordering a collection of content items of the first content system based on the learned content preferences of the user determined to be relevant to the content items of the first content system. | 1. A user-interface method of selecting and presenting a collection of content items of a first content system in which the presentation is ordered at least in part based on content preferences of the user learned from the user selecting content of a second content system, the method comprising: receiving incremental input entered by the user for incrementally identifying desired content items of the second content system, each content item having at least one associated descriptive term to describe the content item; in response to the incremental input entered by the user, presenting a subset of content items of the second content system; receiving selection actions of content items of the subset from the user; determining a user preference signature by analyzing the descriptive terms of the selected content items to learn the content preferences of the user for the content of the second content system; determining a relationship between the content items of the first content system and the content items of the second content system, the relationship defining which learned user content preferences of the user preference signature are relevant to the content items of the first content system; and in response to receiving subsequent incremental input entered by the user for incrementally identifying desired content items of the first content system, selecting and ordering a collection of content items of the first content system based on the learned content preferences of the user determined to be relevant to the content items of the first content system. 7. The method of claim 1 , wherein the first content system is on a server system remote from the user and the second content system is on a user client device. | 0.894875 |
9,524,175 | 1 | 4 | 1. A system, comprising: one or more computing devices comprising one or more hardware processors, wherein the one or more computing devices are configured to: determine, for an overloaded operation invocation identified in source code of a computer program, whether the source code includes, as an argument to the invocation, an expression whose type is context-dependent; and in response to a determination that the source code includes, as an argument to the invocation, an expression whose type is context-dependent, determine, at an overload resolver to which the expression is provided as input, (a) whether each argument of the invocation, including the expression, is compatible with a type of a corresponding parameter indicated in one or more invocable operation declarations identified from the source code, and (b) whether a particular invocable operation declaration of the one or more Invocable operation declarations is identifiable as the most specific invocable operation declaration for the invocation based at least in part on one or more specificity criteria; in response to a determination that (a) each argument of the invocation is compatible with a type of a corresponding parameter indicated in one or more invocable operation declarations in the source code, and (b) a particular invocable operation declaration of the one or more invocable operation declarations is identifiable as the most specific invocable operation declaration for the invocation, generate executable instructions for the invocation in accordance with the particular invocable operation declaration; and in response to a determination that none of the plurality of invocable operation declarations is identifiable as the most specific invocable operation declaration for the invocation, generate an error indication; wherein the error is generated even though each argument of the invocation is compatible with a type of a corresponding parameter indicated in a plurality of invocable operation declarations in the source code. | 1. A system, comprising: one or more computing devices comprising one or more hardware processors, wherein the one or more computing devices are configured to: determine, for an overloaded operation invocation identified in source code of a computer program, whether the source code includes, as an argument to the invocation, an expression whose type is context-dependent; and in response to a determination that the source code includes, as an argument to the invocation, an expression whose type is context-dependent, determine, at an overload resolver to which the expression is provided as input, (a) whether each argument of the invocation, including the expression, is compatible with a type of a corresponding parameter indicated in one or more invocable operation declarations identified from the source code, and (b) whether a particular invocable operation declaration of the one or more Invocable operation declarations is identifiable as the most specific invocable operation declaration for the invocation based at least in part on one or more specificity criteria; in response to a determination that (a) each argument of the invocation is compatible with a type of a corresponding parameter indicated in one or more invocable operation declarations in the source code, and (b) a particular invocable operation declaration of the one or more invocable operation declarations is identifiable as the most specific invocable operation declaration for the invocation, generate executable instructions for the invocation in accordance with the particular invocable operation declaration; and in response to a determination that none of the plurality of invocable operation declarations is identifiable as the most specific invocable operation declaration for the invocation, generate an error indication; wherein the error is generated even though each argument of the invocation is compatible with a type of a corresponding parameter indicated in a plurality of invocable operation declarations in the source code. 4. The system as recited in claim 1 , wherein the expression whose type is context-dependent comprises a method reference. | 0.954748 |
9,747,276 | 1 | 5 | 1. A computer program product, comprising: a non-transitory computer readable storage medium having program instructions embodied therewith, the program instructions readable by a processing circuit to cause the processing circuit to perform a method of determining a crowd behavior, the method comprising: collecting, at one or more recording points in a crowd of individuals, audible expressions that the individuals of the crowd make; generating a graph of the audible expressions as the audible expressions are collected from the individuals, wherein the graph comprises nodes that represent tokens and edges that represent temporal precedence in the audible expressions; determining a crowd behavior by performing a graphical text analysis on the graph; and outputting an indication of the crowd behavior to trigger a crowd control measure, wherein the crowd behavior comprises a risk metric, and wherein the crowd control measure is triggered when the risk metric is above a threshold. | 1. A computer program product, comprising: a non-transitory computer readable storage medium having program instructions embodied therewith, the program instructions readable by a processing circuit to cause the processing circuit to perform a method of determining a crowd behavior, the method comprising: collecting, at one or more recording points in a crowd of individuals, audible expressions that the individuals of the crowd make; generating a graph of the audible expressions as the audible expressions are collected from the individuals, wherein the graph comprises nodes that represent tokens and edges that represent temporal precedence in the audible expressions; determining a crowd behavior by performing a graphical text analysis on the graph; and outputting an indication of the crowd behavior to trigger a crowd control measure, wherein the crowd behavior comprises a risk metric, and wherein the crowd control measure is triggered when the risk metric is above a threshold. 5. The computer program product of claim 1 , wherein the audible expressions of the individuals are collected as the individuals approach or pass by the recording points. | 0.786432 |
8,032,827 | 1 | 5 | 1. A method comprising the steps of: a) for each document in a plurality of documents, generating, by a computer system, text structure tags for the document, said text structure tags identifying a plurality of argumentative text types, wherein a text type comprises a type of argumentative content for an associated portion of a document, said types of argumentative content comprising an argument premise giving support, evidence, or reasoning for or against a conclusion or the conclusion comprising a resulting determination made using one or more argument premises; b) for each document in the plurality of documents, encoding, by the computer system, said document to generate a tree structure comprising a plurality of nodes, wherein said nodes correspond with said text types and hierarchical relationships among said nodes reflect argumentative relationships among said text types; c) selecting, by the computer system, a plurality of tree structures for the plurality of documents; d) combining, by the computer system, the plurality of tree structures as a single logical tree structure; and e) generating, by the computer system, a summary of the plurality of documents by: i) receiving from a user a selection of one or more particular text types for summarization; and ii) extracting, based on said text structure tags, portions of text from the plurality of documents that correspond to nodes from the plurality of tree structures to form a summary of the plurality of documents, the nodes corresponding to said one or more selected text types. | 1. A method comprising the steps of: a) for each document in a plurality of documents, generating, by a computer system, text structure tags for the document, said text structure tags identifying a plurality of argumentative text types, wherein a text type comprises a type of argumentative content for an associated portion of a document, said types of argumentative content comprising an argument premise giving support, evidence, or reasoning for or against a conclusion or the conclusion comprising a resulting determination made using one or more argument premises; b) for each document in the plurality of documents, encoding, by the computer system, said document to generate a tree structure comprising a plurality of nodes, wherein said nodes correspond with said text types and hierarchical relationships among said nodes reflect argumentative relationships among said text types; c) selecting, by the computer system, a plurality of tree structures for the plurality of documents; d) combining, by the computer system, the plurality of tree structures as a single logical tree structure; and e) generating, by the computer system, a summary of the plurality of documents by: i) receiving from a user a selection of one or more particular text types for summarization; and ii) extracting, based on said text structure tags, portions of text from the plurality of documents that correspond to nodes from the plurality of tree structures to form a summary of the plurality of documents, the nodes corresponding to said one or more selected text types. 5. The method as set forth in claim 1 , wherein: receiving a selection of one or more particular text types for summarization comprises receiving a selection for said conclusion text type for summarization; and extracting portions of text from the plurality of documents comprises extracting portions of text from the plurality of documents that correspond to nodes corresponding to said conclusion text type. | 0.597441 |
7,953,600 | 20 | 29 | 20. A system for synthesizing a target voice, comprising: a processor; and a storage medium having program instructions written thereon for execution on the processor, the program instructions including program instructions for: a front end module configured to receive symbolic input descriptive of an utterance to be synthesized, a back end module configured to select one or more portions of the utterance to be constructed from certain Phone-and-Transition (P&T) speech units that function as prototype speech units, the prototype speech units obtained from a target voice corpus, the target voice corpus including speech units recorded from a human speaker, the target voice corpus configured to provide characteristics of the target voice, a unit engine of the back end module configured to apply adaptations to selected ones of the prototype speech units of the target voice corpus that are derived from a context different than the one in which they are to be used in the utterance, to produce adapted speech units that are contextually appropriate for the utterance, and a concatenation engine of the back end module configured to concatenate at least the adapted speech units from the target voice corpus and speech units from a source other than the target voice corpus, to produce a speech waveform for the utterance. | 20. A system for synthesizing a target voice, comprising: a processor; and a storage medium having program instructions written thereon for execution on the processor, the program instructions including program instructions for: a front end module configured to receive symbolic input descriptive of an utterance to be synthesized, a back end module configured to select one or more portions of the utterance to be constructed from certain Phone-and-Transition (P&T) speech units that function as prototype speech units, the prototype speech units obtained from a target voice corpus, the target voice corpus including speech units recorded from a human speaker, the target voice corpus configured to provide characteristics of the target voice, a unit engine of the back end module configured to apply adaptations to selected ones of the prototype speech units of the target voice corpus that are derived from a context different than the one in which they are to be used in the utterance, to produce adapted speech units that are contextually appropriate for the utterance, and a concatenation engine of the back end module configured to concatenate at least the adapted speech units from the target voice corpus and speech units from a source other than the target voice corpus, to produce a speech waveform for the utterance. 29. The system of claim 20 wherein the adaptations comprise an adaptation that time reverses at least a portion of one of the stored prototype speech units. | 0.77193 |
8,902,274 | 1 | 7 | 1. A method, comprising: discovering from a meeting recording, by a meeting recording distribution module, active participants and passive participants of a meeting; generating an active notification comprising an option to manipulate the meeting recording, and a passive notification without the option to manipulate the meeting recording, wherein the manipulating comprises adding content, including metadata, to the meeting recording; and sending the active notification and the passive notification to the active participants and the passive participants, respectively. | 1. A method, comprising: discovering from a meeting recording, by a meeting recording distribution module, active participants and passive participants of a meeting; generating an active notification comprising an option to manipulate the meeting recording, and a passive notification without the option to manipulate the meeting recording, wherein the manipulating comprises adding content, including metadata, to the meeting recording; and sending the active notification and the passive notification to the active participants and the passive participants, respectively. 7. The method of claim 1 , wherein the discovering the active participants and the passive participants comprises: running speaker segmentation and recognition algorithms on the meeting recording; discovering attendees including speakers and non-speakers; and categorizing the speakers as the active participants, and the non-speakers as the passive participants. | 0.716406 |
9,817,991 | 10 | 14 | 10. A multi-tenant computing platform, comprising: a records application configured to store records in a tenant data store; each record having record data stored therein; a graphical user interface configured to display a graphical representation of data associated with one or more records such that the display is restricted to a first set of one or more credentialed users; and a notes application configured to facilitate generation of a note associated with one or more records in the tenant data store, each note having restricted access such that only a second set of one or more credentialed users may access the note, the second set different from the first set; wherein the graphical user interface is configured to display a note over a record if and only if a credentialed user of the graphical user interface is in the first set of one or more credentialed users and in the second set of one or more credentialed users. | 10. A multi-tenant computing platform, comprising: a records application configured to store records in a tenant data store; each record having record data stored therein; a graphical user interface configured to display a graphical representation of data associated with one or more records such that the display is restricted to a first set of one or more credentialed users; and a notes application configured to facilitate generation of a note associated with one or more records in the tenant data store, each note having restricted access such that only a second set of one or more credentialed users may access the note, the second set different from the first set; wherein the graphical user interface is configured to display a note over a record if and only if a credentialed user of the graphical user interface is in the first set of one or more credentialed users and in the second set of one or more credentialed users. 14. The multi-tenant computing platform of claim 10 , wherein the records stored in the tenant data store comprises business records for an enterprise resource planning system. | 0.851852 |
9,495,440 | 17 | 20 | 17. An apparatus comprising processing circuitry configured to cause the apparatus to perform at least: receiving an indication of a received file; queuing the received file into a file classifier queue; and processing a file from the file classifier queue by: a) determining at least one of a file type or a document type of the file from the file classifier queue; b) based on one or both of the file type or the document type, classifying the file from the file classifier queue as an unsupported file, an Optical Character Recognition (OCR) eligible file, or a Full Text Search (FTS) eligible file; c) in an instance in which the file from the file classifier queue is an OCR eligible file, queuing the OCR eligible file into an OCR queue for OCR processing; and d) in an instance in which the file from the file classifier queue is an FTS eligible file, queuing the FTS eligible file into a FTS queue for FTS indexing. | 17. An apparatus comprising processing circuitry configured to cause the apparatus to perform at least: receiving an indication of a received file; queuing the received file into a file classifier queue; and processing a file from the file classifier queue by: a) determining at least one of a file type or a document type of the file from the file classifier queue; b) based on one or both of the file type or the document type, classifying the file from the file classifier queue as an unsupported file, an Optical Character Recognition (OCR) eligible file, or a Full Text Search (FTS) eligible file; c) in an instance in which the file from the file classifier queue is an OCR eligible file, queuing the OCR eligible file into an OCR queue for OCR processing; and d) in an instance in which the file from the file classifier queue is an FTS eligible file, queuing the FTS eligible file into a FTS queue for FTS indexing. 20. The apparatus of claim 17 , wherein classifying the file from the file classifier queue as an FTS eligible file comprises determining that the file from the file classifier queue comprises machine-readable text. | 0.883784 |
8,170,195 | 9 | 12 | 9. A non-transitory tangible computer readable medium for controlling a computer and comprising a plurality of code segments for classifying a plurality of telephonic communications, the computer readable medium comprising: a code segment for receiving the plurality of telephonic communications, wherein each telephonic communication comprises at least one of voice data and event data; a code segment for receiving computer application data comprising data associated with at least one computer application in use during each of the telephonic communications; and, a code segment for analyzing at least two of the plurality of telephonic communications, the code segment comprising: a code segment for translating the voice data associated with each of the at least two of the plurality of telephonic communications into a text format, the text format defining a plurality of components; a code segment for classifying each of the at least two of the plurality of telephonic communications into one of a plurality of call set types; a code segment for classifying at least one of the event data and at least one of the plurality of components occurring during a time interval into one of a plurality of object types; and a code segment for comparing the computer application data associated with the time interval to at least one of the object type and the call set type. | 9. A non-transitory tangible computer readable medium for controlling a computer and comprising a plurality of code segments for classifying a plurality of telephonic communications, the computer readable medium comprising: a code segment for receiving the plurality of telephonic communications, wherein each telephonic communication comprises at least one of voice data and event data; a code segment for receiving computer application data comprising data associated with at least one computer application in use during each of the telephonic communications; and, a code segment for analyzing at least two of the plurality of telephonic communications, the code segment comprising: a code segment for translating the voice data associated with each of the at least two of the plurality of telephonic communications into a text format, the text format defining a plurality of components; a code segment for classifying each of the at least two of the plurality of telephonic communications into one of a plurality of call set types; a code segment for classifying at least one of the event data and at least one of the plurality of components occurring during a time interval into one of a plurality of object types; and a code segment for comparing the computer application data associated with the time interval to at least one of the object type and the call set type. 12. The computer readable medium of claim 9 , further comprising a code segment for generating a graphical user interface for displaying the at least one of the plurality of components and the computer application data for the time interval, the graphical user interface comprising: a code segment for receiving an input prompt to retrieve at least one of the classified at least one component and the computer application data associated with the time interval; a code segment for receiving the input transmission of the prompted at least one of the classified at least one and the computer application data associated with the time interval; and, a code segment for displaying the received at least one of the classified at least one component and the computer application data associated with the time interval. | 0.500613 |
8,370,126 | 1 | 15 | 1. A computer implemented method comprising: translating an abstract phrase from a first language to a second language; receiving the translated abstract phrase comprising a text phrase and a variable at a particular position in the text phrase; receiving a text value for the variable; combining the text phrase of the abstract phrase and the text value according to the particular position of the variable; applying, by a computer system, an integration rule at a boundary of the text phrase of the abstract phrase and the text value to produce an integrated phrase, the integration rule based on a language rule for the second language, wherein the integration rule modifies a portion of the text phrase of the abstract phrase or a portion of the text value. | 1. A computer implemented method comprising: translating an abstract phrase from a first language to a second language; receiving the translated abstract phrase comprising a text phrase and a variable at a particular position in the text phrase; receiving a text value for the variable; combining the text phrase of the abstract phrase and the text value according to the particular position of the variable; applying, by a computer system, an integration rule at a boundary of the text phrase of the abstract phrase and the text value to produce an integrated phrase, the integration rule based on a language rule for the second language, wherein the integration rule modifies a portion of the text phrase of the abstract phrase or a portion of the text value. 15. The method of claim 1 , wherein multiple rules are applied, and wherein a subsequent rule is applied to text modified by a previously applied rule. | 0.928504 |
7,827,242 | 1 | 2 | 1. A computer-implemented method for enabling contextual collaboration within a computer network, said method comprising: receiving a user request for a collaboration space within said computer network; creating, by a computing device, a collaboration space containing a plurality of collaboration elements of different collaboration modalities in response to said user request for said collaboration space, said collaboration space associated with a specific business context; issuing, by said computing device, a Uniform Resource Locator (URL) of said collaboration space in response to said user request; maintaining, by said computing device, resources and resource interrelationships within contexts, said resources including at least one of collaboration elements, processes, tasks, business objects, users, and roles; selecting, by said computing device, a set of said resources to be displayed to a user, accessing, by said computing device, a library of context rules implemented by one of industry standard process ontologies and proprietary schemes; executing, by said computing device, context rules from said library of context rules associated with said specific business context; and outputting to said user said set of resources, and context-specific collaboration content based on said executing said context rules from said library of context rules. | 1. A computer-implemented method for enabling contextual collaboration within a computer network, said method comprising: receiving a user request for a collaboration space within said computer network; creating, by a computing device, a collaboration space containing a plurality of collaboration elements of different collaboration modalities in response to said user request for said collaboration space, said collaboration space associated with a specific business context; issuing, by said computing device, a Uniform Resource Locator (URL) of said collaboration space in response to said user request; maintaining, by said computing device, resources and resource interrelationships within contexts, said resources including at least one of collaboration elements, processes, tasks, business objects, users, and roles; selecting, by said computing device, a set of said resources to be displayed to a user, accessing, by said computing device, a library of context rules implemented by one of industry standard process ontologies and proprietary schemes; executing, by said computing device, context rules from said library of context rules associated with said specific business context; and outputting to said user said set of resources, and context-specific collaboration content based on said executing said context rules from said library of context rules. 2. The method in claim 1 , further comprising: managing, by said computing device, lifecycles of said collaboration spaces; maintaining, by said computing device, membership lists, user profiles, and role associations in said collaboration spaces; adding and removing, by said computing device, said collaboration elements; and performing modality-specific operations, by said computing device, on said collaboration elements. | 0.501171 |
8,832,088 | 12 | 14 | 12. A system comprising: one or more computers and one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising: receiving a search result obtained in response to a query, wherein the search result identifies a resource and has an associated score S; computing a recent impression probability for the query for a recent time period and an overall impression probability for the query for an overall time period, wherein each impression probability corresponds to a ratio of (i) a count of search result impressions selected by users to (ii) a count of all search result impressions presented to users in the respective time periods, wherein the search result impressions were impressions provided in response to the query by a search engine during the respective time period, and wherein the overall time period is a time period that began before the recent time period and is longer than the recent time period; computing a QtoA ratio of the recent impression probability to the overall impression probability; determining that users prefer newer resources over older resources for the query based on the QtoA ratio; determining that the resource is a new resource; and associating a new score S′ with the resource in place of S, wherein the new score S′ signifies a better result than the score S signifies, based on determining, that users prefer newer resources over older resources for the query and that the resource is a new resource. | 12. A system comprising: one or more computers and one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising: receiving a search result obtained in response to a query, wherein the search result identifies a resource and has an associated score S; computing a recent impression probability for the query for a recent time period and an overall impression probability for the query for an overall time period, wherein each impression probability corresponds to a ratio of (i) a count of search result impressions selected by users to (ii) a count of all search result impressions presented to users in the respective time periods, wherein the search result impressions were impressions provided in response to the query by a search engine during the respective time period, and wherein the overall time period is a time period that began before the recent time period and is longer than the recent time period; computing a QtoA ratio of the recent impression probability to the overall impression probability; determining that users prefer newer resources over older resources for the query based on the QtoA ratio; determining that the resource is a new resource; and associating a new score S′ with the resource in place of S, wherein the new score S′ signifies a better result than the score S signifies, based on determining, that users prefer newer resources over older resources for the query and that the resource is a new resource. 14. The system of claim 12 , wherein the recent time period includes at least one previous day, month, or year. | 0.876116 |
8,255,260 | 18 | 19 | 18. The computer-readable storage medium of claim 17 , wherein the filtered exception object data records are stored in the temporary container when no user is subscribed to the filtered exception object data records. | 18. The computer-readable storage medium of claim 17 , wherein the filtered exception object data records are stored in the temporary container when no user is subscribed to the filtered exception object data records. 19. The computer-readable storage medium of claim 18 , wherein the filtered exception object data records are stored in the persistent container when at least one user is subscribed to the filtered exception object data records. | 0.933489 |
10,007,946 | 18 | 19 | 18. The recommendation system of claim 13 , further comprising: a data collection engine configured to electronically monitor, substantially in real time, user interactions with a plurality of unique items and to generate data based on the user interactions for use by the penalty computation engine in calculating dissimilarity penalties. | 18. The recommendation system of claim 13 , further comprising: a data collection engine configured to electronically monitor, substantially in real time, user interactions with a plurality of unique items and to generate data based on the user interactions for use by the penalty computation engine in calculating dissimilarity penalties. 19. The recommendation system of claim 18 , wherein the data collection engine being configured to electronically monitor, substantially in real time, user interactions, comprises being configured to electronically monitor a plurality of item listing services. | 0.935675 |
7,979,788 | 1 | 9 | 1. A document processing apparatus, including a processor, comprising: an attachment unit that attaches a comment to an electronic document as additional information at a first position in a body of the electronic document and that modifies the electronic document to include a modification at a second position in the body of the electronic document; a processing unit that determines, in response to a user's input indicating that the modification has been made by the user based on a content of the comment, that the electronic document is modified by the user accessing the electronic document to include the modification based on the content of the comment and associates the comment with the modified place information indicating the second position at which the electronic document is modified, a character string at the second position prior to the modification, and a character string at the second position after the modification, in response to determining that the document is modified based on the content of the comment; and a storage unit that stores the associated information in a database. | 1. A document processing apparatus, including a processor, comprising: an attachment unit that attaches a comment to an electronic document as additional information at a first position in a body of the electronic document and that modifies the electronic document to include a modification at a second position in the body of the electronic document; a processing unit that determines, in response to a user's input indicating that the modification has been made by the user based on a content of the comment, that the electronic document is modified by the user accessing the electronic document to include the modification based on the content of the comment and associates the comment with the modified place information indicating the second position at which the electronic document is modified, a character string at the second position prior to the modification, and a character string at the second position after the modification, in response to determining that the document is modified based on the content of the comment; and a storage unit that stores the associated information in a database. 9. The document process apparatus according to claim 1 , wherein the modified place information includes at least one of a start line of the modification in the electronic document, a first character in the modification, and a number of characters in the modification. | 0.58125 |
9,262,411 | 8 | 12 | 8. A computer readable storage device, tangibly embodying a program of instructions executable by a computer for translating content, wherein the content has an author who is part of a social network, the program of instructions, when executing, performing the following steps: receiving the content; retrieving from the social network contextual information associated with the content; retrieving from the social network author information associated with the author; creating a content-specific dictionary based upon the retrieved contextual information and the retrieved author information; creating a translation profile based upon the retrieved contextual information, the retrieved author information and the created content-specific dictionary; determining one of a plurality of generic dictionaries to use for the translating, wherein the determination of the one of the plurality of generic dictionaries to use is based upon the translation profile; and translating the received content using the content-specific dictionary and the determined one of the plurality of generic dictionaries to use. | 8. A computer readable storage device, tangibly embodying a program of instructions executable by a computer for translating content, wherein the content has an author who is part of a social network, the program of instructions, when executing, performing the following steps: receiving the content; retrieving from the social network contextual information associated with the content; retrieving from the social network author information associated with the author; creating a content-specific dictionary based upon the retrieved contextual information and the retrieved author information; creating a translation profile based upon the retrieved contextual information, the retrieved author information and the created content-specific dictionary; determining one of a plurality of generic dictionaries to use for the translating, wherein the determination of the one of the plurality of generic dictionaries to use is based upon the translation profile; and translating the received content using the content-specific dictionary and the determined one of the plurality of generic dictionaries to use. 12. The computer readable storage device of claim 8 , wherein the author information comprises at least one of: (a) a writing style of the author; (b) a language style of the author; (c) a background of the author; (d) one or more personal preferences of the author; or (e) any combination thereof. | 0.642686 |
8,478,045 | 8 | 12 | 8. An apparatus for processing an image including a character, comprising: an initial selection device, configured to search in a set of characters one or more characters having highest similarities of shape to a character in the set of characters, hereinafter the character being referred to as a first character, the one or more searched characters forming a similar character list of the first character, and further configured to search in the set of characters one or more characters having highest similarities of shape to each character in the similar character list of the first character, to form a similar character list of each character in the similar character list of the first character; and a cluster forming device, configured to select in the similar character lists one or more characters having a high mutual similarity between each other, as a character cluster. | 8. An apparatus for processing an image including a character, comprising: an initial selection device, configured to search in a set of characters one or more characters having highest similarities of shape to a character in the set of characters, hereinafter the character being referred to as a first character, the one or more searched characters forming a similar character list of the first character, and further configured to search in the set of characters one or more characters having highest similarities of shape to each character in the similar character list of the first character, to form a similar character list of each character in the similar character list of the first character; and a cluster forming device, configured to select in the similar character lists one or more characters having a high mutual similarity between each other, as a character cluster. 12. The apparatus according to claim 8 , wherein one of any two characters of the character cluster is included in the other's similar character list. | 0.910072 |
9,122,776 | 1 | 2 | 1. An electronic health record system, comprising: an electronic device having a display and being capable of receiving user input; a first digital storage segment; a plurality of clinic note templates encoded on the first digital storage segment; a second digital storage segment; a plurality of electronic health records encoded on the second digital storage segment, each record associated with a particular patient; said electronic device effective to access the clinic note templates on the first storage segment and present on the display a template selection screen; said template selection screen containing a plurality of representations of at least a portion of the clinic note templates, wherein said electronic device is effective to present on the display a clinic note formatted according to a particular clinic note template and containing a plurality of fields when the user device receives user input that a user representation of a particular clinic note template is selected; said electronic device effective to receive a user input that a particular field should be manipulated; and said electronic device further effective to present on the display a manipulated field according to the particular user input, wherein: said user input is a portion of a string of textual input; said processor of the user device effective to discern that said portion of a string of textual input is a portion of an acronym; said device effective to present on the display a pop-up window containing a plurality of optional expanded acronyms and receive a second user input that one of said plurality of optional expanded acronyms has been selected; and said device effective to present on the display a completed string of textual input. | 1. An electronic health record system, comprising: an electronic device having a display and being capable of receiving user input; a first digital storage segment; a plurality of clinic note templates encoded on the first digital storage segment; a second digital storage segment; a plurality of electronic health records encoded on the second digital storage segment, each record associated with a particular patient; said electronic device effective to access the clinic note templates on the first storage segment and present on the display a template selection screen; said template selection screen containing a plurality of representations of at least a portion of the clinic note templates, wherein said electronic device is effective to present on the display a clinic note formatted according to a particular clinic note template and containing a plurality of fields when the user device receives user input that a user representation of a particular clinic note template is selected; said electronic device effective to receive a user input that a particular field should be manipulated; and said electronic device further effective to present on the display a manipulated field according to the particular user input, wherein: said user input is a portion of a string of textual input; said processor of the user device effective to discern that said portion of a string of textual input is a portion of an acronym; said device effective to present on the display a pop-up window containing a plurality of optional expanded acronyms and receive a second user input that one of said plurality of optional expanded acronyms has been selected; and said device effective to present on the display a completed string of textual input. 2. The system of claim 1 , further comprising: said template selection screen containing a sidebar including a categorical listing; and said electronic device effective to present on the display a set of clinic note template representations associated with a particular category included in the categorical listing when the user device receives a user input that the particular category is selected. | 0.666945 |
8,523,572 | 1 | 40 | 1. A method for communicating visual images to a handicapped person, said method comprising the steps of: providing at least one device for physically transmitting information to said handicapped person; providing information about said visual images to said handicapped person using said at least one device; and said information providing step comprising delivering a physical signal representative of a key word describing a portion of a visual image to a first part of a body of said handicapped person using said at least one device and further comprising transmitting at least one physical input describing a dynamic element associated with said key word to a second part of the body of said handicapped person; and wherein Dividing the fingers of a hand of said handicapped person into a first group consisting of a pointer finger and a middle finger and into a second group consisting of a ring finger and a pinky and said transmitting step comprises transmitting information about a bad character to one of said fingers of said first group and transmitting information about a good character to one of said fingers of said second group. | 1. A method for communicating visual images to a handicapped person, said method comprising the steps of: providing at least one device for physically transmitting information to said handicapped person; providing information about said visual images to said handicapped person using said at least one device; and said information providing step comprising delivering a physical signal representative of a key word describing a portion of a visual image to a first part of a body of said handicapped person using said at least one device and further comprising transmitting at least one physical input describing a dynamic element associated with said key word to a second part of the body of said handicapped person; and wherein Dividing the fingers of a hand of said handicapped person into a first group consisting of a pointer finger and a middle finger and into a second group consisting of a ring finger and a pinky and said transmitting step comprises transmitting information about a bad character to one of said fingers of said first group and transmitting information about a good character to one of said fingers of said second group. 40. A method according to claim 1 , comprising a conceptual language construct for communicating by at least one of a receiving and transmitting at least one of a at least one physical touch(s), at least one simulated physical touch(s), at least one tap(s), at least one simulated tap(s), at least one vibration(s), and at least one simulated vibration(s) on at least one of a at least one device(s), at least one body part(s), and at least one simulated body part(s), of at least one person(s) who is at least one of a handicapped and a non-handicapped. | 0.500901 |
7,490,078 | 16 | 18 | 16. The method as recited in claim 14 , wherein in the step b), the window definition including window start, window end, tumbling and a window data limiting method is outputted. | 16. The method as recited in claim 14 , wherein in the step b), the window definition including window start, window end, tumbling and a window data limiting method is outputted. 18. The method as recited in claim 16 , wherein when it is confirmed that there is the pre-stored query condition evaluation result and the window data limiting method is a time, a boundary time is acquired by subtracting a tumbling value from the window end time, and the data transmitted before the boundary time are considered as the duplication input data and the data transmitted after the boundary time are considered as the new data. | 0.822581 |
10,127,218 | 1 | 8 | 1. A method for setting one or more properties of multiple instances of an object, the method performed by a computing device having a processor, the method comprising: with the processor, receiving from a user a selection identifying a template to apply to an object instance of an object of an object type, wherein the template sets one or more properties and corresponding template property values of the object instance of the object type; and in response to receiving the template selection, searching for the object instance that matches the object type of the selected template; and applying the selected template to the matched object instance of the object type, including: determining whether the template includes multiple levels of sub-objects; and in response to determining that the template includes multiple levels of sub-objects, determining whether a sub-object of the matched object instance that matches a hierarchical pattern of the selected template already exists in the matched object instance; and in response to determining that the sub-object of the matched object instance does not exist, creating a sub-object in the matched object instance according to the hierarchical pattern of the selected template and applying a template property and a corresponding template property value to the created sub-object according to the selected template. | 1. A method for setting one or more properties of multiple instances of an object, the method performed by a computing device having a processor, the method comprising: with the processor, receiving from a user a selection identifying a template to apply to an object instance of an object of an object type, wherein the template sets one or more properties and corresponding template property values of the object instance of the object type; and in response to receiving the template selection, searching for the object instance that matches the object type of the selected template; and applying the selected template to the matched object instance of the object type, including: determining whether the template includes multiple levels of sub-objects; and in response to determining that the template includes multiple levels of sub-objects, determining whether a sub-object of the matched object instance that matches a hierarchical pattern of the selected template already exists in the matched object instance; and in response to determining that the sub-object of the matched object instance does not exist, creating a sub-object in the matched object instance according to the hierarchical pattern of the selected template and applying a template property and a corresponding template property value to the created sub-object according to the selected template. 8. The method of claim 1 wherein in response to determining that the sub-object of the matched object instance exists, applying the template property and the corresponding template property value to the sub-object according to the selected template. | 0.629464 |
9,860,298 | 15 | 18 | 15. A digital processing system comprising: a processor; a random access memory (RAM); a non-transitory machine readable medium to store one or more instructions, which when retrieved into said RAM and executed by said processor causes said digital processing system to provide access to services implemented by stateless objects, said digital processing system performing the actions of: examining a first stateless object to determine a plurality of services implemented by said first stateless object and a specific ones of HTTP (Hypertext Transfer Protocol) verbs via which each of said plurality of services is accessible, wherein each service of said plurality of services is represented by a corresponding method in said first stateless object; sending for display said plurality of services implemented by said first stateless object, said plurality of services including a first service and a second service; receiving input data from an administrator indicating selection of a first set of services of said plurality of services, wherein said first set of services includes said first service but does not include said second service; and upon deployment of said first stateless object on an application server, providing access to said first set of services from said application server via corresponding HTTP verb, wherein said first service is provided access via a first HTTP verb and said second service is not accessible via any of said HTTP verbs. | 15. A digital processing system comprising: a processor; a random access memory (RAM); a non-transitory machine readable medium to store one or more instructions, which when retrieved into said RAM and executed by said processor causes said digital processing system to provide access to services implemented by stateless objects, said digital processing system performing the actions of: examining a first stateless object to determine a plurality of services implemented by said first stateless object and a specific ones of HTTP (Hypertext Transfer Protocol) verbs via which each of said plurality of services is accessible, wherein each service of said plurality of services is represented by a corresponding method in said first stateless object; sending for display said plurality of services implemented by said first stateless object, said plurality of services including a first service and a second service; receiving input data from an administrator indicating selection of a first set of services of said plurality of services, wherein said first set of services includes said first service but does not include said second service; and upon deployment of said first stateless object on an application server, providing access to said first set of services from said application server via corresponding HTTP verb, wherein said first service is provided access via a first HTTP verb and said second service is not accessible via any of said HTTP verbs. 18. The digital processing system of claim 15 , further performing the actions of: receiving a second input data indicating that said first service is to be accessible via a second HTTP verb also, wherein said providing provides access to said first service via both of said first HTTP verb and said second HTTP verb. | 0.852283 |
9,454,759 | 10 | 11 | 10. A system for maintaining consumer privacy in behavioral scoring, comprising: a first computing system; and a second computing system, wherein the first computing system includes a receiver configured to receive a plurality of account identifiers, and, for each account identifier, a corresponding first encrypted account identifier and corresponding disguised set of consumer characteristics from a second computing system, wherein the first encrypted account identifier is a produced via encryption of the corresponding account identifier using a first one-way encryption, and wherein the receiver of the first computing system is configured to encrypt each account identifier into a second encrypted account identifier using a second one-way encryption upon receipt, and a plurality of transaction data entries, wherein each transaction data entry includes data related to a payment transaction including at least a second encrypted account identifier and transaction data; and a processor configured to generate an algorithm configured to calculate a behavior prediction score corresponding to the behavior prediction request using disguised consumer characteristic values, wherein the generated algorithm is based on at least the transaction data included in each received transaction data entry and the disguised set of consumer characteristics mapped to the second encrypted account identifier included in the respective transaction data entry, and the first computing system does not receive any unencrypted account identifiers, any undisguised consumer characteristics, or any personally identifiable information. | 10. A system for maintaining consumer privacy in behavioral scoring, comprising: a first computing system; and a second computing system, wherein the first computing system includes a receiver configured to receive a plurality of account identifiers, and, for each account identifier, a corresponding first encrypted account identifier and corresponding disguised set of consumer characteristics from a second computing system, wherein the first encrypted account identifier is a produced via encryption of the corresponding account identifier using a first one-way encryption, and wherein the receiver of the first computing system is configured to encrypt each account identifier into a second encrypted account identifier using a second one-way encryption upon receipt, and a plurality of transaction data entries, wherein each transaction data entry includes data related to a payment transaction including at least a second encrypted account identifier and transaction data; and a processor configured to generate an algorithm configured to calculate a behavior prediction score corresponding to the behavior prediction request using disguised consumer characteristic values, wherein the generated algorithm is based on at least the transaction data included in each received transaction data entry and the disguised set of consumer characteristics mapped to the second encrypted account identifier included in the respective transaction data entry, and the first computing system does not receive any unencrypted account identifiers, any undisguised consumer characteristics, or any personally identifiable information. 11. The system of claim 10 , wherein the processor of the first computing system is further configured to calculate a behavior prediction score for each first encrypted account identifier by application of the corresponding disguised set of consumer characteristics to the generated algorithm; and first computing system further includes a transmitter configured to transmit at least the calculated behavior prediction score for each first encrypted account identifier and the corresponding first encrypted account identifier. | 0.500949 |
9,973,521 | 5 | 6 | 5. The method of claim 4 , wherein scanning, by the computer, each record of the security log stream comprises: wherein the scan is an n-gram scan that scans the each line starting at one end and advancing it way to the other end of the symbol string one symbol at a time; and wherein n is an integer that represents the number of characters that are being scan at one time. | 5. The method of claim 4 , wherein scanning, by the computer, each record of the security log stream comprises: wherein the scan is an n-gram scan that scans the each line starting at one end and advancing it way to the other end of the symbol string one symbol at a time; and wherein n is an integer that represents the number of characters that are being scan at one time. 6. The method of claim 5 , wherein the integer n is an integer chosen in the range of 2 to 9. | 0.978912 |
7,945,859 | 1 | 10 | 1. A method in a computing device for exchanging context attributes through an application programming interface of a facility, the method comprising: with at least one processor: receiving an enumeration request through the application programming interface for an enumeration of context attribute types; in response to receiving the enumeration request, providing to a requesting attribute consumer a list of context attribute types available from the facility, each of the context attributes being identified by a respective name; receiving an invocation request to provide an attribute value, the invocation request being generated by the requesting attribute consumer, the invocation request identifying the type of the context attribute whose value is to be provided, the context attribute type being in the list and being identified in the invocation request by the respective name in the list; and in response to receiving the invocation request, providing a value for the identified attribute to the requesting attribute consumer. | 1. A method in a computing device for exchanging context attributes through an application programming interface of a facility, the method comprising: with at least one processor: receiving an enumeration request through the application programming interface for an enumeration of context attribute types; in response to receiving the enumeration request, providing to a requesting attribute consumer a list of context attribute types available from the facility, each of the context attributes being identified by a respective name; receiving an invocation request to provide an attribute value, the invocation request being generated by the requesting attribute consumer, the invocation request identifying the type of the context attribute whose value is to be provided, the context attribute type being in the list and being identified in the invocation request by the respective name in the list; and in response to receiving the invocation request, providing a value for the identified attribute to the requesting attribute consumer. 10. The method of claim 1 wherein the computing device has a user, and wherein the identified attribute is information reflecting an aspect of the user. | 0.819905 |
9,130,651 | 1 | 49 | 1. An energy harvesting communication device configured with on chip signal booster apparatus; comprising: at least a communication apparatus; at least an antenna apparatus in association with an input and/or output device; at least a processor in communication with at least one of: said at least a communication apparatus; said at least an antenna apparatus; a charge platform in association with at least charging circuit; at least an interactive media in association with at least an interactive interface; an output device; and at least a sensor apparatus embedded in silicon substrate and etched and/or fused in nano-fiber and/or microfiber material, said at least a sensor apparatus in association with said at least a communication apparatus to provide at least one of an effective energy harvesting medium, communication clarity, communication medium, detection selectivity medium, and detection platform. | 1. An energy harvesting communication device configured with on chip signal booster apparatus; comprising: at least a communication apparatus; at least an antenna apparatus in association with an input and/or output device; at least a processor in communication with at least one of: said at least a communication apparatus; said at least an antenna apparatus; a charge platform in association with at least charging circuit; at least an interactive media in association with at least an interactive interface; an output device; and at least a sensor apparatus embedded in silicon substrate and etched and/or fused in nano-fiber and/or microfiber material, said at least a sensor apparatus in association with said at least a communication apparatus to provide at least one of an effective energy harvesting medium, communication clarity, communication medium, detection selectivity medium, and detection platform. 49. The energy harvesting communication device of claim 1 , wherein said communication apparatus further configured with at least one of: an energy platform operable for recharging at least a circuit having a source connected to at least a power terminal; a CMOS multiple antenna configured with at least a drain connected to a sensing node in association with the recharging circuit, at least a gate connected to a pre-charging circuit in communication with the source, further comprising at least a signal source; at least an application layer; at least an application layer message; at least a multimedia wireless sensor communication network. | 0.818845 |
8,738,630 | 19 | 21 | 19. The apparatus of claim 16 , wherein the storage unit comprises: a database; and an association unit, wherein the database is configured to store the annotation content, and wherein the association unit is configured to associate the annotation content stored in the database with the image corresponding thereto. | 19. The apparatus of claim 16 , wherein the storage unit comprises: a database; and an association unit, wherein the database is configured to store the annotation content, and wherein the association unit is configured to associate the annotation content stored in the database with the image corresponding thereto. 21. The apparatus of claim 19 , wherein the parsed image content information is merchandise information, and wherein the image is in jpg or jpeg format. | 0.971642 |
8,086,038 | 9 | 11 | 9. The method of claim 6 , wherein creating the feature index from the invisible junction feature descriptors comprises: creating a quantization tree; and adding a feature point to the quantization tree for the invisible junction feature descriptors. | 9. The method of claim 6 , wherein creating the feature index from the invisible junction feature descriptors comprises: creating a quantization tree; and adding a feature point to the quantization tree for the invisible junction feature descriptors. 11. The method of claim 9 , further comprising: extracting an additional invisible junction feature descriptor; and adding a second feature point to the quantization tree for the additional invisible junction feature descriptor. | 0.940314 |
4,046,382 | 1 | 8 | 1. A game apparatus comprising: a plurality of playing boards each having (comprising) a series of words (pertaining to the same topic) listed in a plurality of rows horizontally (and) disposed on the front face thereof, said words all comprising an equal number of letters and arranged in columns with said letters which occupy the same serial position in each of said words falling in the same column, each of said columns labelled with a numerical value, the rear face of said boards having said words and the definitions thereof disposed thereon the playing boards being divided into a plurality of sets wherein the playing boards within a set contain words pertaining to one specific topic, each playing board within a set having a unique arrangement of words; a master board comprising a plurality of juxtaposed (justaposed) columns each having one of said numerical values at the top of each of said columns and the letters of the alphabet in sequential order listed in each column; a score board with a grid disposed thereon the vertical rows thereof labelled with said topics (categories) and horizontal rows adapted to receive therein the players names, the vertical column furthermost from said names labelled "total"; a plurality of markers; and a plurality of cards comprising random combinations of said numerical values and the letters of the alphabet disposed thereon. | 1. A game apparatus comprising: a plurality of playing boards each having (comprising) a series of words (pertaining to the same topic) listed in a plurality of rows horizontally (and) disposed on the front face thereof, said words all comprising an equal number of letters and arranged in columns with said letters which occupy the same serial position in each of said words falling in the same column, each of said columns labelled with a numerical value, the rear face of said boards having said words and the definitions thereof disposed thereon the playing boards being divided into a plurality of sets wherein the playing boards within a set contain words pertaining to one specific topic, each playing board within a set having a unique arrangement of words; a master board comprising a plurality of juxtaposed (justaposed) columns each having one of said numerical values at the top of each of said columns and the letters of the alphabet in sequential order listed in each column; a score board with a grid disposed thereon the vertical rows thereof labelled with said topics (categories) and horizontal rows adapted to receive therein the players names, the vertical column furthermost from said names labelled "total"; a plurality of markers; and a plurality of cards comprising random combinations of said numerical values and the letters of the alphabet disposed thereon. 8. The game apparatus as claimed in claim 1, wherein said playing boards, said master board, and said score board comprise at the uppermost portions thereof the indicia "COIN-O" and juxtaposed thereunder the indicia "A FIVE LETTER THESAURUS." | 0.59396 |
7,844,957 | 1 | 8 | 1. A computer-implemented method for designing and compiling custom runtime components that provide improved processing of certain types of messages that comprise data objects serialized for transmission from one system to another, the method comprising: in a graphical user interface, receiving design-time input from a user for characterizing logical structure and physical structure of a particular message type in serialized form; based on said design-time input, creating metadata in markup language format that characterizes the logical structure and physical structure of the particular message type in serialized form; based on the metadata, automatically generating source code for de novo creation of custom runtime components comprising newly created custom source code that is highly optimized for runtime processing of said particular message type; and compiling the source code to create said custom runtime components for deployment in a runtime environment, so that at runtime, messages of the particular message type are processed with said custom runtime components in a manner that is highly optimized for the particular message type. | 1. A computer-implemented method for designing and compiling custom runtime components that provide improved processing of certain types of messages that comprise data objects serialized for transmission from one system to another, the method comprising: in a graphical user interface, receiving design-time input from a user for characterizing logical structure and physical structure of a particular message type in serialized form; based on said design-time input, creating metadata in markup language format that characterizes the logical structure and physical structure of the particular message type in serialized form; based on the metadata, automatically generating source code for de novo creation of custom runtime components comprising newly created custom source code that is highly optimized for runtime processing of said particular message type; and compiling the source code to create said custom runtime components for deployment in a runtime environment, so that at runtime, messages of the particular message type are processed with said custom runtime components in a manner that is highly optimized for the particular message type. 8. The method of claim 1 , wherein the custom runtime components are optimized to eliminate unnecessary conversion of message elements at runtime. | 0.699588 |
8,014,039 | 16 | 17 | 16. A non-transitory computer readable storage medium having stored thereon a program that when executed by a computer causes the computer to implement a process of managing a document using a document management system that includes an image data storing unit for storing a scanned image file, a scanning unit for reading a document, generating image data, acquiring a document identifier assigned to the document, assigning a file name generated based on the document identifier to the image data, and recording the image data in the image data storing unit as a scanned image file, a document management server including a destination folder for storing the scanned image file, and a file name conversion table, wherein the document management server acquires the scanned image file stored in the image data storing unit, specifies the destination folder based on the document identifier contained in the file name of the scanned image file using the file name conversion table, and stores the scanned image file in the destination folder. | 16. A non-transitory computer readable storage medium having stored thereon a program that when executed by a computer causes the computer to implement a process of managing a document using a document management system that includes an image data storing unit for storing a scanned image file, a scanning unit for reading a document, generating image data, acquiring a document identifier assigned to the document, assigning a file name generated based on the document identifier to the image data, and recording the image data in the image data storing unit as a scanned image file, a document management server including a destination folder for storing the scanned image file, and a file name conversion table, wherein the document management server acquires the scanned image file stored in the image data storing unit, specifies the destination folder based on the document identifier contained in the file name of the scanned image file using the file name conversion table, and stores the scanned image file in the destination folder. 17. The non-transitory computer readable medium according to claim 16 , wherein the acquiring further comprises acquiring, using the scanning unit, the document identifier assigned to the document from a bar code detected in the image data generated by the scanning unit. | 0.737403 |
5,510,981 | 14 | 19 | 14. A method as claimed in claim 13, characterized in that each target hypothesis comprises a series of target words selected from a vocabulary comprising words in the second language and a null word representing the absence of a word. | 14. A method as claimed in claim 13, characterized in that each target hypothesis comprises a series of target words selected from a vocabulary comprising words in the second language and a null word representing the absence of a word. 19. A method as claimed in claim 14, characterized in that: the context of the target word in the target hypothesis which is connected to a source word comprises at least one word having a part of speech in the target hypothesis; and the estimated conditional probability of occurrence of the source word, given the target word in the target hypothesis which is connected to the source word and given the context of the target word which is connected to the source word, comprises at least one function having a value dependent on the part of speech in the target hypothesis of at least one word in the context of the target word which is connected to the source word. | 0.818182 |
8,166,306 | 9 | 10 | 9. A method on a computer for verifying a digital signature using a semantics signature scheme comprising: receiving on the computer a digital signature for a compound message, wherein the compound message comprises; receiving a message, being base content, to be signed; adjoining assertions to the message; adjoining ontologies to the message, wherein the ontologies are a formal specification of vocabulary and rules used to state the assertions; adjoining a description of a reasoner to the message, wherein the reasoner is configured to validates the assertions against the corresponding ontologies, the reasoner is configured to validate a syntactic conformance of the assertions to the rules of the ontologies, and the reasoner is configured to determine subsumption relationships between terms in the assertion including when one term denotes entities more general than other entities; and adjoining world beliefs to the message, wherein the world beliefs provide background knowledge to the reasoner; wherein forming the compound message comprising on the computer comprises combining each of the message, the assertions, the ontologies, the description of the reasoner, and the world beliefs into a single semantic structure to be signed with a key as the compound message; and signing the compound message being the single semantic structure using a signature the key such that the message, the assertions, the ontologies, the description, and the world beliefs are included within the compound message signed by the key, wherein the assertions indicate an intended meaning of the key when verified verifying the digital signature; verifying that a structure of the compound message conforms to a semantic signature data schema; and in response to proper verification of the digital signature and the structure of the compound message on the computer, utilizing the described reasoner to verify a conformance of the assertions to the ontologies, wherein the assertions indicate an intended meaning of the digital signature. | 9. A method on a computer for verifying a digital signature using a semantics signature scheme comprising: receiving on the computer a digital signature for a compound message, wherein the compound message comprises; receiving a message, being base content, to be signed; adjoining assertions to the message; adjoining ontologies to the message, wherein the ontologies are a formal specification of vocabulary and rules used to state the assertions; adjoining a description of a reasoner to the message, wherein the reasoner is configured to validates the assertions against the corresponding ontologies, the reasoner is configured to validate a syntactic conformance of the assertions to the rules of the ontologies, and the reasoner is configured to determine subsumption relationships between terms in the assertion including when one term denotes entities more general than other entities; and adjoining world beliefs to the message, wherein the world beliefs provide background knowledge to the reasoner; wherein forming the compound message comprising on the computer comprises combining each of the message, the assertions, the ontologies, the description of the reasoner, and the world beliefs into a single semantic structure to be signed with a key as the compound message; and signing the compound message being the single semantic structure using a signature the key such that the message, the assertions, the ontologies, the description, and the world beliefs are included within the compound message signed by the key, wherein the assertions indicate an intended meaning of the key when verified verifying the digital signature; verifying that a structure of the compound message conforms to a semantic signature data schema; and in response to proper verification of the digital signature and the structure of the compound message on the computer, utilizing the described reasoner to verify a conformance of the assertions to the ontologies, wherein the assertions indicate an intended meaning of the digital signature. 10. The method of claim 9 , wherein the compound message further comprises world beliefs. | 0.914587 |
7,818,345 | 12 | 14 | 12. The method of claim 11 , further comprising: transferring the contents of the block corresponding to the text into a text file; integrating at least one specific basic code defined by a series of basic codes into said text file, the specific basic code being associated with said first part. | 12. The method of claim 11 , further comprising: transferring the contents of the block corresponding to the text into a text file; integrating at least one specific basic code defined by a series of basic codes into said text file, the specific basic code being associated with said first part. 14. The method of claim 12 , further comprising: interpreting the specific basic code into an specific interpreted code; associating said specific interpreted code with a location in the database. | 0.96687 |
7,809,548 | 33 | 34 | 33. The method of claim 32 , wherein determining at least one connecting relation between at least two of the plurality of sentences comprises determining at least one connecting relation based upon a similarity relation between the at least two of the plurality of sentences. | 33. The method of claim 32 , wherein determining at least one connecting relation between at least two of the plurality of sentences comprises determining at least one connecting relation based upon a similarity relation between the at least two of the plurality of sentences. 34. The method of claim 33 , wherein determining at least one connecting relation based upon the similarity relation comprises determining at least one connecting relation as a function of contents overlap between at least two of the plurality of sentences. | 0.927524 |
7,574,449 | 7 | 8 | 7. The computer storage medium of claim 1 , further comprising the steps of: performing transformations on the first article; and updating the vector array based on the transformations. | 7. The computer storage medium of claim 1 , further comprising the steps of: performing transformations on the first article; and updating the vector array based on the transformations. 8. The computer storage medium of claim 7 , wherein the performing transformations step performs at least one transformation selected from the group consisting of an inverse document frequency transform, a term frequency transform, Zipf's law filtering, and band-pass filtering. | 0.890119 |
8,140,340 | 13 | 17 | 13. A computer program product for utilizing a voiceprint to authorize a user to perform an operation restricted to authorized users, the computer program product comprising: one or more computer-readable, tangible storage devices; program instructions, stored on at least one of the one or more storage devices, to transmit an utterance request; program instructions, stored on at least one of the one or more storage devices, to receive a reply to the utterance request; program instructions, stored on at least one of the one or more storage devices, to process the utterance request to create a voiceprint, the voiceprint generated via a user assembly process; program instructions, stored on at least one of the one or more storage devices, to store the voiceprint in an audio attribute file that can be acquired, imported, exported and updated; program instructions, stored on at least one of the one or more storage devices, to associate the voiceprint with an avatar of a first virtual universe; and program instructions, stored on at least one of the one or more storage devices, to authorize the avatar to access services or authorize the avatar to perform operations that are restricted to authorized users; program instructions, stored on at least one of the one or more storage devices, to detect a movement of the avatar from the first virtual universe provided by a first computing device to a second virtual universe of a second computing device, different from the first computing device; and program instructions, stored on at least one of the one or more storage devices, to in response to detecting the movement of the avatar from the first virtual universe to the second virtual universe, transmit the audio attribute file to the second computing device for use by the second computing device to identify the avatar for accessing services or authorizing the avatar to perform operations that are restricted to authorized avatars on the second computing device. | 13. A computer program product for utilizing a voiceprint to authorize a user to perform an operation restricted to authorized users, the computer program product comprising: one or more computer-readable, tangible storage devices; program instructions, stored on at least one of the one or more storage devices, to transmit an utterance request; program instructions, stored on at least one of the one or more storage devices, to receive a reply to the utterance request; program instructions, stored on at least one of the one or more storage devices, to process the utterance request to create a voiceprint, the voiceprint generated via a user assembly process; program instructions, stored on at least one of the one or more storage devices, to store the voiceprint in an audio attribute file that can be acquired, imported, exported and updated; program instructions, stored on at least one of the one or more storage devices, to associate the voiceprint with an avatar of a first virtual universe; and program instructions, stored on at least one of the one or more storage devices, to authorize the avatar to access services or authorize the avatar to perform operations that are restricted to authorized users; program instructions, stored on at least one of the one or more storage devices, to detect a movement of the avatar from the first virtual universe provided by a first computing device to a second virtual universe of a second computing device, different from the first computing device; and program instructions, stored on at least one of the one or more storage devices, to in response to detecting the movement of the avatar from the first virtual universe to the second virtual universe, transmit the audio attribute file to the second computing device for use by the second computing device to identify the avatar for accessing services or authorizing the avatar to perform operations that are restricted to authorized avatars on the second computing device. 17. The computer program product of claim 13 , further comprising program instructions, stored on at least one of the one or more storage devices, to time-stamp the utterance and compare the timestamp to wall clock time to authenticate the utterance. | 0.905732 |
9,465,791 | 17 | 18 | 17. The system of claim 13 , wherein said one or more documents comprise documents being processed by at least one user, and wherein said processor is further configured to maintain a word count for each word in said one or more documents and wherein said word frequencies in said predefined misspelling criteria are based on said word counts. | 17. The system of claim 13 , wherein said one or more documents comprise documents being processed by at least one user, and wherein said processor is further configured to maintain a word count for each word in said one or more documents and wherein said word frequencies in said predefined misspelling criteria are based on said word counts. 18. The system of claim 17 , wherein said processor is further configured to suggest a correction of said at least one given word using said word within said predefined edit distance and having a frequency above said predefined high threshold. | 0.892668 |
9,940,394 | 1 | 5 | 1. A work graph generating apparatus, comprising: a memory; a component collection in the memory, including: a work graph generating component; a processor disposed in communication with the memory, and configured to issue a plurality of processing instructions from the component collection stored in the memory, wherein the processor issues instructions from the work graph generating component, stored in the memory, to: obtain, via at least one processor, a work graph generation request, wherein the work graph generation request includes group level access control data; determine, via at least one processor, a set of metadata access control carrying messages, wherein access control data associated with metadata access control carrying messages in the set of metadata access control carrying messages corresponds to the group level access control data; determine, via at least one processor, a set of users, wherein access control data associated with users in the set of users corresponds to the group level access control data; calculate, via at least one processor, from the perspective of each user in the set of users, a user priority score for each of the other users in the set of users, wherein a user priority score from the perspective of a first user for a second user is calculated based on the number of metadata access control carrying messages, in the set of metadata access control carrying messages, associated with the second user that were user-pertinent to the first user; determine, via at least one processor, a set of channels, wherein access control data associated with channels in the set of channels corresponds to the group level access control data; calculate, via at least one processor, from the perspective of each user in the set of users, a channel priority score for each of the channels in the set of channels, wherein a channel priority score from the perspective of a user for a channel is calculated based on the number of metadata access control carrying messages, in the set of metadata access control carrying messages, associated with that channel that were channel-pertinent to that user; determine, via at least one processor, a set of topics associated with the set of metadata access control carrying messages; calculate, via at least one processor, from the perspective of each user in the set of users, a topic priority score for each of the topics in the set of topics, wherein a topic priority score from the perspective of a user for a topic is calculated based on the number of metadata access control carrying messages, in the set of metadata access control carrying messages, associated with that topic that were topic-pertinent to that user; and generate, via at least one processor, a work graph data structure that includes a set of user objects corresponding to the set of users, wherein a user object for a user includes data regarding the calculated user priority scores, channel priority scores, and topic priority scores associated with that user, and wherein the work graph data structure is associated with group level access control data. | 1. A work graph generating apparatus, comprising: a memory; a component collection in the memory, including: a work graph generating component; a processor disposed in communication with the memory, and configured to issue a plurality of processing instructions from the component collection stored in the memory, wherein the processor issues instructions from the work graph generating component, stored in the memory, to: obtain, via at least one processor, a work graph generation request, wherein the work graph generation request includes group level access control data; determine, via at least one processor, a set of metadata access control carrying messages, wherein access control data associated with metadata access control carrying messages in the set of metadata access control carrying messages corresponds to the group level access control data; determine, via at least one processor, a set of users, wherein access control data associated with users in the set of users corresponds to the group level access control data; calculate, via at least one processor, from the perspective of each user in the set of users, a user priority score for each of the other users in the set of users, wherein a user priority score from the perspective of a first user for a second user is calculated based on the number of metadata access control carrying messages, in the set of metadata access control carrying messages, associated with the second user that were user-pertinent to the first user; determine, via at least one processor, a set of channels, wherein access control data associated with channels in the set of channels corresponds to the group level access control data; calculate, via at least one processor, from the perspective of each user in the set of users, a channel priority score for each of the channels in the set of channels, wherein a channel priority score from the perspective of a user for a channel is calculated based on the number of metadata access control carrying messages, in the set of metadata access control carrying messages, associated with that channel that were channel-pertinent to that user; determine, via at least one processor, a set of topics associated with the set of metadata access control carrying messages; calculate, via at least one processor, from the perspective of each user in the set of users, a topic priority score for each of the topics in the set of topics, wherein a topic priority score from the perspective of a user for a topic is calculated based on the number of metadata access control carrying messages, in the set of metadata access control carrying messages, associated with that topic that were topic-pertinent to that user; and generate, via at least one processor, a work graph data structure that includes a set of user objects corresponding to the set of users, wherein a user object for a user includes data regarding the calculated user priority scores, channel priority scores, and topic priority scores associated with that user, and wherein the work graph data structure is associated with group level access control data. 5. The apparatus of claim 1 , wherein the user-pertinent metadata access control carrying messages are any of: metadata access control carrying messages from the second user read by the first user, metadata access control carrying messages from the first user to the second user, metadata access control carrying messages from the second user responded to by the first user. | 0.810537 |
8,825,488 | 8 | 12 | 8. One or more computer-readable storage media devices having stored thereon multiple instructions executable by one or more processors to perform operations comprising: generating a sequential alignment of script words from script data to dialogue words from audio data, the audio data including timecodes associated with the dialogue words; matching at least some sequences of the script words to corresponding sequences of the dialogue words to determine hard alignment points; partitioning the sequential alignment of the script words into alignment sub-matrices, the bounds of the alignment sub- matrices being defined by adjacent hard alignment points, and the alignment sub-matrices comprising a sub-set of the script words and a corresponding sub-set of the dialogue words that occur between the hard alignment points; removing symbols and punctuation from the sub-set of script words in the alignment sub-matrices; aligning the sub-set of script words in each alignment sub-matrix of the alignment sub-matrices with a corresponding sub-set of dialogue words in each alignment sub-matrix of the alignment sub-matrices to determine a best fit alignment, comprising: filtering the sub-set of dialogue words to heuristically remove stop words; matching the sub-set of the script words and the corresponding sub-set of the dialogue words based on phonetic matching; using a word edit distance algorithm to match the script words in each alignment sub-matrix of the alignment sub-matrices with the corresponding sub-set of the dialogue words in each alignment sub-matrix of the alignment sub-matrices to determine soft alignment points; determine timecodes for the hard and soft alignment points; interpolating, based on the timecodes associated with at least some matched dialogue words, to determine timecodes for one or more unmatched script words; and generating time-aligned script data comprising the sub-set of the script words and their determined timecodes. | 8. One or more computer-readable storage media devices having stored thereon multiple instructions executable by one or more processors to perform operations comprising: generating a sequential alignment of script words from script data to dialogue words from audio data, the audio data including timecodes associated with the dialogue words; matching at least some sequences of the script words to corresponding sequences of the dialogue words to determine hard alignment points; partitioning the sequential alignment of the script words into alignment sub-matrices, the bounds of the alignment sub- matrices being defined by adjacent hard alignment points, and the alignment sub-matrices comprising a sub-set of the script words and a corresponding sub-set of the dialogue words that occur between the hard alignment points; removing symbols and punctuation from the sub-set of script words in the alignment sub-matrices; aligning the sub-set of script words in each alignment sub-matrix of the alignment sub-matrices with a corresponding sub-set of dialogue words in each alignment sub-matrix of the alignment sub-matrices to determine a best fit alignment, comprising: filtering the sub-set of dialogue words to heuristically remove stop words; matching the sub-set of the script words and the corresponding sub-set of the dialogue words based on phonetic matching; using a word edit distance algorithm to match the script words in each alignment sub-matrix of the alignment sub-matrices with the corresponding sub-set of the dialogue words in each alignment sub-matrix of the alignment sub-matrices to determine soft alignment points; determine timecodes for the hard and soft alignment points; interpolating, based on the timecodes associated with at least some matched dialogue words, to determine timecodes for one or more unmatched script words; and generating time-aligned script data comprising the sub-set of the script words and their determined timecodes. 12. The one or more computer-readable storage media devices of claim 8 , wherein the best fit alignment is the alignment with the lowest indication of possible error. | 0.752239 |
8,793,260 | 15 | 16 | 15. The computer system of claim 10 , wherein the entity recognition component identifies an expanded set of entities related to one or more entities specified in the search query, and identifies the plurality of entities from the query terms of the search query and from the expanded set of entities. | 15. The computer system of claim 10 , wherein the entity recognition component identifies an expanded set of entities related to one or more entities specified in the search query, and identifies the plurality of entities from the query terms of the search query and from the expanded set of entities. 16. The computer system of claim 15 , wherein the entity recognition component identifies the expanded set of entities according to common attributes between the one or more entities specified in the search query. | 0.917249 |
8,326,595 | 2 | 3 | 2. The method of claim 1 , wherein the Devanagari state machine comprises eight states including: initial, matra, vowel, vowel modifier, halant, nukta, consonant, and invalid. | 2. The method of claim 1 , wherein the Devanagari state machine comprises eight states including: initial, matra, vowel, vowel modifier, halant, nukta, consonant, and invalid. 3. The method of claim 2 , wherein a validity of a first character of a word in the Devanagari text is determined by the initial state. | 0.941609 |
9,214,156 | 1 | 3 | 1. A method of automatically managing a dialogue with a user, comprising: transforming, at a dialogue manager, user-input data received from a client dialogue application into a generic semantic representation, the generic semantic representation being independent of a language and an input modality associated with the user-input data; determining, by the dialogue manager, whether the user-input data is indicative of a new request by the user or a refinement request by the user refining one or more previous requests by the user, based on the generic semantic representation and at least one of a maintained state of the dialogue, general knowledge data representing one or more concepts, and data representing history of the dialogue; sending multi-facet output data, indicative of one or more actions for the client dialogue application to perform, the one or more actions being determined based on a result of said determining whether the generic semantic representation is indicative of the new request by the user or the refinement by the user refining the one or more previous requests by the user; sending a query to a backend end system for retrieving data associated with the determined user-request, the query being generated based on the determined user-request and the maintained state of the dialogue; receiving a response to the query from the backend system; and updating a list of data items based on the response received from the backend system. | 1. A method of automatically managing a dialogue with a user, comprising: transforming, at a dialogue manager, user-input data received from a client dialogue application into a generic semantic representation, the generic semantic representation being independent of a language and an input modality associated with the user-input data; determining, by the dialogue manager, whether the user-input data is indicative of a new request by the user or a refinement request by the user refining one or more previous requests by the user, based on the generic semantic representation and at least one of a maintained state of the dialogue, general knowledge data representing one or more concepts, and data representing history of the dialogue; sending multi-facet output data, indicative of one or more actions for the client dialogue application to perform, the one or more actions being determined based on a result of said determining whether the generic semantic representation is indicative of the new request by the user or the refinement by the user refining the one or more previous requests by the user; sending a query to a backend end system for retrieving data associated with the determined user-request, the query being generated based on the determined user-request and the maintained state of the dialogue; receiving a response to the query from the backend system; and updating a list of data items based on the response received from the backend system. 3. The method according to claim 1 further comprising updating the history of the dialogue based on the generic semantic representation generated or the list of data updated. | 0.888175 |
8,386,405 | 11 | 17 | 11. A computer-readable non-transitory storage medium storing a set of computer instructions for interacting with a user, wherein the set of computer instructions, when executed on a computer having access to an electronic knowledge database, causes the computer to, automatically: (a) generate a structured representation of a received user input; (b) compare the structured representation of the received user input with a plurality of expected user statement fields that are entries in the electronic knowledge database, and are associated with respective action fields specifying at least one action; and (c) when one of the plurality of expected user statements fields matches the structured representation of the received user input, cause the at least one action specified by the action field associated with the matching one of the plurality of expected user statement fields to be performed; further, the set of computer instructions, when executed on the computer, causes the computer to: (i) when a match is identified in part (c), generate a second structural representation of a second received user input; and (ii) compare the second structured representation of the second received user input with a second plurality of expected user statement fields that are entries in the electronic knowledge database and are associated with respective action fields specifying at least one action; (A) wherein the entries of the knowledge database are arranged in a hierarchical structure; (B) wherein each entry in the electronic knowledge database also comprises an associated identification field indicative of a position in the hierarchical structure; and (C) wherein all the positions indicated by the identification fields associated with the second plurality of expected user statement fields substantially match; and (iii) when one of the second plurality of expected user statements fields matches the second structured representation of the second received user input, cause the at least one action specified by the action field associated with the matching one of second plurality of expected user statement fields to be performed. | 11. A computer-readable non-transitory storage medium storing a set of computer instructions for interacting with a user, wherein the set of computer instructions, when executed on a computer having access to an electronic knowledge database, causes the computer to, automatically: (a) generate a structured representation of a received user input; (b) compare the structured representation of the received user input with a plurality of expected user statement fields that are entries in the electronic knowledge database, and are associated with respective action fields specifying at least one action; and (c) when one of the plurality of expected user statements fields matches the structured representation of the received user input, cause the at least one action specified by the action field associated with the matching one of the plurality of expected user statement fields to be performed; further, the set of computer instructions, when executed on the computer, causes the computer to: (i) when a match is identified in part (c), generate a second structural representation of a second received user input; and (ii) compare the second structured representation of the second received user input with a second plurality of expected user statement fields that are entries in the electronic knowledge database and are associated with respective action fields specifying at least one action; (A) wherein the entries of the knowledge database are arranged in a hierarchical structure; (B) wherein each entry in the electronic knowledge database also comprises an associated identification field indicative of a position in the hierarchical structure; and (C) wherein all the positions indicated by the identification fields associated with the second plurality of expected user statement fields substantially match; and (iii) when one of the second plurality of expected user statements fields matches the second structured representation of the second received user input, cause the at least one action specified by the action field associated with the matching one of second plurality of expected user statement fields to be performed. 17. The storage medium of claim 11 wherein, further, the set of computer instructions, when executed on the computer, causes the computer to: (i) when no match is identified in part (c), compare the structured representation of the received user input with each of a second plurality of expected user statement fields that are entries in the electronic knowledge database and are associated with respective action fields specifying at least one action; (A) wherein each entry in the electronic knowledge database further comprises an associated context field specifying a context; and (B) wherein each context specified by the context fields associated with the second plurality of expected user statements does not match any of the contexts specified by the context fields associated the plurality of expected user statement fields in part (b); and (ii) when one of the second plurality of expected user statements fields matches the structured representation of the received user input, cause the at least one action specified by the action field associated with the matching one of the second plurality of expected user statement fields to be performed. | 0.500432 |
9,619,571 | 13 | 14 | 13. A non-transitory computer readable medium having stored thereon computer executable instructions comprising: receiving, by an entity extraction computer, user input of search query parameters; extracting, by the entity extraction computer, a plurality of entities from the search query parameters by comparing each entity in the plurality of extracted entities with an entity co-occurrence in-memory database that includes a confidence score indicative of a degree of certainty of co-occurrence of an extracted entity with one or more related entities in an electronic data corpus, wherein the entity co-occurrence database further comprises one or more entries for the plurality of entities, and wherein each entry of the one or more entries for a given entity of the plurality of entities contains its semantically related entities, and wherein the co-occurrence is an instance of an entity of plurality of entities identified by an entry of the one or more entries in the entity co-occurrence database, and wherein the semantically-related entity corresponds to a model indicating distinct entities, assigning, by the entity extraction computer, an index identifier (index ID) to each of the entities in the plurality of extracted entities; disambiguating, by the entity extraction computer, each of the entities in the plurality of extracted entities from one another based on relatedness of index IDs; identifying, by the entity extraction computer, a subset of entities associated with each of the entities in the plurality of extracted entities based on relatedness of index IDs; linking, by the entity extraction computer, each entity to the associated subset of entities based at least on confidence scores; saving, by the entity extraction computer, the index ID for each of the plurality of extracted entities in the electronic data corpus, the electronic data corpus being indexed by an index ID corresponding to each of the one or more related entities; searching, by a search server computer, the entity indexed electronic data corpus to locate the plurality of extracted entities and identify index IDs of data records in which at least two of the plurality of extracted entities co-occur; and building, by the search server computer, a search result list having data records corresponding to the identified index IDs. | 13. A non-transitory computer readable medium having stored thereon computer executable instructions comprising: receiving, by an entity extraction computer, user input of search query parameters; extracting, by the entity extraction computer, a plurality of entities from the search query parameters by comparing each entity in the plurality of extracted entities with an entity co-occurrence in-memory database that includes a confidence score indicative of a degree of certainty of co-occurrence of an extracted entity with one or more related entities in an electronic data corpus, wherein the entity co-occurrence database further comprises one or more entries for the plurality of entities, and wherein each entry of the one or more entries for a given entity of the plurality of entities contains its semantically related entities, and wherein the co-occurrence is an instance of an entity of plurality of entities identified by an entry of the one or more entries in the entity co-occurrence database, and wherein the semantically-related entity corresponds to a model indicating distinct entities, assigning, by the entity extraction computer, an index identifier (index ID) to each of the entities in the plurality of extracted entities; disambiguating, by the entity extraction computer, each of the entities in the plurality of extracted entities from one another based on relatedness of index IDs; identifying, by the entity extraction computer, a subset of entities associated with each of the entities in the plurality of extracted entities based on relatedness of index IDs; linking, by the entity extraction computer, each entity to the associated subset of entities based at least on confidence scores; saving, by the entity extraction computer, the index ID for each of the plurality of extracted entities in the electronic data corpus, the electronic data corpus being indexed by an index ID corresponding to each of the one or more related entities; searching, by a search server computer, the entity indexed electronic data corpus to locate the plurality of extracted entities and identify index IDs of data records in which at least two of the plurality of extracted entities co-occur; and building, by the search server computer, a search result list having data records corresponding to the identified index IDs. 14. The computer readable medium of claim 13 wherein the instructions further comprise sorting, by the search server computer, the search result list by relevance based on the confidence score and forwarding, by the search server computer, the sorted search result list to a user device. | 0.63486 |
8,046,322 | 12 | 15 | 12. A computer-based system for constraint-based mining of activity patterns within a framework, said system comprising: a data input; a plurality of data mining tools within the framework and operable to run on said system, said data mining tools configured to search data received at said data input for one or both of temporal and spatial patterns for activities of interest within one or more scenarios, each pattern including one or more atoms, each atom defined on a predicate that includes one or more typed arguments; a plurality of constraints, said constraints based on knowledge and experiences, and operable to cause said system to determine whether one or more patterns satisfies the said constraints, said constraints organized based on a subsumption relationship among the constraints and including a syntactic filter constraint configured to utilize a sequence of modes to filter patterns and avoid generation of patterns with redundant atoms, a semantic filter constraint having a minimum frequency threshold, a sequence of modes and a Boolean expression on arguments in the modes, and at least one of a generation rule constraint, a maximum length constraint, an extended length constraint, and a complex constraint; and at least one database configured for operation as a pattern repository. | 12. A computer-based system for constraint-based mining of activity patterns within a framework, said system comprising: a data input; a plurality of data mining tools within the framework and operable to run on said system, said data mining tools configured to search data received at said data input for one or both of temporal and spatial patterns for activities of interest within one or more scenarios, each pattern including one or more atoms, each atom defined on a predicate that includes one or more typed arguments; a plurality of constraints, said constraints based on knowledge and experiences, and operable to cause said system to determine whether one or more patterns satisfies the said constraints, said constraints organized based on a subsumption relationship among the constraints and including a syntactic filter constraint configured to utilize a sequence of modes to filter patterns and avoid generation of patterns with redundant atoms, a semantic filter constraint having a minimum frequency threshold, a sequence of modes and a Boolean expression on arguments in the modes, and at least one of a generation rule constraint, a maximum length constraint, an extended length constraint, and a complex constraint; and at least one database configured for operation as a pattern repository. 15. A computer-based system according to claim 12 wherein to search data received at said data input, said system is configured to: initialize the search by creating a single pattern using a target predicate; and invoke a refining process with the single pattern. | 0.571661 |
7,707,167 | 9 | 10 | 9. The method of claim 1 , wherein creating the knowledge interchange profile further comprises for each of the items of interest: performing an interest analysis; and performing a noun phrase analysis. | 9. The method of claim 1 , wherein creating the knowledge interchange profile further comprises for each of the items of interest: performing an interest analysis; and performing a noun phrase analysis. 10. The method of claim 9 , wherein performing the interest analysis comprises: identifying keywords within the items of interest; assigning an interest weight value to each of the keywords respectively; adjusting the interest weight value of each of the keywords depending on the location of the keywords within the item of interest; adjusting the interest weight value of each of the keywords depending on the frequency of occurrence of the keywords in the item of interest; and eliminating ones of the keywords having interest weight values not greater than a predetermined value. | 0.777141 |
7,584,092 | 12 | 17 | 12. A computer-implemented method of selecting boundaries for application of a paraphrase alternation pattern to an input string, the method comprising: utilizing a computer processor that is a functional component of the computer to apply the paraphrase alternation pattern multiple times to the input string with multiple boundaries so as to create a plurality of alternation alternatives, wherein each alternation alternative is a different sequence of words included in the input string; generating a language model based on a set of test data and then applying the language model to the plurality of alternation alternatives to determine which, based on frequency within the set of test data, is a relatively commonly used sequence of words; and wherein applying so as to create a plurality of alternation alternatives comprise applying so as to switch different combinations of words around a word in the input string identified as being a pivot word. | 12. A computer-implemented method of selecting boundaries for application of a paraphrase alternation pattern to an input string, the method comprising: utilizing a computer processor that is a functional component of the computer to apply the paraphrase alternation pattern multiple times to the input string with multiple boundaries so as to create a plurality of alternation alternatives, wherein each alternation alternative is a different sequence of words included in the input string; generating a language model based on a set of test data and then applying the language model to the plurality of alternation alternatives to determine which, based on frequency within the set of test data, is a relatively commonly used sequence of words; and wherein applying so as to create a plurality of alternation alternatives comprise applying so as to switch different combinations of words around a word in the input string identified as being a pivot word. 17. The method of claim 12 , wherein applying so as to create a plurality of alternation alternatives comprises applying so as to switch different combinations of words around a pivot word. | 0.849762 |
8,050,888 | 1 | 3 | 1. A method of automatically applying hypothesis testing to at least one data set, the method comprising using a computer to carry out the steps of: providing a plurality of statistical tests applicable to the at least one data set, the tests having a variety of characteristics and associated conventions; seeking an indication as to at least one characteristic of the data set; selecting a test from among the plurality of tests based on the indications and associated conventions; providing a notification of the nature of the selected test, the indications and established conventions; characterizing the data set, including establishing test criteria, selecting an appropriate reference test value depending on the established test criteria; and eliciting an indication of a description of the data of interest; constructing a null hypothesis statement and an alternative hypothesis statement; receiving an indication of a significance level, conducting the selected test including calculating the values of the test statistic, reference values, confidence bounds and p-values, comparing the calculated p-value to the indicated significance level, comparing the value of the test statistic to one or more reference values, and assessing the confidence bounds in view of the null hypothesis statement; stating a conclusion based on the selected test and the indicated test criteria, the conclusion including whether to reject the null hypothesis or not reject the null hypothesis, and the basis for the conclusion. | 1. A method of automatically applying hypothesis testing to at least one data set, the method comprising using a computer to carry out the steps of: providing a plurality of statistical tests applicable to the at least one data set, the tests having a variety of characteristics and associated conventions; seeking an indication as to at least one characteristic of the data set; selecting a test from among the plurality of tests based on the indications and associated conventions; providing a notification of the nature of the selected test, the indications and established conventions; characterizing the data set, including establishing test criteria, selecting an appropriate reference test value depending on the established test criteria; and eliciting an indication of a description of the data of interest; constructing a null hypothesis statement and an alternative hypothesis statement; receiving an indication of a significance level, conducting the selected test including calculating the values of the test statistic, reference values, confidence bounds and p-values, comparing the calculated p-value to the indicated significance level, comparing the value of the test statistic to one or more reference values, and assessing the confidence bounds in view of the null hypothesis statement; stating a conclusion based on the selected test and the indicated test criteria, the conclusion including whether to reject the null hypothesis or not reject the null hypothesis, and the basis for the conclusion. 3. The method set forth in claim 1 wherein determining the test includes seeking an indication as to the time ordered nature of the data set including generating a notification of process stability, seeking an indication of the nature of data as being attribute data or continuous data and, if the indication is that the data are attribute data, then seeking an indication as to the number of samples from which the data are drawn, an indication of sample size, and seeking an indication of normality of the data, wherein, if the indication is that the data are continuous, then seeking an indication as to the number of samples from which the data are drawn, an indication of sample size and an indication as to whether the data are normal, not normal, or if the distribution is unknown, wherein, if the indication is that the data are one of not normal or unknown, then providing notifications to use one of a normality test to determine normality, non-parametric tests, and data transformation functions. | 0.557168 |
8,361,117 | 1 | 12 | 1. A spinal cross connector, comprising: a first connector element for engaging a spinal fixation element, the first connector element having a female member; a second connector element for engaging a spinal fixation element, the second connector element having a male member that is receivable within the female member such that the male member is (i) adjustably slidable within the female member along a longitudinal axis of the male member, (ii) rotatable about the longitudinal axis within the female member, and (iii) pivotable within the female member such that the longitudinal axis can be angularly oriented relative to a longitudinal axis of the first connector element; and a fastening element adapted to be disposed within the female member to engage and lock the male member in a fixed position relative to the female member; wherein the male member is disposed through the female member and the male member includes a retaining element on a terminal end thereof that is adapted to prevent removal of the male member from the female member, the retaining element being a discrete element from the male member that is disposed external to the female member when the male member is disposed through the female member. | 1. A spinal cross connector, comprising: a first connector element for engaging a spinal fixation element, the first connector element having a female member; a second connector element for engaging a spinal fixation element, the second connector element having a male member that is receivable within the female member such that the male member is (i) adjustably slidable within the female member along a longitudinal axis of the male member, (ii) rotatable about the longitudinal axis within the female member, and (iii) pivotable within the female member such that the longitudinal axis can be angularly oriented relative to a longitudinal axis of the first connector element; and a fastening element adapted to be disposed within the female member to engage and lock the male member in a fixed position relative to the female member; wherein the male member is disposed through the female member and the male member includes a retaining element on a terminal end thereof that is adapted to prevent removal of the male member from the female member, the retaining element being a discrete element from the male member that is disposed external to the female member when the male member is disposed through the female member. 12. The spinal cross connector of claim 1 , wherein the retaining element has a diameter greater than a width of a female opening formed in the female member for receiving the male member, the retaining element thereby retaining the male member within the female member. | 0.736328 |
7,639,899 | 14 | 15 | 14. The digital pictorial book system as claimed in claim 1 , further comprising an image capturing control means for controlling the operation of said image capturing sensor on the basis of the content of the distinguishing feature selected by said distinguishing feature selecting means. | 14. The digital pictorial book system as claimed in claim 1 , further comprising an image capturing control means for controlling the operation of said image capturing sensor on the basis of the content of the distinguishing feature selected by said distinguishing feature selecting means. 15. The digital pictorial book system as claimed in claim 14 further comprising a featuring part searching means for searching for an image showing a part of the main object, wherein the distinguishing feature shows the part of the object, and said image capturing control means controls the operation of said image capturing sensor on the basis of the image showing the part searched out by said featuring part searching means. | 0.890983 |
9,349,132 | 1 | 6 | 1. A method in a system of a host organization, the system having at least a processor and a memory therein, wherein the method comprises: generating indices from a dataset of columns and rows, the indices representing probabilistic relationships between the rows and the columns of the dataset; storing the indices within a database system of the host organization; exposing the database system of the host organization via a request interface; receiving, at the request interface, a query for the database system specifying a GROUP command term and a specified column as a parameter for the GROUP command term; querying the database system using the GROUP command term and passing the specified column to generate a predictive record set; returning the predictive record set responsive to the query, the predictive record set having a plurality of groups specified therein, each returned group of the returned groups of the predictive record set including a group of one or more rows of the dataset; and wherein a confidence indicator returned with each respective row of the one or more rows specified within each group of the plurality of groups returned with the predictive record set ranges from a minimum of 0 indicating a lowest possible confidence in a result that the respective row belongs to the group specified to a maximum of 1 indicating a highest possible confidence in the result that the respective row belongs to the group specified. | 1. A method in a system of a host organization, the system having at least a processor and a memory therein, wherein the method comprises: generating indices from a dataset of columns and rows, the indices representing probabilistic relationships between the rows and the columns of the dataset; storing the indices within a database system of the host organization; exposing the database system of the host organization via a request interface; receiving, at the request interface, a query for the database system specifying a GROUP command term and a specified column as a parameter for the GROUP command term; querying the database system using the GROUP command term and passing the specified column to generate a predictive record set; returning the predictive record set responsive to the query, the predictive record set having a plurality of groups specified therein, each returned group of the returned groups of the predictive record set including a group of one or more rows of the dataset; and wherein a confidence indicator returned with each respective row of the one or more rows specified within each group of the plurality of groups returned with the predictive record set ranges from a minimum of 0 indicating a lowest possible confidence in a result that the respective row belongs to the group specified to a maximum of 1 indicating a highest possible confidence in the result that the respective row belongs to the group specified. 6. The method of claim 1 , wherein each row corresponds to a registered voter and wherein the groupings specified by the predictive record define naturally targetable voting blocs with each voting bloc predicted to be likely to react similarly to one or more of a common campaign message, a common campaign issue, and common campaign advertising. | 0.811547 |
9,424,336 | 11 | 15 | 11. A machine-readable medium having stored thereon instructions which, when executed by a machine, cause the machine to perform operations comprising: monitoring, by a local query platform of the database system, data at a database communicatively coupled to the local query platform, wherein monitoring includes detecting one or more data occurrences in the data, wherein the one or more data occurrences include one or more modifications to one or more portions of the data relating to one or more tenants in a multi-tenant environment; transmitting, by the local query platform, the one or more data occurrences from the database to a remote data processing entity to process the one or more data occurrences, wherein results of the processing of the one or more data occurrences are cached at the database by the remote processing entity over a network, wherein the one or more data occurrences are assigned one or more classifications relating to the one or more tenants; mapping, by the local query platform, one or more values to the results of the one or more data occurrences based on the one or more classifications; and generating, by the local query platform, search data from the results based on the mapped values such that a customized portion of the search data is suggested to a tenant in response to a query placed by the tenant. | 11. A machine-readable medium having stored thereon instructions which, when executed by a machine, cause the machine to perform operations comprising: monitoring, by a local query platform of the database system, data at a database communicatively coupled to the local query platform, wherein monitoring includes detecting one or more data occurrences in the data, wherein the one or more data occurrences include one or more modifications to one or more portions of the data relating to one or more tenants in a multi-tenant environment; transmitting, by the local query platform, the one or more data occurrences from the database to a remote data processing entity to process the one or more data occurrences, wherein results of the processing of the one or more data occurrences are cached at the database by the remote processing entity over a network, wherein the one or more data occurrences are assigned one or more classifications relating to the one or more tenants; mapping, by the local query platform, one or more values to the results of the one or more data occurrences based on the one or more classifications; and generating, by the local query platform, search data from the results based on the mapped values such that a customized portion of the search data is suggested to a tenant in response to a query placed by the tenant. 15. The machine-readable medium of claim 11 , wherein the one or more predictive answers are based on processing of data occurrences by the remote data processing entity, wherein the one or more predictive answers are further based on a search history of the tenant such that a first portion of a predictive answer is pre-computed to match with a second portion of the predictive answer, wherein a first value of the first portion is predictively mapped to a second value of the second portion. | 0.581356 |
9,110,659 | 7 | 8 | 7. The system of claim 6 , wherein the policy processor is further configured to perform: identifying additional classes in the plurality of classes; creating additional class instances for each of the identified additional classes; and connecting the class instances. | 7. The system of claim 6 , wherein the policy processor is further configured to perform: identifying additional classes in the plurality of classes; creating additional class instances for each of the identified additional classes; and connecting the class instances. 8. The system of claim 7 , wherein the policy processor is further configured to perform: invoking a source code generator method on each instance of a relationship class in the connected class instances; and wherein generating source code further comprises creating a single source code file comprising source code configured to generate the connected class instances. | 0.892168 |
9,244,901 | 10 | 16 | 10. A non-transitory computer readable medium comprising instructions that when executed by a processor, cause the processor to perform: analyzing utterances using one or more rules; assigning a tag to the analyzed utterances based on the one or more rules by a tagging server; and generating at least a report based on the one or more rules to include a unique utterance for each tag, the unique utterance displayed in a descending order. | 10. A non-transitory computer readable medium comprising instructions that when executed by a processor, cause the processor to perform: analyzing utterances using one or more rules; assigning a tag to the analyzed utterances based on the one or more rules by a tagging server; and generating at least a report based on the one or more rules to include a unique utterance for each tag, the unique utterance displayed in a descending order. 16. The computer readable medium according to claim 10 , further comprising instructions for determining statistics for each assigned tag. | 0.598837 |
8,166,392 | 23 | 25 | 23. A machine-readable storage device having instructions stored thereon for execution by a processor to perform a method comprising: receiving sensor input, the sensor input indicating a user context; receiving a plurality of messages comprising text; receiving user input associated with each of at least a portion of the plurality of messages, the user input comprising, for each message, an indication of whether the user wishes to be interrupted with that message in an indicated context; based on the user input and the text of the portion of the plurality of messages, training a message classifier to associate a priority with a received message based on text of the message and a context of the user, as indicated by the sensor input, at a time of receipt of the received message; receiving a subsequent message at a subsequent time; generating a priority of the subsequent message based on the message classifier and an indication of user context at the subsequent time; and outputting the priority. | 23. A machine-readable storage device having instructions stored thereon for execution by a processor to perform a method comprising: receiving sensor input, the sensor input indicating a user context; receiving a plurality of messages comprising text; receiving user input associated with each of at least a portion of the plurality of messages, the user input comprising, for each message, an indication of whether the user wishes to be interrupted with that message in an indicated context; based on the user input and the text of the portion of the plurality of messages, training a message classifier to associate a priority with a received message based on text of the message and a context of the user, as indicated by the sensor input, at a time of receipt of the received message; receiving a subsequent message at a subsequent time; generating a priority of the subsequent message based on the message classifier and an indication of user context at the subsequent time; and outputting the priority. 25. The storage device of claim 23 wherein the message classifier comprises one of a Bayesian classifier and a support vector machine classifier. | 0.831395 |
7,630,552 | 38 | 42 | 38. A method of assessing a document using a computer system, comprising: providing a document to the computer system, wherein the document comprises at least two non-signature information fields; analyzing, using the computer system, a correlation of information between two or more of the non-signature information fields, wherein the analysis of a first non-signature information field of the document is dependent on what information is in a second non-signature information field of the document; and comparing, using the computer system, writing in the first non-signature information field of the document to information from a corresponding non-signature information field of at least one other document, wherein the comparison is based on the correlation analysis between the first non-signature information field and the second non-signature information field. | 38. A method of assessing a document using a computer system, comprising: providing a document to the computer system, wherein the document comprises at least two non-signature information fields; analyzing, using the computer system, a correlation of information between two or more of the non-signature information fields, wherein the analysis of a first non-signature information field of the document is dependent on what information is in a second non-signature information field of the document; and comparing, using the computer system, writing in the first non-signature information field of the document to information from a corresponding non-signature information field of at least one other document, wherein the comparison is based on the correlation analysis between the first non-signature information field and the second non-signature information field. 42. The method of claim 38 , wherein the first non-signature information field is a legal or courtesy amount, wherein the second non-signature field information field is a payee field, wherein comparing writing in the first non-signature information field document to information from a corresponding non-signature information field of at least one other document comprises determining whether the amount in the first non-signature information field of the document matches at least one amount from a lexicon of amounts associated with the payee. | 0.500914 |
9,244,902 | 13 | 18 | 13. A system comprising: a storage device; and a computing device in communication with the storage device, the computing device configured to: based on a user interaction, capture a text string that is within an application and that is in a first language, wherein the text string includes a token, wherein the application is executed on a client device, and wherein the user interaction causes the text string to be presented on the client device; in accordance with the user interaction, substitute the token with at least one word, and thereby providing an updated text string which is in the first language, wherein the substituting of the token is based on a language structure of a second language; transmit the updated text string to a translation device; obtain, from the translation device, a translated text string which is in the second language, wherein the translated text string is a translation of the updated text string; localize the captured text string by using the translated text string; and cause the client device to display the localized text string. | 13. A system comprising: a storage device; and a computing device in communication with the storage device, the computing device configured to: based on a user interaction, capture a text string that is within an application and that is in a first language, wherein the text string includes a token, wherein the application is executed on a client device, and wherein the user interaction causes the text string to be presented on the client device; in accordance with the user interaction, substitute the token with at least one word, and thereby providing an updated text string which is in the first language, wherein the substituting of the token is based on a language structure of a second language; transmit the updated text string to a translation device; obtain, from the translation device, a translated text string which is in the second language, wherein the translated text string is a translation of the updated text string; localize the captured text string by using the translated text string; and cause the client device to display the localized text string. 18. The system of claim 13 , wherein the computing device is further configured to substitute the token with a word in the first language when a translation of the captured text string is unavailable in the storage device. | 0.682857 |
8,060,491 | 16 | 20 | 16. The apparatus of claim 15 , wherein the text associated with the content items comprises tag data input by one or more users. | 16. The apparatus of claim 15 , wherein the text associated with the content items comprises tag data input by one or more users. 20. The apparatus of claim 16 , wherein the metadata comprises at least one of time information regarding a time the at least one content item was created and location information regarding a location the at least one content item was created. | 0.916895 |
9,658,990 | 11 | 12 | 11. The computer program product of claim 10 wherein the actions further comprise: specially merging two or more of the plurality of sections by: identifying a first section at a first set of coordinate positions, wherein the first set of coordinate positions forms a first rectangular boundary around the first section, and wherein the identification of the first section is based on at least one special rule; identifying a second section based on at a second set of coordinate positions, wherein the second set of coordinate positions forms a second rectangular boundary around the second section, and wherein the identification of the second section is based on a proximity to the first section; merging the first and second sections to form one of the increasingly larger sections; and repeating the building of the zero or more directional links between the increasingly larger section formed by the merger of the first and second sections with the other sections included in the plurality of sections. | 11. The computer program product of claim 10 wherein the actions further comprise: specially merging two or more of the plurality of sections by: identifying a first section at a first set of coordinate positions, wherein the first set of coordinate positions forms a first rectangular boundary around the first section, and wherein the identification of the first section is based on at least one special rule; identifying a second section based on at a second set of coordinate positions, wherein the second set of coordinate positions forms a second rectangular boundary around the second section, and wherein the identification of the second section is based on a proximity to the first section; merging the first and second sections to form one of the increasingly larger sections; and repeating the building of the zero or more directional links between the increasingly larger section formed by the merger of the first and second sections with the other sections included in the plurality of sections. 12. The computer program product of claim 11 wherein identification of the first section based on one of the special rules further comprises: identifying that the first section is an island section that is void of any directional links to other sections from the plurality of sections. | 0.919989 |
6,167,411 | 17 | 24 | 17. An apparatus in accordance with claim 16, wherein said receiving means comprises means for receiving at least one handwritten new character in the handwriting capture widget. | 17. An apparatus in accordance with claim 16, wherein said receiving means comprises means for receiving at least one handwritten new character in the handwriting capture widget. 24. An apparatus in accordance with claim 17, wherein said selecting means comprises means for overriding the sequentially ordered list of text entry widgets. | 0.926987 |
9,454,615 | 2 | 3 | 2. The method of claim 1 , wherein identifying at least one connection between at least two of the generated phrases further comprises: identifying the directly connected phrases; and filtering out the identified directly connected non-sentiment phrases to identify the hidden connections. | 2. The method of claim 1 , wherein identifying at least one connection between at least two of the generated phrases further comprises: identifying the directly connected phrases; and filtering out the identified directly connected non-sentiment phrases to identify the hidden connections. 3. The method of claim 2 , wherein filtering out the identified directly connected non-sentiment phrases to identify the hidden connections further comprises: analyzing the hidden connections to determine whether at least two hidden connections share a common non-sentiment phrase; and upon determining that at least two analyzed hidden connections share a common non-sentiment phrase, identifying a new hidden connection respective of the at least two analyzed hidden connections. | 0.788292 |
5,440,672 | 1 | 2 | 1. A method for automatically generating fuzzy reasoning rules which is performed by a controller apparatus, including the steps of: performing a fuzzy reasoning process based on rule parameters of membership functions constituting fuzzy reasoning rules representing relationships between input data and output data stored in a rule memory for storing rule parameters of membership functions constituting fuzzy reasoning rules and outputting results of said fuzzy reasoning process, each of said fuzzy reasoning rules being composed of antecedents and consequents; calculating a reasoning error and a change in the reasoning error to obtain a calculated reasoning error and a calculated change based on the results of said fuzzy reasoning process and said plurality of pairs of predetermined input and output data; adjusting said rule parameters of membership functions constituting said fuzzy reasoning rules stored in said rule memory, based on the results of said fuzzy reasoning process and a plurality of pairs of predetermined input and output data for said fuzzy reasoning process which are predetermined by a rule designer, when said calculated change is larger than a predetermined first threshold value; generating new rule parameters of membership functions constituting fuzzy reasoning rules and storing said new generated rule parameters of membership functions constituting said fuzzy reasoning rules in said rule memory, when said calculated change in the reasoning error is equal or smaller than said predetermined first threshold value; and alternately adjusting and generating rule parameters repeatedly until said calculated reasoning error is equal to or smaller than a predetermined second threshold value. | 1. A method for automatically generating fuzzy reasoning rules which is performed by a controller apparatus, including the steps of: performing a fuzzy reasoning process based on rule parameters of membership functions constituting fuzzy reasoning rules representing relationships between input data and output data stored in a rule memory for storing rule parameters of membership functions constituting fuzzy reasoning rules and outputting results of said fuzzy reasoning process, each of said fuzzy reasoning rules being composed of antecedents and consequents; calculating a reasoning error and a change in the reasoning error to obtain a calculated reasoning error and a calculated change based on the results of said fuzzy reasoning process and said plurality of pairs of predetermined input and output data; adjusting said rule parameters of membership functions constituting said fuzzy reasoning rules stored in said rule memory, based on the results of said fuzzy reasoning process and a plurality of pairs of predetermined input and output data for said fuzzy reasoning process which are predetermined by a rule designer, when said calculated change is larger than a predetermined first threshold value; generating new rule parameters of membership functions constituting fuzzy reasoning rules and storing said new generated rule parameters of membership functions constituting said fuzzy reasoning rules in said rule memory, when said calculated change in the reasoning error is equal or smaller than said predetermined first threshold value; and alternately adjusting and generating rule parameters repeatedly until said calculated reasoning error is equal to or smaller than a predetermined second threshold value. 2. The method as claimed in claim 1, wherein said newly generating rule parameters step includes the steps of: determining a region for generating fuzzy reasoning rules, said region being defined by said input data; generating membership functions of antecedents of fuzzy reasoning rules in said determined region, and storing rule parameters of said generated membership functions of the antecedents of the fuzzy reasoning rules in said rule memory; and generating membership functions of consequents of fuzzy reasoning rules based on the antecedents of the fuzzy reasoning rules stored in said rule memory, and storing rule parameters of said generated membership functions of the consequents of the fuzzy reasoning rules in said rule memory. | 0.668153 |
8,073,700 | 1 | 9 | 1. A method carried out by at least one computer, the method comprising acts of: receiving a request comprising speech data from a mobile device; querying a network service using query information obtained from the speech data, whereby search results are received from the network service; formatting the search results for presentation on a display of the mobile device; generating a voice grammar based at least in part on the search results; and sending the search results and the voice grammar generated from the search results to the mobile device. | 1. A method carried out by at least one computer, the method comprising acts of: receiving a request comprising speech data from a mobile device; querying a network service using query information obtained from the speech data, whereby search results are received from the network service; formatting the search results for presentation on a display of the mobile device; generating a voice grammar based at least in part on the search results; and sending the search results and the voice grammar generated from the search results to the mobile device. 9. The method of claim 1 , wherein the at least one computer comprises a proxy server. | 0.937591 |
9,747,510 | 17 | 20 | 17. The computer-implemented method of claim 16 , wherein the plurality of components include an orientation detection component, a language detection component, and a rotation component. | 17. The computer-implemented method of claim 16 , wherein the plurality of components include an orientation detection component, a language detection component, and a rotation component. 20. The computer-implemented method of claim 17 , wherein the rotation component is configured to re-render the display of the characters of the second language from the horizontal layout to the vertical layout. | 0.926275 |
9,258,373 | 20 | 25 | 20. A method for generating a geofeed based on one or more altitude parameters, the method being implemented in a computer that includes one or more processors programmed with one or more computer program modules that, when executed by the one or more processors, causes the computer to perform the method, the method comprising: obtaining, by the computer, content associated with the geofeed, the content aggregated from a plurality of content providers based on one or more geographically definable locations, the content being provided by the plurality of content providers based on respective requests formatted specifically for individual ones of the plurality of content providers, wherein the respective requests comprise the one or more geographically definable locations; identifying, by the computer, the one or more altitude parameters; determining, by the computer, one or more altitude attributes related to the content; filtering, by the computer, in or out the content based on the one or more altitude parameters and the one or more altitude attributes related to the content; and communicating, by the computer, the geofeed comprising the filtered content. | 20. A method for generating a geofeed based on one or more altitude parameters, the method being implemented in a computer that includes one or more processors programmed with one or more computer program modules that, when executed by the one or more processors, causes the computer to perform the method, the method comprising: obtaining, by the computer, content associated with the geofeed, the content aggregated from a plurality of content providers based on one or more geographically definable locations, the content being provided by the plurality of content providers based on respective requests formatted specifically for individual ones of the plurality of content providers, wherein the respective requests comprise the one or more geographically definable locations; identifying, by the computer, the one or more altitude parameters; determining, by the computer, one or more altitude attributes related to the content; filtering, by the computer, in or out the content based on the one or more altitude parameters and the one or more altitude attributes related to the content; and communicating, by the computer, the geofeed comprising the filtered content. 25. The method of claim 20 , wherein the one or more altitude attributes related to the content are determined by the computer. | 0.814869 |
9,436,927 | 11 | 14 | 11. A system for web-based multiuser collaboration, the system comprising: a processor; and an optical disk, magnetic storage device, or semiconductor storage device having executable instructions stored thereupon which, when executed by the processor, cause the processor to model a document on a server into semantic pieces as a plurality of cells for a construct of the document, identify at least one cell of interest of the plurality of cells to at least one user of a plurality of users, the at least one cell of interest comprising a portion of the document cached on the server, in response to identifying the at least one cell of interest, send the cached portion of the at least one cell of interest to a browser associated with the at least one user, associate the at least one cell of interest with the at least one user, store an association between the at least one cell of interest and the at least one user, obtain a first revision of interest to the at least one cell of interest, determine, based upon the association between the at least one cell of interest and the at least one user, that the first revision of interest is to be sent to the browser associated with the at least one user, and send a cached portion of the first revision of interest to the browser associated with the at least one user, whereby the cached portion of the first revision is configured to be displayed by the browser along with a first identifier indicating the association between the at least one cell of interest and the at least one user. | 11. A system for web-based multiuser collaboration, the system comprising: a processor; and an optical disk, magnetic storage device, or semiconductor storage device having executable instructions stored thereupon which, when executed by the processor, cause the processor to model a document on a server into semantic pieces as a plurality of cells for a construct of the document, identify at least one cell of interest of the plurality of cells to at least one user of a plurality of users, the at least one cell of interest comprising a portion of the document cached on the server, in response to identifying the at least one cell of interest, send the cached portion of the at least one cell of interest to a browser associated with the at least one user, associate the at least one cell of interest with the at least one user, store an association between the at least one cell of interest and the at least one user, obtain a first revision of interest to the at least one cell of interest, determine, based upon the association between the at least one cell of interest and the at least one user, that the first revision of interest is to be sent to the browser associated with the at least one user, and send a cached portion of the first revision of interest to the browser associated with the at least one user, whereby the cached portion of the first revision is configured to be displayed by the browser along with a first identifier indicating the association between the at least one cell of interest and the at least one user. 14. The system of claim 11 , wherein the optical disk, magnetic storage device, or semiconductor storage device contains further instructions which, when executed by the processor, further causes the processor to: receive a request for the at least one cell of interest; and redirect the request to the cache. | 0.697652 |
4,802,231 | 8 | 9 | 8. In an automated pattern recognition system in which the characteristics of known patterns are stored as a series of reference templates to be compared against the characteristics of incoming unknown pattern templates, a method of reducing matching errors comprising the steps of: (a) determining those incoming pattern templates which tend to be erroneously matched to reference templates; (b) creating independent error templates which correspond to the incoming pattern templates which tend to be erroneously matched; (c) comparing incoming pattern templates against the said reference templates and the said independent error templates; (d) identifying the unknown pattern as a match whenever its template is most closely matched to a reference template; and (e) discarding the unknown pattern as a non-match whenever its template is most closely matched to an independent error template. | 8. In an automated pattern recognition system in which the characteristics of known patterns are stored as a series of reference templates to be compared against the characteristics of incoming unknown pattern templates, a method of reducing matching errors comprising the steps of: (a) determining those incoming pattern templates which tend to be erroneously matched to reference templates; (b) creating independent error templates which correspond to the incoming pattern templates which tend to be erroneously matched; (c) comparing incoming pattern templates against the said reference templates and the said independent error templates; (d) identifying the unknown pattern as a match whenever its template is most closely matched to a reference template; and (e) discarding the unknown pattern as a non-match whenever its template is most closely matched to an independent error template. 9. The method of claim 8 further comprising the step of creating linked error templates which are linked to specified reference templates. | 0.503597 |
8,892,589 | 17 | 18 | 17. The system of claim 15 , wherein the instructions further cause the one or more computers to perform operations comprising: identifying, from a data store, a plurality of previous search queries that were received from the particular user device; identifying, from among the previous search queries, a first search query that is related to a first topic; determining that a second search query, from among the previous search queries, was received after the first search query and is related to a second topic that differs from the first topic; and defining, as a beginning of a search session for the second search query, a time after receipt of the first search query and up to a time at which the second search query was received. | 17. The system of claim 15 , wherein the instructions further cause the one or more computers to perform operations comprising: identifying, from a data store, a plurality of previous search queries that were received from the particular user device; identifying, from among the previous search queries, a first search query that is related to a first topic; determining that a second search query, from among the previous search queries, was received after the first search query and is related to a second topic that differs from the first topic; and defining, as a beginning of a search session for the second search query, a time after receipt of the first search query and up to a time at which the second search query was received. 18. The system of claim 17 , wherein determining that at least the first threshold number of previous search queries are search queries for a same topic comprises: determining that at least the first threshold number of previous search queries are search queries for the second topic; and determining that the first threshold number of previous search queries were received between the beginning of the search session and receipt of the current search query. | 0.841413 |
7,797,643 | 13 | 21 | 13. In a computer system including a display screen comprising a result display area of a graphical user interface, a computer-implemented method of shortening a plurality of text display blocks displayed in the result display area of the graphical user interface, the method comprising: in response to movement of a single control displayed in a control area of the user interface distinguished from the result display area, determining a longest text display block of the displayed plurality of text display blocks, each text display block has a size individually determined based on the amount of data to be displayed in the block; shortening by one increment the size of the longest text display block of the displayed plurality of text display blocks, wherein at least two of the text display blocks have different amounts of data and are displayed having different sizes, and wherein the shortening is dynamic, visible and concurrent with the movement of the control; determining whether the displayed plurality of text display blocks are of equal size; and in response to a determination that the displayed plurality of text display blocks are of equal size, shortening the sizes of the displayed plurality of text display blocks as a group until a minimum size is reached, wherein the shortening is dynamic, visible and concurrent with the movement of the control. | 13. In a computer system including a display screen comprising a result display area of a graphical user interface, a computer-implemented method of shortening a plurality of text display blocks displayed in the result display area of the graphical user interface, the method comprising: in response to movement of a single control displayed in a control area of the user interface distinguished from the result display area, determining a longest text display block of the displayed plurality of text display blocks, each text display block has a size individually determined based on the amount of data to be displayed in the block; shortening by one increment the size of the longest text display block of the displayed plurality of text display blocks, wherein at least two of the text display blocks have different amounts of data and are displayed having different sizes, and wherein the shortening is dynamic, visible and concurrent with the movement of the control; determining whether the displayed plurality of text display blocks are of equal size; and in response to a determination that the displayed plurality of text display blocks are of equal size, shortening the sizes of the displayed plurality of text display blocks as a group until a minimum size is reached, wherein the shortening is dynamic, visible and concurrent with the movement of the control. 21. The method of claim 13 , further comprising: maintaining an aspect of each of the displayed plurality of text display blocks throughout the shortening of the sizes of the displayed plurality of text display blocks. | 0.621528 |
9,792,897 | 23 | 24 | 23. The method of claim 19 , further comprising providing the plurality of detection indicator values to a hidden layer of the ensemble phoneme recognition neural network. | 23. The method of claim 19 , further comprising providing the plurality of detection indicator values to a hidden layer of the ensemble phoneme recognition neural network. 24. The method of claim 23 , further comprising providing the first feature stream to an input layer of the ensemble phoneme recognition neural network. | 0.961597 |
9,235,846 | 1 | 2 | 1. A method in a host organization, the method comprising: receiving a tabular dataset from a user as input, the tabular dataset having data values organized as columns and rows; identifying a plurality of null values within the tabular dataset, the null values being dispersed across multiple rows and multiple columns of the tabular dataset; generating indices from the tabular dataset of columns and rows, the indices representing probabilistic relationships between the rows and the columns of the tabular dataset; displaying the tabular dataset as output to the user, the displayed output including the data values depicted as known values and the null values depicted as unknown values; receiving input from the user to populate at least a portion of the unknown values within the displayed tabular dataset with predicted values; querying the indices for the predicted values; receiving a confidence indicator for every one of the plurality of null values within the tabular dataset responsive to querying the indices for the predicted values, the confidence indicator based on a comparison of known results corresponding to known and non-null values within the dataset with the predicted values; and displaying the predicted values as updated output to the user, wherein displaying the predicted values as updated output to the user comprises displaying selected ones of the predicted values that correspond to the confidence indicator being in excess of a default minimum confidence threshold or a user specified minimum confidence threshold when present. | 1. A method in a host organization, the method comprising: receiving a tabular dataset from a user as input, the tabular dataset having data values organized as columns and rows; identifying a plurality of null values within the tabular dataset, the null values being dispersed across multiple rows and multiple columns of the tabular dataset; generating indices from the tabular dataset of columns and rows, the indices representing probabilistic relationships between the rows and the columns of the tabular dataset; displaying the tabular dataset as output to the user, the displayed output including the data values depicted as known values and the null values depicted as unknown values; receiving input from the user to populate at least a portion of the unknown values within the displayed tabular dataset with predicted values; querying the indices for the predicted values; receiving a confidence indicator for every one of the plurality of null values within the tabular dataset responsive to querying the indices for the predicted values, the confidence indicator based on a comparison of known results corresponding to known and non-null values within the dataset with the predicted values; and displaying the predicted values as updated output to the user, wherein displaying the predicted values as updated output to the user comprises displaying selected ones of the predicted values that correspond to the confidence indicator being in excess of a default minimum confidence threshold or a user specified minimum confidence threshold when present. 2. The method of claim 1 : wherein generating indices from the tabular dataset of columns and rows further comprises storing the indices within a database of the host organization; and wherein querying the indices for the predicted values comprises querying the database for the predicted values. | 0.857692 |
8,239,366 | 1 | 12 | 1. A method, implemented at least in part on a microprocessor, of performing a search for content on the Internet, the method comprising: receiving voice input provided from a user; and generating at least one text search query for a plurality of Internet-accessible search engines that search for content on the Internet, wherein the at least one text search query is generated, at least in part, by performing speech recognition on the voice input; wherein the at least one text search query comprises at least two text search queries; wherein the act of generating further comprises: generating a first of the at least two text search queries, at least in part by performing speech recognition on the voice input using a first language model associated with a first of the plurality of search engines; and generating a second of the at least two text search queries, at least in part by performing speech recognition on the voice input using a second language model, different from the first language model, associated with a second of the plurality of search engines; wherein the first language model is one that was trained on content indexed by the first of the plurality of search engines; wherein the first of the plurality of search engines is a site-specific search engine; and wherein the second of the plurality of search engines is a general search engine. | 1. A method, implemented at least in part on a microprocessor, of performing a search for content on the Internet, the method comprising: receiving voice input provided from a user; and generating at least one text search query for a plurality of Internet-accessible search engines that search for content on the Internet, wherein the at least one text search query is generated, at least in part, by performing speech recognition on the voice input; wherein the at least one text search query comprises at least two text search queries; wherein the act of generating further comprises: generating a first of the at least two text search queries, at least in part by performing speech recognition on the voice input using a first language model associated with a first of the plurality of search engines; and generating a second of the at least two text search queries, at least in part by performing speech recognition on the voice input using a second language model, different from the first language model, associated with a second of the plurality of search engines; wherein the first language model is one that was trained on content indexed by the first of the plurality of search engines; wherein the first of the plurality of search engines is a site-specific search engine; and wherein the second of the plurality of search engines is a general search engine. 12. The method of claim 1 , wherein generating the first of the at least two search queries further comprises performing speech recognition on the voice input using a language model different from the first language model. | 0.894487 |
10,133,736 | 8 | 9 | 8. A computer program product to provide a contextual analogy response, the computer program product comprising a computer readable storage device having program code embodied therewith, the program code executable by a processing unit to: denote an analogy phrase within segments of a communication; parse a set of the segments prior to the denoted analogy phrase; detect an anaphora within the analogy phrase, including the processing unit to: search the set of segments for an entity represented by the detected anaphora; and connect the entity to the detected anaphora; create a sentence structure including an action term from the analogy and a replacement of the anaphora with the entity; populate the created sentence structure with the entity connected with the anaphora; resolve an explanation of the analogy with respect to the set of sentences; retrieve a contextual response correlating to a sentiment of the analogy phrase; and output the response including the retrieved contextual response and the populated sentence structure, wherein the contextual response resolves an explanation of the analogy phrase. | 8. A computer program product to provide a contextual analogy response, the computer program product comprising a computer readable storage device having program code embodied therewith, the program code executable by a processing unit to: denote an analogy phrase within segments of a communication; parse a set of the segments prior to the denoted analogy phrase; detect an anaphora within the analogy phrase, including the processing unit to: search the set of segments for an entity represented by the detected anaphora; and connect the entity to the detected anaphora; create a sentence structure including an action term from the analogy and a replacement of the anaphora with the entity; populate the created sentence structure with the entity connected with the anaphora; resolve an explanation of the analogy with respect to the set of sentences; retrieve a contextual response correlating to a sentiment of the analogy phrase; and output the response including the retrieved contextual response and the populated sentence structure, wherein the contextual response resolves an explanation of the analogy phrase. 9. The computer program product of claim 8 , wherein the sentence parsing further comprises program code executable by a processing unit to: identify grammatical sub-components of the segments; identify grammatical sub-components of the analogy phrase; and match at least one segment grammatical sob-component corresponding to at least one analogy phrase grammatical sub-component. | 0.618236 |
10,056,077 | 1 | 8 | 1. A method of entering text into a music system using a processor, comprising: recording speech presented by a user using a resident capture facility; providing the speech as a recording to a speech recognition facility; selecting at least one statistical language model, including a large vocabulary statistical language model, from a set of language models based at least in part on contextual information relating to the recording, wherein the at least one statistical language model selected includes a general language model for artists, a general language model for song titles, and a general language model for music types; determining that the at least one statistical language model selected provides insufficient recognition output and requires an additional recognition pass of the recording; conducting the additional recognition pass of the recording; selecting at least one other statistical language model based at least in part on the additional recognition pass of the recording and client state information of the recording; generating results utilizing the speech of the recording recognized by the speech recognition facility; and using the results in the music system, wherein the music system provides information relating to a music application to the speech recognition facility, wherein generating the results is based at least in part on the information, wherein the information relating to the music application includes contextual information within the music application, and wherein the contextual information includes at least one of a usage history of the music application and information from at least one of a favorites list and playlists of the user. | 1. A method of entering text into a music system using a processor, comprising: recording speech presented by a user using a resident capture facility; providing the speech as a recording to a speech recognition facility; selecting at least one statistical language model, including a large vocabulary statistical language model, from a set of language models based at least in part on contextual information relating to the recording, wherein the at least one statistical language model selected includes a general language model for artists, a general language model for song titles, and a general language model for music types; determining that the at least one statistical language model selected provides insufficient recognition output and requires an additional recognition pass of the recording; conducting the additional recognition pass of the recording; selecting at least one other statistical language model based at least in part on the additional recognition pass of the recording and client state information of the recording; generating results utilizing the speech of the recording recognized by the speech recognition facility; and using the results in the music system, wherein the music system provides information relating to a music application to the speech recognition facility, wherein generating the results is based at least in part on the information, wherein the information relating to the music application includes contextual information within the music application, and wherein the contextual information includes at least one of a usage history of the music application and information from at least one of a favorites list and playlists of the user. 8. The method of claim 1 , further comprising selecting a different statistical language model based on the results generated. | 0.807927 |
10,133,729 | 1 | 4 | 1. A system comprising: one or more processors; and a memory storing instructions which, when executed by one or more processors, cause the one or more processors to perform operation comprising: receiving a query comprising one or more words; computing a vector for individual words of the one or more words; determining an initial hidden vector corresponding to a semantic representation of the query; mapping, using mapping software, the one or more words of the query based on the initial hidden vector, wherein the mapping is rendered sequentially; matching the semantic representation of the query, represented in the initial hidden vector, to a semantic representation corresponding to one or more responses; providing, in a user interface, the one or more responses based at least in part on the matching, the user interface indicating a semantic similarity between the query and the one or more responses; receiving click-through data associated with the one or more responses, the click-through data identifying a response from among the one or more responses as a positive match; and training the mapping software based at least in part on the click-through data. | 1. A system comprising: one or more processors; and a memory storing instructions which, when executed by one or more processors, cause the one or more processors to perform operation comprising: receiving a query comprising one or more words; computing a vector for individual words of the one or more words; determining an initial hidden vector corresponding to a semantic representation of the query; mapping, using mapping software, the one or more words of the query based on the initial hidden vector, wherein the mapping is rendered sequentially; matching the semantic representation of the query, represented in the initial hidden vector, to a semantic representation corresponding to one or more responses; providing, in a user interface, the one or more responses based at least in part on the matching, the user interface indicating a semantic similarity between the query and the one or more responses; receiving click-through data associated with the one or more responses, the click-through data identifying a response from among the one or more responses as a positive match; and training the mapping software based at least in part on the click-through data. 4. The system of claim 1 , the operations further comprising: sending the one or more responses to a user associated with the query. | 0.906117 |
9,014,511 | 9 | 12 | 9. A computer program product comprising a computer usable medium having control logic stored therein for causing a computer to enhance user queries, said control logic comprising: a first computer readable program code that enables the computer to receive a user query and identify one or more trigger words in the user query; a second computer readable program code that enables the computer to select one or more corresponding tags from a landmark database corresponding to the one or more trigger words; a third computer readable program code that enables the computer to supplement the user query with the one or more corresponding tags to generate a supplemented user query; a fourth computer readable program code that enables the computer to retrieve landmarks based on the supplemented user query; and a fifth computer readable program code that enables the computer to generate a user interface including the one or more retrieved landmarks and display one or more summary lists of visual clusters for the retrieved landmarks on the user interface, wherein each summary list corresponds to one of the retrieved landmarks, and to display popularity information on the one or more summary lists. | 9. A computer program product comprising a computer usable medium having control logic stored therein for causing a computer to enhance user queries, said control logic comprising: a first computer readable program code that enables the computer to receive a user query and identify one or more trigger words in the user query; a second computer readable program code that enables the computer to select one or more corresponding tags from a landmark database corresponding to the one or more trigger words; a third computer readable program code that enables the computer to supplement the user query with the one or more corresponding tags to generate a supplemented user query; a fourth computer readable program code that enables the computer to retrieve landmarks based on the supplemented user query; and a fifth computer readable program code that enables the computer to generate a user interface including the one or more retrieved landmarks and display one or more summary lists of visual clusters for the retrieved landmarks on the user interface, wherein each summary list corresponds to one of the retrieved landmarks, and to display popularity information on the one or more summary lists. 12. The computer program product of claim 9 , wherein each summary list includes descriptive information about the visual clusters. | 0.657068 |
7,809,602 | 1 | 2 | 1. A computer-implemented method for measuring and reporting business intelligence based on comments collected from web page users using software associated with accessed web pages, comprising: using a computer system, accessing a plurality of user comments collected from users of one or more web pages using feedback collection software that provides users who access a particular web page a viewable element through which to provide their comments regarding one or more aspects of a business associated with the particular web page; using a computer system to assign a rating selected from a plurality of available ratings to each collected user comment based on a subjective assessment of the collected user comment; using a computer system, associating each of the plurality of collected user comments with one or more of a plurality of predefined business-related categories; and using a computer system, generating a report identifying, for each of the plurality of predefined business-related categories, one or more quantitative values derived from the collected user comments associated with that business-related category; wherein a quantitative value identified in the report for a particular predefined business-related category comprises a quantity of collected user comments assigned to a particular rating; wherein the report comprises a bar graph comprising a plurality of color-coded bars, each color-coded bar representing a corresponding one of the plurality of predefined business-related categories and each color representing a corresponding one of the plurality of available ratings; and wherein the bar graph comprises a first half and a second half, the first half being separated from the second half by an axis of the graph. | 1. A computer-implemented method for measuring and reporting business intelligence based on comments collected from web page users using software associated with accessed web pages, comprising: using a computer system, accessing a plurality of user comments collected from users of one or more web pages using feedback collection software that provides users who access a particular web page a viewable element through which to provide their comments regarding one or more aspects of a business associated with the particular web page; using a computer system to assign a rating selected from a plurality of available ratings to each collected user comment based on a subjective assessment of the collected user comment; using a computer system, associating each of the plurality of collected user comments with one or more of a plurality of predefined business-related categories; and using a computer system, generating a report identifying, for each of the plurality of predefined business-related categories, one or more quantitative values derived from the collected user comments associated with that business-related category; wherein a quantitative value identified in the report for a particular predefined business-related category comprises a quantity of collected user comments assigned to a particular rating; wherein the report comprises a bar graph comprising a plurality of color-coded bars, each color-coded bar representing a corresponding one of the plurality of predefined business-related categories and each color representing a corresponding one of the plurality of available ratings; and wherein the bar graph comprises a first half and a second half, the first half being separated from the second half by an axis of the graph. 2. The method of claim 1 , wherein the first half comprises a mirror-image of the second half. | 0.792952 |
8,661,041 | 11 | 12 | 11. The semantic-based searching method of claim 8 , wherein in the associative search structure, an information item to be a final search object is previously stored in each application that receives the input search query. | 11. The semantic-based searching method of claim 8 , wherein in the associative search structure, an information item to be a final search object is previously stored in each application that receives the input search query. 12. The semantic-based searching method of claim 11 , wherein the generating of the search result for the final search object includes determining a first information item, a second information item, a search order, and a search means from the previously defined associative search structure and generating the search result for the search query based on the determination result in response to the input search query being received, wherein the search query is applied to the first information item and the second information item participates in a search between the first information item and the final search object. | 0.725177 |
7,921,360 | 10 | 11 | 10. The computer program product of claim 7 further comprising: code for setting a restriction feature flag in said modified document to activate restricted editing. | 10. The computer program product of claim 7 further comprising: code for setting a restriction feature flag in said modified document to activate restricted editing. 11. The computer program product of claim 10 wherein said code for prohibiting is activated in response to said set restriction feature flag. | 0.931287 |
9,021,007 | 20 | 22 | 20. An apparatus for enabling interoperability between a plurality of participants in a network, the apparatus comprising: one or more memories; and one or more processors coupled to the one or more memories, the one or more processors configured: to determine a value associated with a value metric defined for at least a portion of the network; to determine two or more alternative information flows between two or more of the plurality of participants in the network based at least in part on one or more semantic models corresponding to the plurality of participants and on the value associated with the value metric, wherein the one or more semantic models define inputs, outputs, and functionality for each of the plurality of participants and define at least a portion of information produced or consumed by the plurality of participants; and to optimize an overall value of the network by selecting combinations of said alternative information flows for at least one portion of the network in order to satisfy consumers of information. | 20. An apparatus for enabling interoperability between a plurality of participants in a network, the apparatus comprising: one or more memories; and one or more processors coupled to the one or more memories, the one or more processors configured: to determine a value associated with a value metric defined for at least a portion of the network; to determine two or more alternative information flows between two or more of the plurality of participants in the network based at least in part on one or more semantic models corresponding to the plurality of participants and on the value associated with the value metric, wherein the one or more semantic models define inputs, outputs, and functionality for each of the plurality of participants and define at least a portion of information produced or consumed by the plurality of participants; and to optimize an overall value of the network by selecting combinations of said alternative information flows for at least one portion of the network in order to satisfy consumers of information. 22. The apparatus of claim 20 , wherein the one or more processors are further configured to perform the determining steps multiple times in order to modify the value associated with the value metric. | 0.851852 |
8,442,970 | 1 | 2 | 1. A method for constructing a search query, comprising: receiving a plurality of characters corresponding to characters entered into a query box; matching the plurality of characters to a category; constructing a query based on the matching of the plurality of characters, the constructed query including the matched category; receiving a selection of the constructed query; providing a plurality of facets corresponding to the matched category; adding a facet to the constructed query to form an expanded constructed query, the facet being added in response to receiving a selection of the facet from the provided plurality of facets; providing, in response to receiving the selection of the facet from the provided plurality of facets, at least one facet value corresponding to the added facet; and adding a facet value to the expanded constructed query in response to receiving a selection of the facet value from the provided at least one facet value, wherein the selection of the facet is received prior to receiving a selection of a facet value corresponding to the facet. | 1. A method for constructing a search query, comprising: receiving a plurality of characters corresponding to characters entered into a query box; matching the plurality of characters to a category; constructing a query based on the matching of the plurality of characters, the constructed query including the matched category; receiving a selection of the constructed query; providing a plurality of facets corresponding to the matched category; adding a facet to the constructed query to form an expanded constructed query, the facet being added in response to receiving a selection of the facet from the provided plurality of facets; providing, in response to receiving the selection of the facet from the provided plurality of facets, at least one facet value corresponding to the added facet; and adding a facet value to the expanded constructed query in response to receiving a selection of the facet value from the provided at least one facet value, wherein the selection of the facet is received prior to receiving a selection of a facet value corresponding to the facet. 2. The method of claim 1 , wherein matching the plurality of characters to a category comprises matching the plurality of characters to a facet or facet value associated with the category. | 0.83959 |
8,793,246 | 6 | 7 | 6. A computer program product tangibly stored on a computer readable storage device, the computer program product comprising instructions for causing a computer system to perform operations comprising: receiving, from a client device, information indicative of a keyword and information indicative of a user specified network domain of interest; receiving, from search engine systems, search results for the keyword; determining, a first search engine ranking score of a search result returned from a first one of the search engine systems and associated with the user specified network domain of interest; determining a second search engine ranking score of a search result returned from a second, different search engine system and associated with the user specified network domain of interest; generating information for: a first visual representation of information indicative of the search result from the first one of the search engine systems that is associated with the user specified network domain of interest; and a second visual representation of information indicative of the search result from the second one of the search engine systems that is associated with the user specified network domain of interest; selecting, from the received search results, a predefined number of search results for the keyword with increased search engine ranking scores relative to other search engine ranking scores for other retrieved search results for the keyword; and transmitting to the client device information indicative of the selected predefined number of search results, the first visual representation and the second visual representation. | 6. A computer program product tangibly stored on a computer readable storage device, the computer program product comprising instructions for causing a computer system to perform operations comprising: receiving, from a client device, information indicative of a keyword and information indicative of a user specified network domain of interest; receiving, from search engine systems, search results for the keyword; determining, a first search engine ranking score of a search result returned from a first one of the search engine systems and associated with the user specified network domain of interest; determining a second search engine ranking score of a search result returned from a second, different search engine system and associated with the user specified network domain of interest; generating information for: a first visual representation of information indicative of the search result from the first one of the search engine systems that is associated with the user specified network domain of interest; and a second visual representation of information indicative of the search result from the second one of the search engine systems that is associated with the user specified network domain of interest; selecting, from the received search results, a predefined number of search results for the keyword with increased search engine ranking scores relative to other search engine ranking scores for other retrieved search results for the keyword; and transmitting to the client device information indicative of the selected predefined number of search results, the first visual representation and the second visual representation. 7. The computer program product of claim 6 , wherein the operations further comprise: transmitting, to the client device, information indicative of at least a portion of the search results received. | 0.82931 |
8,538,184 | 1 | 8 | 1. In a document analysis system including a server, a method of enhancing electronic documents to improve automatic recognition and classification of the electronic documents, the method comprising: receiving, by the server, jobs containing job documents from a plurality of users, wherein each received job document is a binarized, one-bit-per-document-pixel image version of an original grayscale or color image source document; filtering, by the server, each page of the received binarized document to infer binarized background artifacts which result from the binarization of the original grayscale or color image source document and reside in the vicinity of binarized text and binarized image features in the page; distinguishing, by the server, the binarized text and binarized image features from the binarized background artifacts; extracting, by the server, the binarized text and binarized image features from the received binarized document; automatically recognizing and classifying, by the server, the received binarized document into a document category by using the extracted binarized text and binarized image features; organizing, by the server, each received job according to the document category of the corresponding job document; and removing, by the server, the binarized background artifacts, wherein the removal of the binarized background artifacts is performed after the binarized document image is inverted to white-on-black. | 1. In a document analysis system including a server, a method of enhancing electronic documents to improve automatic recognition and classification of the electronic documents, the method comprising: receiving, by the server, jobs containing job documents from a plurality of users, wherein each received job document is a binarized, one-bit-per-document-pixel image version of an original grayscale or color image source document; filtering, by the server, each page of the received binarized document to infer binarized background artifacts which result from the binarization of the original grayscale or color image source document and reside in the vicinity of binarized text and binarized image features in the page; distinguishing, by the server, the binarized text and binarized image features from the binarized background artifacts; extracting, by the server, the binarized text and binarized image features from the received binarized document; automatically recognizing and classifying, by the server, the received binarized document into a document category by using the extracted binarized text and binarized image features; organizing, by the server, each received job according to the document category of the corresponding job document; and removing, by the server, the binarized background artifacts, wherein the removal of the binarized background artifacts is performed after the binarized document image is inverted to white-on-black. 8. The method of claim 1 further comprising enabling a human trainer to assist in classifying documents to be used to train the automatic recognition and classification of subsequently-received documents. | 0.593625 |
9,549,085 | 1 | 9 | 1. A computer system for proactively creating an image product, comprising: a computer memory configured to store a library of specification terms for image products; and a computer processing system configured to receive a command comprising a text from a user, conduct lexical analysis of the text in the command, tokenize the command into a plurality of tokens, and match one or more of the tokens to the specification terms in the library to determine specification parameters for an image product, wherein the computer processing system is configured to automatically identify images based on the specification parameters by the computer system, and automatically create a design for the image product that incorporates at least some of the images identified based on the specification parameters. | 1. A computer system for proactively creating an image product, comprising: a computer memory configured to store a library of specification terms for image products; and a computer processing system configured to receive a command comprising a text from a user, conduct lexical analysis of the text in the command, tokenize the command into a plurality of tokens, and match one or more of the tokens to the specification terms in the library to determine specification parameters for an image product, wherein the computer processing system is configured to automatically identify images based on the specification parameters by the computer system, and automatically create a design for the image product that incorporates at least some of the images identified based on the specification parameters. 9. The computer system of claim 1 , further comprising: a printer configured to produce a physical manifestation of the image product based on the design for the image product. | 0.797235 |
9,767,148 | 1 | 5 | 1. A method, implemented at least partly by a device, the method comprising: configuring the database system to operate at a limited capacity below its full capacity for execution of database queries of a database, wherein the database system includes one or more processors operable to process data stored in the database in a database environment in order to process the database queries; learning about optimization of execution of one or more selected database queries that do not meet at least one performance criteria associated with a target performance for processing the selected database queries with the limited capacity in the database environment, by using the excess capacity of the database system configured to operate with the limited capacity for the execution of database queries of the database; allowing at least one portion of the excess capacity available to the database system to be used to perform one or more learning activities associated with learning about optimization of execution of one or more selected database queries in the database environment that do not meet at least one performance criteria; and not allowing the at least one portion of the excess capacity available to the database system to be used to perform other activities not associated with the learning about optimization of execution of the database queries in the database environment. | 1. A method, implemented at least partly by a device, the method comprising: configuring the database system to operate at a limited capacity below its full capacity for execution of database queries of a database, wherein the database system includes one or more processors operable to process data stored in the database in a database environment in order to process the database queries; learning about optimization of execution of one or more selected database queries that do not meet at least one performance criteria associated with a target performance for processing the selected database queries with the limited capacity in the database environment, by using the excess capacity of the database system configured to operate with the limited capacity for the execution of database queries of the database; allowing at least one portion of the excess capacity available to the database system to be used to perform one or more learning activities associated with learning about optimization of execution of one or more selected database queries in the database environment that do not meet at least one performance criteria; and not allowing the at least one portion of the excess capacity available to the database system to be used to perform other activities not associated with the learning about optimization of execution of the database queries in the database environment. 5. The method of claim 1 , wherein the one or more learning operations include one or more operations for calculating one or more costs associated with one or more execution plans that are not currently identified as optimal execution plans for execution of one or more database queries of the database. | 0.658784 |
9,619,250 | 10 | 11 | 10. The system of claim 9 , further comprising a template management module that includes a library of templates effects selectable by an author for use in authoring an electronic book. | 10. The system of claim 9 , further comprising a template management module that includes a library of templates effects selectable by an author for use in authoring an electronic book. 11. The system of claim 10 , wherein the relational database tracks the relation of display objects such that the relational display of the same is selectably preserved during authoring of an electronic book. | 0.955801 |
7,992,131 | 40 | 53 | 40. A computer-readable memory comprising: software to cause a computer to receive an invocation of a first macro and a variable as an argument for the first macro; software to cause said computer to automatically identify a second macro to be invoked to perform, on said variable, an operation identified by the first macro; wherein the first macro and the second macro have different names; wherein the second macro is defined within said computer to comprise first assembler instructions for use with at least variables of an element type identical to a corresponding type of the variable; software to cause said computer to automatically expand the second macro using at least the first assembler instructions, to generate second assembler instructions in an assembly language; and software to cause said computer to use an assembler for said assembly language to generate object code, based at least on the second assembler instructions; wherein the second assembler instructions comprise at least one opcode which depends at least on said corresponding type of the variable. | 40. A computer-readable memory comprising: software to cause a computer to receive an invocation of a first macro and a variable as an argument for the first macro; software to cause said computer to automatically identify a second macro to be invoked to perform, on said variable, an operation identified by the first macro; wherein the first macro and the second macro have different names; wherein the second macro is defined within said computer to comprise first assembler instructions for use with at least variables of an element type identical to a corresponding type of the variable; software to cause said computer to automatically expand the second macro using at least the first assembler instructions, to generate second assembler instructions in an assembly language; and software to cause said computer to use an assembler for said assembly language to generate object code, based at least on the second assembler instructions; wherein the second assembler instructions comprise at least one opcode which depends at least on said corresponding type of the variable. 53. The computer-readable memory of claim 40 further comprising: software to cause said computer to receive and process a statement comprising an invocation of another macro to instantiate said variable using said corresponding type while identifying at least the variable's name, and a resource address to which the variable is bound. | 0.708696 |
9,830,912 | 9 | 17 | 9. A computing device configured to provide a multimodal interface for entering input, the computing device comprising: a hardware input mechanism; a hardware audio unit; a computer storage medium storing computer-readable components comprising computer-readable instructions: a processor configured to execute the computer-readable instructions, the computer-readable components comprising: a key-input module configured to collect one or more key inputs entered by a user using the hardware input mechanism; an audio-input module configured to collect, in parallel with the key inputs, one or more speech samples spoken by the user using the hardware audio unit; a multimodal module that dynamically reduces a vocabulary as key inputs are entered, but waits for performing speech recognition until an end of utterance indicator is entered, the vocabulary is dynamically reduced based on the key inputs and on a classification type associated with the key inputs, wherein one classification type includes the end of word indicator that is not a letter, and, upon receiving the end of word indicator, obtains and stores the key inputs and an utterance detected segment from the one or more speech samples, wherein the utterance detected segment comprises speech samples spoken by the user corresponding to the word, and performs speech recognition when the end of word indicator is received on the utterance detected segment using a current state of the dynamically reduced vocabulary. | 9. A computing device configured to provide a multimodal interface for entering input, the computing device comprising: a hardware input mechanism; a hardware audio unit; a computer storage medium storing computer-readable components comprising computer-readable instructions: a processor configured to execute the computer-readable instructions, the computer-readable components comprising: a key-input module configured to collect one or more key inputs entered by a user using the hardware input mechanism; an audio-input module configured to collect, in parallel with the key inputs, one or more speech samples spoken by the user using the hardware audio unit; a multimodal module that dynamically reduces a vocabulary as key inputs are entered, but waits for performing speech recognition until an end of utterance indicator is entered, the vocabulary is dynamically reduced based on the key inputs and on a classification type associated with the key inputs, wherein one classification type includes the end of word indicator that is not a letter, and, upon receiving the end of word indicator, obtains and stores the key inputs and an utterance detected segment from the one or more speech samples, wherein the utterance detected segment comprises speech samples spoken by the user corresponding to the word, and performs speech recognition when the end of word indicator is received on the utterance detected segment using a current state of the dynamically reduced vocabulary. 17. The computing device of claim 9 , wherein the multimodal module further identifies a best choice along with a plurality of alternative best choices. | 0.869863 |
8,150,700 | 10 | 11 | 10. A method of controlling a mobile terminal, the method comprising: receiving an input to activate a voice recognition function on the mobile terminal; activating the voice recognition function upon receiving the input to activate the voice recognition function; determining a meaning of an input voice instruction based on at least one prior operation performed on the mobile terminal and a language included in the voice instruction; determining a number of menus that match the meaning of the input voice instruction with a probability greater than a predetermined threshold; and executing a single menu if there is the single menu that matches the meaning of the input voice instruction with the probability greater than the predetermined threshold, or displaying the number of menus on the display unit if the number of menus is greater than one. | 10. A method of controlling a mobile terminal, the method comprising: receiving an input to activate a voice recognition function on the mobile terminal; activating the voice recognition function upon receiving the input to activate the voice recognition function; determining a meaning of an input voice instruction based on at least one prior operation performed on the mobile terminal and a language included in the voice instruction; determining a number of menus that match the meaning of the input voice instruction with a probability greater than a predetermined threshold; and executing a single menu if there is the single menu that matches the meaning of the input voice instruction with the probability greater than the predetermined threshold, or displaying the number of menus on the display unit if the number of menus is greater than one. 11. The mobile terminal of claim 10 , wherein the predetermined threshold is set by a manufacturer of the terminal or by a user of the terminal. | 0.908513 |
9,646,614 | 36 | 41 | 36. A system for speaker identification, comprising: one or more processors; memory; and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the one or more programs including instructions for: receiving a spoken utterance; generating a first phoneme-independent representation based on the spoken utterance; decomposing the first phoneme-independent representation into at least one content-independent characteristic unit; comparing the at least one content-independent characteristic unit to at least one content-independent recognition distribution value associated with a registered user of the device, the at least one content-independent recognition distribution value previously generated by: generating a second phoneme-independent representation based on speech from the registered user; and decomposing the second phoneme-independent representation into a content-independent recognition unit, the at least one content-independent recognition distribution value based on the content-independent recognition unit; and determining that the spoken utterance is spoken by the registered user if the at least one content-independent characteristic unit is within a threshold limit of the at least one content-independent recognition distribution value. | 36. A system for speaker identification, comprising: one or more processors; memory; and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the one or more programs including instructions for: receiving a spoken utterance; generating a first phoneme-independent representation based on the spoken utterance; decomposing the first phoneme-independent representation into at least one content-independent characteristic unit; comparing the at least one content-independent characteristic unit to at least one content-independent recognition distribution value associated with a registered user of the device, the at least one content-independent recognition distribution value previously generated by: generating a second phoneme-independent representation based on speech from the registered user; and decomposing the second phoneme-independent representation into a content-independent recognition unit, the at least one content-independent recognition distribution value based on the content-independent recognition unit; and determining that the spoken utterance is spoken by the registered user if the at least one content-independent characteristic unit is within a threshold limit of the at least one content-independent recognition distribution value. 41. The system of claim 36 , further comprising instructions for causing the one or more processor to: compute the at least one content-independent recognition distribution value from the at least one content-independent recognition unit. | 0.777985 |
10,089,388 | 17 | 18 | 17. A system for obtaining search results in a search client, comprising: a computing device; a gesture-enabled input device in communication with the computing device; and a search client executable by the computing device, wherein the search client, when executed by the computing device, is configured to cause the computing device to at least: display a plurality of user interface elements on the gesture-enabled input device; obtain a search term from a user in response to the user interacting with at least one of the user interface elements; transmit the search term to a search engine in response to the gesture-enabled input device detecting a first gesture; obtain a plurality of search results from the search engine, each one of the plurality of search results being based on a role of the user within an enterprise, the role determined by at least one of a job title or calendar data; and generate a rendering of the search results using a document structure and a document layout provided by the search engine, wherein the rendering of the search results comprises contextual content for the search term. | 17. A system for obtaining search results in a search client, comprising: a computing device; a gesture-enabled input device in communication with the computing device; and a search client executable by the computing device, wherein the search client, when executed by the computing device, is configured to cause the computing device to at least: display a plurality of user interface elements on the gesture-enabled input device; obtain a search term from a user in response to the user interacting with at least one of the user interface elements; transmit the search term to a search engine in response to the gesture-enabled input device detecting a first gesture; obtain a plurality of search results from the search engine, each one of the plurality of search results being based on a role of the user within an enterprise, the role determined by at least one of a job title or calendar data; and generate a rendering of the search results using a document structure and a document layout provided by the search engine, wherein the rendering of the search results comprises contextual content for the search term. 18. The system of claim 17 , wherein the search client is further configured to cause the computing device to at least: obtain a user request to increase an amount of the contextual content for the search term that is included in the rendering of the search results; and generate an updated rendering of the search results that comprises an increased amount of contextual content for the search term. | 0.501247 |
10,102,851 | 3 | 6 | 3. A computer-implemented method comprising: under control of one or more computing devices configured with specific computer-executable instructions, generating first speech recognition results using a first portion of a plurality of sequential portions of audio data, wherein the audio data represents a user utterance, and wherein the first speech recognition results are generated without using any sequential portion, of the plurality of sequential portions of audio data, following the first portion; generating a first semantic representation of the user utterance using the first speech recognition results and without using speech recognition results representing a second portion, of the plurality of sequential portions of audio data, following the first portion; determining a first score indicating a degree of confidence in the first semantic representation; determining that the first score satisfies a first threshold; in response to determining that the first score satisfies the first threshold: identifying a content item being requested by the user utterance; and loading a data file representing the content item; generating second speech recognition results using the first portion and the second portion of the plurality of sequential portions of audio data; generating a second semantic representation of the user utterance using the second speech recognition results; determining a second score indicating a degree to which the second semantic representation is the same as the first semantic representation; determining that the second score satisfies a second threshold; and in response to determining that the second score satisfies the second threshold, initiating presentation of the content item using the data file. | 3. A computer-implemented method comprising: under control of one or more computing devices configured with specific computer-executable instructions, generating first speech recognition results using a first portion of a plurality of sequential portions of audio data, wherein the audio data represents a user utterance, and wherein the first speech recognition results are generated without using any sequential portion, of the plurality of sequential portions of audio data, following the first portion; generating a first semantic representation of the user utterance using the first speech recognition results and without using speech recognition results representing a second portion, of the plurality of sequential portions of audio data, following the first portion; determining a first score indicating a degree of confidence in the first semantic representation; determining that the first score satisfies a first threshold; in response to determining that the first score satisfies the first threshold: identifying a content item being requested by the user utterance; and loading a data file representing the content item; generating second speech recognition results using the first portion and the second portion of the plurality of sequential portions of audio data; generating a second semantic representation of the user utterance using the second speech recognition results; determining a second score indicating a degree to which the second semantic representation is the same as the first semantic representation; determining that the second score satisfies a second threshold; and in response to determining that the second score satisfies the second threshold, initiating presentation of the content item using the data file. 6. The computer-implemented method of claim 3 , wherein the first portion of audio data comprises a portion prior to a first word boundary, and wherein the second portion of audio data comprises a portion subsequent to the first word boundary and prior to a second word boundary. | 0.813752 |
8,423,383 | 71 | 87 | 71. An online system for providing online medical consultation services including quantitative and qualitative medical opinions from a panel of selected medical professionals, the system comprising: (a) creating a database of potential participating medical professionals, along with information about each the potential participating medical professionals, including the qualifications of the potential participating medical professionals; (b) means for a user seeking medical consultation services to access the system; (c) means for user to electronically submit information to the system regarding the desired medical consultation services; (d) means for selecting a panel of medical professionals qualified to provide the desired medical consultation services based upon information in the database; (e) means for electronically providing question(s) based on the user submitted information, and the user submitted information, to the medical professionals in the selected panel such that the medical professionals in the selected panel formulate response(s) to provided question(s) and comments regarding user submitted information; (f) means for electronically forwarding the responses and comments from the medical professionals in the selected panel to the system; (g) means for calculating the degree of consensus of forwarded responses to questions; (h) means for displaying said calculated consensus on a system website accessible to user; and (i) means for displaying said comments forwarded from the medical professionals on a system website accessible to the user. | 71. An online system for providing online medical consultation services including quantitative and qualitative medical opinions from a panel of selected medical professionals, the system comprising: (a) creating a database of potential participating medical professionals, along with information about each the potential participating medical professionals, including the qualifications of the potential participating medical professionals; (b) means for a user seeking medical consultation services to access the system; (c) means for user to electronically submit information to the system regarding the desired medical consultation services; (d) means for selecting a panel of medical professionals qualified to provide the desired medical consultation services based upon information in the database; (e) means for electronically providing question(s) based on the user submitted information, and the user submitted information, to the medical professionals in the selected panel such that the medical professionals in the selected panel formulate response(s) to provided question(s) and comments regarding user submitted information; (f) means for electronically forwarding the responses and comments from the medical professionals in the selected panel to the system; (g) means for calculating the degree of consensus of forwarded responses to questions; (h) means for displaying said calculated consensus on a system website accessible to user; and (i) means for displaying said comments forwarded from the medical professionals on a system website accessible to the user. 87. The system of claim 71 further wherein the system is periodically checked for new user submissions. | 0.930686 |
7,996,407 | 13 | 14 | 13. A non-transitory computer executable program medium storing a program for making a computer execute a method for information clustering, said method making said computer execute the steps of; accumulating and clustering documents in a document repository, said documents including loosely related clusters between said documents being time sliced so as to define chunks of said documents; generating document-keyword vectors, said document-keyword vectors consisting of sparse numeral values depending on presence of keywords in said documents; reducing dimensions of said keywords to create a dimension reduction matrix of said document-keyword matrix; and generating a centroid vector of said cluster, said cluster being retrieved from said document-keyword vector using a principal component in a same line of said dimension reduction matrix, said centroid vectors being defined from keywords and weight of documents within said cluster; and storing said centroid vectors in an item repository together with said keywords and said weights of said centroid vector. | 13. A non-transitory computer executable program medium storing a program for making a computer execute a method for information clustering, said method making said computer execute the steps of; accumulating and clustering documents in a document repository, said documents including loosely related clusters between said documents being time sliced so as to define chunks of said documents; generating document-keyword vectors, said document-keyword vectors consisting of sparse numeral values depending on presence of keywords in said documents; reducing dimensions of said keywords to create a dimension reduction matrix of said document-keyword matrix; and generating a centroid vector of said cluster, said cluster being retrieved from said document-keyword vector using a principal component in a same line of said dimension reduction matrix, said centroid vectors being defined from keywords and weight of documents within said cluster; and storing said centroid vectors in an item repository together with said keywords and said weights of said centroid vector. 14. The program medium of claim 13 , wherein said method further comprises the steps of; retrieving a principal document in said document using said principal component as a first query vector and subsequently retrieving documents defining said clusters using said principal document as a second query vector. | 0.671277 |
9,875,222 | 1 | 5 | 1. A method for capturing video presentations, the method comprising: detecting, performed by one or more microprocessors, when a video presentation has begun by analyzing an incoming video stream; determining whether a presentation element in the video presentation is static or dynamic in response to detecting that the video presentation has begun; generating an image from the presentation element when the presentation element is static; generating a video clip from the presentation element when the presentation element is dynamic; extracting textual content of the presentation element from the image; associating a plurality of weights with a plurality of text of the textual content of the presentation element based on types of the plurality of text such that a first weight is associated with a first text of the plurality of text that is not a title of the presentation element and a second weight is associated with a second text of the plurality of text of the presentation element, the second weight being greater than the first weight and associated with the second text in response to determining that the second text is a title of the presentation element, the first text and the second text being weighted textual content; receiving supplemental content corresponding to the image or the video clip; storing the weighted textual content and the supplemental content in a searchable index; detecting when the video presentation has stopped by analyzing the incoming video stream; and stopping the generation of the video clip and the image in response to detecting that the video presentation has stopped, wherein in response to the extracted textual content associated with the image, stored in the searchable index, matching a search query: audio content is extracted from the generated video clip, and the audio content associated with the image is played and returned in response to the search query. | 1. A method for capturing video presentations, the method comprising: detecting, performed by one or more microprocessors, when a video presentation has begun by analyzing an incoming video stream; determining whether a presentation element in the video presentation is static or dynamic in response to detecting that the video presentation has begun; generating an image from the presentation element when the presentation element is static; generating a video clip from the presentation element when the presentation element is dynamic; extracting textual content of the presentation element from the image; associating a plurality of weights with a plurality of text of the textual content of the presentation element based on types of the plurality of text such that a first weight is associated with a first text of the plurality of text that is not a title of the presentation element and a second weight is associated with a second text of the plurality of text of the presentation element, the second weight being greater than the first weight and associated with the second text in response to determining that the second text is a title of the presentation element, the first text and the second text being weighted textual content; receiving supplemental content corresponding to the image or the video clip; storing the weighted textual content and the supplemental content in a searchable index; detecting when the video presentation has stopped by analyzing the incoming video stream; and stopping the generation of the video clip and the image in response to detecting that the video presentation has stopped, wherein in response to the extracted textual content associated with the image, stored in the searchable index, matching a search query: audio content is extracted from the generated video clip, and the audio content associated with the image is played and returned in response to the search query. 5. The method of claim 1 , wherein the audio content is extracted from the incoming video stream. | 0.802041 |
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