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8,396,714 | 15 | 16 | 15. The computer-readable medium of claim 14 , wherein the operations further comprise: synthesizing a speech segment based on the modified text string; and providing the speech segment to a user device for playback with the media asset on the user device. | 15. The computer-readable medium of claim 14 , wherein the operations further comprise: synthesizing a speech segment based on the modified text string; and providing the speech segment to a user device for playback with the media asset on the user device. 16. The computer-readable medium of claim 15 , wherein the connecter term type specifies a respective pronunciation version for the connector term, and wherein synthesizing the speech segment based on the modified text string further comprises: selecting a particular pronunciation for the connector term based on the respective pronunciation version; and synthesizing the speech segment in accordance with the particular pronunciation for the connector term and the phonemes obtained for the text string. | 0.5 |
10,121,467 | 4 | 5 | 4. The computer-implemented method of claim 1 , wherein the first score is based on a difference between a first vector representing how the first word sequence is used in the text corpus and a second vector representing how the second word sequence is used in the text corpus. | 4. The computer-implemented method of claim 1 , wherein the first score is based on a difference between a first vector representing how the first word sequence is used in the text corpus and a second vector representing how the second word sequence is used in the text corpus. 5. The computer-implemented method of claim 4 , wherein: the first vector is determined by processing the text corpus using a neural network language model, the neural network language model being trained using training text and indicators of word sequence validity. | 0.705752 |
10,068,085 | 13 | 16 | 13. A tangible, non-transitory computer-readable storage medium storing one or more programs, the one or more programs comprising instructions, when executed by a computing device, cause the computing device to: present, by the computing device, a prompt for a choice of at least one selected language during password creation; receive a user input selecting the at least one selected language in response to the prompt, wherein the at least one selected language is different from a device language that the electronic device defaults to once the electronic device is unlocked; present the keyboard with a first character mapping for the at least one selected language; receive a password input for password creation through the keyboard with the first character mapping, wherein the received password input for password creation is inputted in multiple languages; store data related to the at least one selected language used during password creation based on the user input, wherein the data comprises an identifier of the at least one selected language; present, by the electronic device, the keyboard with a second character mapping for the device language; after presenting the keyboard with the second character mapping, present, by the electronic device, a prompt for password entry; in response to the prompt for the password entry: select, by the electronic device, the first character mapping based on the identifier stored during password creation; and in response to selecting the first character mapping by the electronic device, automatically update, by the electronic device, the keyboard from the second character mapping for the device language to the first character mapping, wherein the keyboard is updated to the first character mapping while presenting the prompt for password entry; and receive a password input for password entry using the first character mapping, wherein the received password input for password entry is inputted in the multiple languages. | 13. A tangible, non-transitory computer-readable storage medium storing one or more programs, the one or more programs comprising instructions, when executed by a computing device, cause the computing device to: present, by the computing device, a prompt for a choice of at least one selected language during password creation; receive a user input selecting the at least one selected language in response to the prompt, wherein the at least one selected language is different from a device language that the electronic device defaults to once the electronic device is unlocked; present the keyboard with a first character mapping for the at least one selected language; receive a password input for password creation through the keyboard with the first character mapping, wherein the received password input for password creation is inputted in multiple languages; store data related to the at least one selected language used during password creation based on the user input, wherein the data comprises an identifier of the at least one selected language; present, by the electronic device, the keyboard with a second character mapping for the device language; after presenting the keyboard with the second character mapping, present, by the electronic device, a prompt for password entry; in response to the prompt for the password entry: select, by the electronic device, the first character mapping based on the identifier stored during password creation; and in response to selecting the first character mapping by the electronic device, automatically update, by the electronic device, the keyboard from the second character mapping for the device language to the first character mapping, wherein the keyboard is updated to the first character mapping while presenting the prompt for password entry; and receive a password input for password entry using the first character mapping, wherein the received password input for password entry is inputted in the multiple languages. 16. The tangible, non-transitory computer readable storage medium of claim 13 , wherein the one or more programs cause the computing device to: allow a device administrator to preselect a set of languages, wherein the at least one selected language is selected from the preselected set of languages during password creation. | 0.5 |
7,721,259 | 1 | 2 | 1. A configurable software application system comprising: a processor; and a memory coupled to the processor and configured to store a software application configuration tool executable by the processor for generation of customized metadata variants of a software application, the software application configuration tool including: base metadata configured to characterize data processing logic within the software application; custom metadata configured to define a variant of the software application including custom data processing logic within the software application, the custom metadata data being configured to be overlaid on the base metadata and to inherit attributes of the base metadata; a context evaluator configured to overlay the custom metadata on the base metadata in response to a request to execute the software application received from an end user, responsive to an execution context; a runtime metadata interpreter configured to generate executable instructions for the software application using the base metadata and overlaid custom metadata at runtime; wherein the configuration system includes a metadata packager configured to determine that the custom metadata and the base metadata are needed to generate an executable variant of the software application; and a metadata analyzer configured to determine if the first custom metadata meets the requirements of relationship metadata when overlaid on the base metadata. | 1. A configurable software application system comprising: a processor; and a memory coupled to the processor and configured to store a software application configuration tool executable by the processor for generation of customized metadata variants of a software application, the software application configuration tool including: base metadata configured to characterize data processing logic within the software application; custom metadata configured to define a variant of the software application including custom data processing logic within the software application, the custom metadata data being configured to be overlaid on the base metadata and to inherit attributes of the base metadata; a context evaluator configured to overlay the custom metadata on the base metadata in response to a request to execute the software application received from an end user, responsive to an execution context; a runtime metadata interpreter configured to generate executable instructions for the software application using the base metadata and overlaid custom metadata at runtime; wherein the configuration system includes a metadata packager configured to determine that the custom metadata and the base metadata are needed to generate an executable variant of the software application; and a metadata analyzer configured to determine if the first custom metadata meets the requirements of relationship metadata when overlaid on the base metadata. 2. The system of claim 1 , further including a configuration system configured for a user of the configuration system to define the custom metadata. | 0.614583 |
9,805,025 | 7 | 11 | 7. A computer implemented method for determination of standard exact clauses and non-standard clauses from a plurality of documents, the method comprising: obtaining a primary policy comprising one or more features, a clause example, and a first threshold for generating a plurality of feature replaced clauses by automatically replacing one or more of the original clauses in the plurality of documents with a feature of the one or more features; comparing each of the plurality of feature replaced clauses and a clause example using a semantic language evaluator to obtain a first feature data set comprising standard clauses; automatically replacing an available variation of one of the standard clauses in the plurality of documents with a variable; comparing a clause and at least one of the clause example and the variable, the clause obtained from the plurality of documents with the available variation replaced with the variable; obtaining, in response to the comparison, the standard exact clause comprising the clause matching at least one of the clause example and the variable; obtaining a second feature data set encompassing the first feature data set, the second feature data set corresponding to a secondary policy, the secondary policy comprising the one or more features, the clause example, and a second threshold for use in the semantic language evaluator; obtaining a difference data set comprised of a difference between the first feature data set and the second feature data set, the difference data set comprising a non-standard clause, the non-standard clause being semantically related to but not matching the clause example; and updating, automatically in response to obtaining the difference data set, a database to identify the standard exact clause and the non-standard clause from the plurality of documents. | 7. A computer implemented method for determination of standard exact clauses and non-standard clauses from a plurality of documents, the method comprising: obtaining a primary policy comprising one or more features, a clause example, and a first threshold for generating a plurality of feature replaced clauses by automatically replacing one or more of the original clauses in the plurality of documents with a feature of the one or more features; comparing each of the plurality of feature replaced clauses and a clause example using a semantic language evaluator to obtain a first feature data set comprising standard clauses; automatically replacing an available variation of one of the standard clauses in the plurality of documents with a variable; comparing a clause and at least one of the clause example and the variable, the clause obtained from the plurality of documents with the available variation replaced with the variable; obtaining, in response to the comparison, the standard exact clause comprising the clause matching at least one of the clause example and the variable; obtaining a second feature data set encompassing the first feature data set, the second feature data set corresponding to a secondary policy, the secondary policy comprising the one or more features, the clause example, and a second threshold for use in the semantic language evaluator; obtaining a difference data set comprised of a difference between the first feature data set and the second feature data set, the difference data set comprising a non-standard clause, the non-standard clause being semantically related to but not matching the clause example; and updating, automatically in response to obtaining the difference data set, a database to identify the standard exact clause and the non-standard clause from the plurality of documents. 11. The method of claim 7 , further comprising: automatically replacing available variations of one or more of the standard clauses in the plurality of documents with additional variables; and comparing additional clauses and additional clause examples to obtain additional standard exact clauses, the additional clauses obtained from the plurality of documents with the available variation replaced with the additional variables, the additional standard exact clauses comprising the additional clauses matching respective ones of the additional clause examples and the additional variables. | 0.5 |
8,615,804 | 6 | 7 | 6. The method as claimed in claim 5 , wherein the value comparison is used to compare the characters during execution of the executable computer code, whereby the executable computer code continues to function normally as the value comparison is used and the taint status of each of the characters is carried along with each of the characters. | 6. The method as claimed in claim 5 , wherein the value comparison is used to compare the characters during execution of the executable computer code, whereby the executable computer code continues to function normally as the value comparison is used and the taint status of each of the characters is carried along with each of the characters. 7. The method as claimed in claim 6 , wherein the taint status of the characters is not considered during the value comparison. | 0.5 |
9,531,649 | 1 | 10 | 1. A computer-implemented method, comprising: receiving, at a computing system and as having been sent by a first remote computing device, an electronic message that includes a username but does not include information that fully identifies a recipient for the electronic message; identifying, by the computing system, multiple domains for which the username may be valid, including a first domain and a second domain; querying, by the computing system, the first domain to determine that the username in the electronic message is not a valid username for the first domain; querying, by the computing system, the second domain to determine that the username in the electronic message is a valid username for the second domain; selecting, by the computing system and based on having determined that the username in the electronic message is not a valid username for the first domain but is a valid username for the second domain, to transmit the electronic message to a user account that is associated with the username and the second domain; identifying, by the computing system, a second remote computing device that is associated with the user account and to which the electronic message is to be transmitted; modifying, by the computing system and before the electronic message is transmitted to the second remote computing device, the electronic message to add the second domain into the electronic message, so that the electronic message includes information that fully identifies the recipient for the electronic message; and transmitting, by the computing system as a result of having selected to transmit the electronic message to the user account, the electronic message that has been modified to include the second domain to the second remote computing device that is associated with the user account. | 1. A computer-implemented method, comprising: receiving, at a computing system and as having been sent by a first remote computing device, an electronic message that includes a username but does not include information that fully identifies a recipient for the electronic message; identifying, by the computing system, multiple domains for which the username may be valid, including a first domain and a second domain; querying, by the computing system, the first domain to determine that the username in the electronic message is not a valid username for the first domain; querying, by the computing system, the second domain to determine that the username in the electronic message is a valid username for the second domain; selecting, by the computing system and based on having determined that the username in the electronic message is not a valid username for the first domain but is a valid username for the second domain, to transmit the electronic message to a user account that is associated with the username and the second domain; identifying, by the computing system, a second remote computing device that is associated with the user account and to which the electronic message is to be transmitted; modifying, by the computing system and before the electronic message is transmitted to the second remote computing device, the electronic message to add the second domain into the electronic message, so that the electronic message includes information that fully identifies the recipient for the electronic message; and transmitting, by the computing system as a result of having selected to transmit the electronic message to the user account, the electronic message that has been modified to include the second domain to the second remote computing device that is associated with the user account. 10. The computer-implemented method of claim 1 , wherein the electronic message does not include a name of the first domain, and does not include a name of the second domain. | 0.861685 |
8,965,910 | 2 | 3 | 2. The method of claim 1 , further comprising, before step (a), searching for an ontology schema path between classes with respect to all classes stored in the ontology schema database, respectively, and storing the searched ontology schema paths in the ontology schema path database. | 2. The method of claim 1 , further comprising, before step (a), searching for an ontology schema path between classes with respect to all classes stored in the ontology schema database, respectively, and storing the searched ontology schema paths in the ontology schema path database. 3. The method of claim 2 , further comprising, if an update of the ontology schema database is detected, searching for an ontology schema path of the updated class and updating the ontology schema path database. | 0.5 |
8,600,736 | 1 | 22 | 1. A method of operating a computer to perform linguistic analysis, comprising the steps of: splitting an input text into words and sentences; for each sentence, comparing phrases in each sentence with known phrases stored in a database, as follows: for each word in the sentence, comparing a value thereof and values of the words following it with values of words of stored phrases; in the event a match is found between the value of at least two consecutive words and the value of words of a stored phrase, labelling the matched at least two consecutive words with an overphrase that describes the matched value; after a penultimate word has been compared, recasting the sentence by replacing the matched phrases by respective overphrases; and then repeating the step of comparing phrases with the recast sentence until there is no further recasting by the step of using the overphrase in the comparison as a word until there is no further match found. | 1. A method of operating a computer to perform linguistic analysis, comprising the steps of: splitting an input text into words and sentences; for each sentence, comparing phrases in each sentence with known phrases stored in a database, as follows: for each word in the sentence, comparing a value thereof and values of the words following it with values of words of stored phrases; in the event a match is found between the value of at least two consecutive words and the value of words of a stored phrase, labelling the matched at least two consecutive words with an overphrase that describes the matched value; after a penultimate word has been compared, recasting the sentence by replacing the matched phrases by respective overphrases; and then repeating the step of comparing phrases with the recast sentence until there is no further recasting by the step of using the overphrase in the comparison as a word until there is no further match found. 22. A method according to claim 1 , wherein said step of comparing each word in the sentence and values of the words following it with values of words of stored phrases, performs this step, starting with a longest stored phrase that starts with that word, and working from longest to shortest. | 0.533439 |
6,105,044 | 22 | 28 | 22. The data processing system of claim 21, wherein the means for receiving only the requested portion includes means for receiving a starting point element, the starting point element having been selected according to the indicated starting point; and wherein the means of generating a digital form includes: means for providing a plurality of property specifications for type names utilized for elements in the digital document; means for receiving an identity of any ancestor elements of the starting point element; and means for applying a property specification corresponding to the type name of ancestor elements identified for each selected element to the text content of each selected element to produce the digital form. | 22. The data processing system of claim 21, wherein the means for receiving only the requested portion includes means for receiving a starting point element, the starting point element having been selected according to the indicated starting point; and wherein the means of generating a digital form includes: means for providing a plurality of property specifications for type names utilized for elements in the digital document; means for receiving an identity of any ancestor elements of the starting point element; and means for applying a property specification corresponding to the type name of ancestor elements identified for each selected element to the text content of each selected element to produce the digital form. 28. The data processing system of claim 22, further comprising means for providing access to an indication of the starting point element in a history table. | 0.872757 |
6,119,122 | 1 | 2 | 1. A computer system, comprising: a) a management service for a computer network having a plurality of objects of different types, each of said objects having at least one associated attribute with an attribute syntax, a plurality of said attributes having an associated value being of a data type corresponding to the attribute syntax of the associated attribute; b) a data structure adapted to represent one or more attributes and associated values of a target object, said data structure being capable of being modified; c) a user interface for displaying at least a portion of the data structure as an attribute tree structure irrespective of the target object type, said user interface being adapted to receive inputs from a human user; d) one or more generic syntax editors adapted to receive inputs from a human user to modify the data structure, each of said one or more generic syntax editors corresponding to at least one attribute syntax; and e) a mechanism to modify the target object to include modifications made to the data structure. | 1. A computer system, comprising: a) a management service for a computer network having a plurality of objects of different types, each of said objects having at least one associated attribute with an attribute syntax, a plurality of said attributes having an associated value being of a data type corresponding to the attribute syntax of the associated attribute; b) a data structure adapted to represent one or more attributes and associated values of a target object, said data structure being capable of being modified; c) a user interface for displaying at least a portion of the data structure as an attribute tree structure irrespective of the target object type, said user interface being adapted to receive inputs from a human user; d) one or more generic syntax editors adapted to receive inputs from a human user to modify the data structure, each of said one or more generic syntax editors corresponding to at least one attribute syntax; and e) a mechanism to modify the target object to include modifications made to the data structure. 2. A computer system as recited in claim 1, wherein upon the selection of an attribute or its value, a generic syntax editor is displayed corresponding to the attribute syntax of the selected attribute. | 0.5 |
8,572,539 | 1 | 3 | 1. A system for regulating voltage to a plurality of circuit elements in a datapath to maximize power efficiency in a desynchronized circuit, the system, comprising: a first controller circuit, the first controller circuit comprising at least a first pulsed latch enable signal, a request signal output and an acknowledge signal input; a second controller circuit, the second controller circuit comprising at least second pulsed latch enable signal, a request signal input and an acknowledge signal output; a request event conductor to transmit the request signal output of the first controller circuit to the request signal input of the second controller circuit; an acknowledge event conductor to transmit the acknowledge signal output of the second controller circuit to the acknowledge signal input of the first controller circuit; a detector component, comprising a filter circuit, to detect a speed mismatch over a selectable period of time to determine a time separation between a first time of arrival of a request event signal assertion on the request signal output and a second time of arrival of an acknowledge event signal assertion on the acknowledge signal output, wherein the selectable period of time is based at least in part on a selectable number of samples; and a compensator circuit to adjust a supply voltage to the plurality of circuit elements in the data path based on the detected time separation. | 1. A system for regulating voltage to a plurality of circuit elements in a datapath to maximize power efficiency in a desynchronized circuit, the system, comprising: a first controller circuit, the first controller circuit comprising at least a first pulsed latch enable signal, a request signal output and an acknowledge signal input; a second controller circuit, the second controller circuit comprising at least second pulsed latch enable signal, a request signal input and an acknowledge signal output; a request event conductor to transmit the request signal output of the first controller circuit to the request signal input of the second controller circuit; an acknowledge event conductor to transmit the acknowledge signal output of the second controller circuit to the acknowledge signal input of the first controller circuit; a detector component, comprising a filter circuit, to detect a speed mismatch over a selectable period of time to determine a time separation between a first time of arrival of a request event signal assertion on the request signal output and a second time of arrival of an acknowledge event signal assertion on the acknowledge signal output, wherein the selectable period of time is based at least in part on a selectable number of samples; and a compensator circuit to adjust a supply voltage to the plurality of circuit elements in the data path based on the detected time separation. 3. The system as set forth in claim 1 , wherein the compensator circuit comprises at least one of, a signal to raise a voltage, a signal to lower a voltage, a signal to select a number of samples. | 0.623077 |
7,877,371 | 9 | 12 | 9. A non-transitory computer-readable storage medium storing instructions that when executed by a computer cause the computer to perform a method for selectively deleting clusters of conceptually-related words from a probabilistic generative model for textual documents, the method comprising: receiving a current model, which contains terminal nodes representing random variables for words and contains one or more cluster nodes representing clusters of conceptually related words; wherein nodes in the current model are coupled together by weighted links, so that for a cluster node with an incoming link from a node that has fired which causes the cluster node in the current model to fire with a probability proportionate to a weight of the incoming link, an outgoing link from the cluster node to another node causes the other node to fire with a probability proportionate to the weight of the outgoing link; and processing a given cluster node in the current model for possible deletion by, determining a number of outgoing links from the given cluster node to terminal nodes and/or cluster nodes in the current model; determining that the determined number of outgoing links is less than a minimum value; and deleting the given cluster node from the current model. | 9. A non-transitory computer-readable storage medium storing instructions that when executed by a computer cause the computer to perform a method for selectively deleting clusters of conceptually-related words from a probabilistic generative model for textual documents, the method comprising: receiving a current model, which contains terminal nodes representing random variables for words and contains one or more cluster nodes representing clusters of conceptually related words; wherein nodes in the current model are coupled together by weighted links, so that for a cluster node with an incoming link from a node that has fired which causes the cluster node in the current model to fire with a probability proportionate to a weight of the incoming link, an outgoing link from the cluster node to another node causes the other node to fire with a probability proportionate to the weight of the outgoing link; and processing a given cluster node in the current model for possible deletion by, determining a number of outgoing links from the given cluster node to terminal nodes and/or cluster nodes in the current model; determining that the determined number of outgoing links is less than a minimum value; and deleting the given cluster node from the current model. 12. The computer-readable storage medium of claim 9 , wherein deleting the given cluster node from the current model involves: deleting outgoing links from the given cluster node; deleting incoming links into the given cluster node; and deleting the given cluster node. | 0.724949 |
9,239,710 | 11 | 19 | 11. A method to perform a software application transformation, comprising: receiving a source grammar comprising a plurality of source grammar elements of a source application, the source grammar specifying syntactic rules governing a source programming language of the source application; receiving a plurality of target grammars comprising a plurality of target grammar elements of a transformed application, the plurality of target grammars comprising different target grammars of multiple target programming languages, each of the plurality of target grammars specifying syntactic rules governing a corresponding target programming language of the transformed application; receiving a rules set comprising a plurality of rules specifying transformations from at least one source grammar element of the source grammar into at least one target grammar element of the plurality of target grammars; receiving a source input containing at least one source code construct in the source grammar; analyzing, using at least one processor, the received source input to determine a structure for an abstract syntax tree; creating, using the at least one processor, a composite grammar that includes at least one portion of the source grammar of the source programming language and at least one portion of the plurality of target grammars of the multiple target programming languages; generating, using the at least one processor, the abstract syntax tree based at least on an analysis of the source input, wherein the abstract syntax tree represents at least a portion of the composite grammar that includes the at least one portion the source grammar of the source programming language, and at least one portion of a first target grammar of a first target programming language and at least one portion of a second target grammar of a second target programming language, and contains a node having a node annotation that corresponds to a rule of the rules set, the first target grammar being different than the second target grammar; and transforming, using the at least one processor, the generated abstract syntax tree based on at least one rule of the rules set. | 11. A method to perform a software application transformation, comprising: receiving a source grammar comprising a plurality of source grammar elements of a source application, the source grammar specifying syntactic rules governing a source programming language of the source application; receiving a plurality of target grammars comprising a plurality of target grammar elements of a transformed application, the plurality of target grammars comprising different target grammars of multiple target programming languages, each of the plurality of target grammars specifying syntactic rules governing a corresponding target programming language of the transformed application; receiving a rules set comprising a plurality of rules specifying transformations from at least one source grammar element of the source grammar into at least one target grammar element of the plurality of target grammars; receiving a source input containing at least one source code construct in the source grammar; analyzing, using at least one processor, the received source input to determine a structure for an abstract syntax tree; creating, using the at least one processor, a composite grammar that includes at least one portion of the source grammar of the source programming language and at least one portion of the plurality of target grammars of the multiple target programming languages; generating, using the at least one processor, the abstract syntax tree based at least on an analysis of the source input, wherein the abstract syntax tree represents at least a portion of the composite grammar that includes the at least one portion the source grammar of the source programming language, and at least one portion of a first target grammar of a first target programming language and at least one portion of a second target grammar of a second target programming language, and contains a node having a node annotation that corresponds to a rule of the rules set, the first target grammar being different than the second target grammar; and transforming, using the at least one processor, the generated abstract syntax tree based on at least one rule of the rules set. 19. The method of claim 11 , wherein the transforming includes subjecting the at least one rule of the rules set to a condition. | 0.963984 |
7,898,394 | 8 | 13 | 8. A system for providing and accessing information, the system comprising: a knowledgebase configured to store information items associated with a community; a portal configured to couple with the knowledgebase and provide access to the knowledgebase; and a tagging module configured to be coupled with the knowledgebase and the portal, wherein the tagging module is configured to provide for a first set of tags configured to be applied to the information items in the knowledgebase, provide for a second set of tags configured to be applied to information items in the knowledgebase, and search the knowledgebase based on at least one of the first set of tags and the second set of tags. | 8. A system for providing and accessing information, the system comprising: a knowledgebase configured to store information items associated with a community; a portal configured to couple with the knowledgebase and provide access to the knowledgebase; and a tagging module configured to be coupled with the knowledgebase and the portal, wherein the tagging module is configured to provide for a first set of tags configured to be applied to the information items in the knowledgebase, provide for a second set of tags configured to be applied to information items in the knowledgebase, and search the knowledgebase based on at least one of the first set of tags and the second set of tags. 13. The system of claim 8 , further comprising a staging area coupled to the knowledgebase, wherein staging area is configured to store a new information item received through the portal. | 0.637597 |
7,788,582 | 7 | 11 | 7. A computer readable medium as recited in claim 5 , wherein the fields presented in the search assistant are dynamically determined and are different depending on a selection of one of the categories. | 7. A computer readable medium as recited in claim 5 , wherein the fields presented in the search assistant are dynamically determined and are different depending on a selection of one of the categories. 11. A computer readable medium as recited in claim 7 , wherein the different predetermined categories in the search assistant further includes at least one of: an audiobooks category and a podcasts category. | 0.5 |
9,607,105 | 1 | 4 | 1. A method comprising: under control of one or more computing systems configured with specific executable instructions: receiving a content item associated with a content source, the content item including one or more approved portions that have been approved by a publisher for providing as a search result; identifying the one or more approved portions of an electronic book; extracting the one or more approved portions from the content item received from the content source to form extracted textual content; creating a digital sample for the content item, wherein the digital sample includes the extracted textual content from the content item, a type associated with the content item and a content item identifier that identifies the content item; receiving a search query from a client computing device; searching for the search query within the digital sample; identifying search results within the digital sample associated with the search query based at least in part on the searching; mapping the search results to a portion of the content item received from the content source, wherein the mapping the search results to the portion of the content item comprises: receiving a results identifier associated with the search results, and an associated text string; mapping the results identifier to the content item identifier; determining a location of the associated text string from within the content item based at least in part on the results identifier; and converting the associated text string to a format for presentation on the client computing device; and providing the portion of the content items to the client computing device. | 1. A method comprising: under control of one or more computing systems configured with specific executable instructions: receiving a content item associated with a content source, the content item including one or more approved portions that have been approved by a publisher for providing as a search result; identifying the one or more approved portions of an electronic book; extracting the one or more approved portions from the content item received from the content source to form extracted textual content; creating a digital sample for the content item, wherein the digital sample includes the extracted textual content from the content item, a type associated with the content item and a content item identifier that identifies the content item; receiving a search query from a client computing device; searching for the search query within the digital sample; identifying search results within the digital sample associated with the search query based at least in part on the searching; mapping the search results to a portion of the content item received from the content source, wherein the mapping the search results to the portion of the content item comprises: receiving a results identifier associated with the search results, and an associated text string; mapping the results identifier to the content item identifier; determining a location of the associated text string from within the content item based at least in part on the results identifier; and converting the associated text string to a format for presentation on the client computing device; and providing the portion of the content items to the client computing device. 4. The method of claim 1 , wherein the converting the associated text string to the format for presentation on the client computing device further comprises converting the associated text string to at least one of hypertext markup language (HTML) text format or an eBook format. | 0.582583 |
7,756,987 | 10 | 11 | 10. A method implemented at least in part by a computing device, the method comprising: providing a typographically erroneous domain name; tracing the domain name wherein the tracing comprises entering the domain name as part of a URL and recording one or more subsequent URLs; identifying a domain parking service for the domain name based at least in part on information in one of the recorded URLs; determining client identification information in at least one of the recorded URLs wherein the client identification information identifies a customer of the domain parking service, wherein the client identification information is a particular client identifier extracted from a Client ID (cid) field of the final destination URL; and blocking one or more domain names based at least in part on the client identification information. | 10. A method implemented at least in part by a computing device, the method comprising: providing a typographically erroneous domain name; tracing the domain name wherein the tracing comprises entering the domain name as part of a URL and recording one or more subsequent URLs; identifying a domain parking service for the domain name based at least in part on information in one of the recorded URLs; determining client identification information in at least one of the recorded URLs wherein the client identification information identifies a customer of the domain parking service, wherein the client identification information is a particular client identifier extracted from a Client ID (cid) field of the final destination URL; and blocking one or more domain names based at least in part on the client identification information. 11. The method of claim 10 further comprising storing the client identification information in a database wherein the database comprises a database for use in blocking domain names. | 0.618143 |
7,650,272 | 17 | 31 | 17. An apparatus for automatically evaluating Bayesian network models for decision support, the apparatus comprising a computer system including a processor, a memory coupled with the processor, an input coupled with the processor for receiving user input and data input, and an output coupled with the processor for outputting display data, wherein the computer system further comprises means, residing in its processor and memory, for: receiving a Bayesian Network (BN) model including evidence nodes and conclusion nodes, where the conclusion nodes are linked with the evidence nodes by causal dependency links, and where the evidence nodes have evidence states and the conclusion nodes have conclusion states; setting the states of the conclusion nodes to desired conclusion states and determining, by propagating down the causal dependency links, a corresponding probability of occurrence of evidence states of the evidence nodes and producing, from the probability of occurrence, a plurality of samples of most likely states of the evidence nodes; setting the states of the evidence nodes to states corresponding to the plurality of samples of the evidence states, and propagating the evidence states back up the causal dependency links to the conclusion nodes, to obtain a plurality of probabilities of the resulting states of the conclusion nodes; and outputting a representation of the plurality of the probabilities of the resulting states of the conclusion nodes. | 17. An apparatus for automatically evaluating Bayesian network models for decision support, the apparatus comprising a computer system including a processor, a memory coupled with the processor, an input coupled with the processor for receiving user input and data input, and an output coupled with the processor for outputting display data, wherein the computer system further comprises means, residing in its processor and memory, for: receiving a Bayesian Network (BN) model including evidence nodes and conclusion nodes, where the conclusion nodes are linked with the evidence nodes by causal dependency links, and where the evidence nodes have evidence states and the conclusion nodes have conclusion states; setting the states of the conclusion nodes to desired conclusion states and determining, by propagating down the causal dependency links, a corresponding probability of occurrence of evidence states of the evidence nodes and producing, from the probability of occurrence, a plurality of samples of most likely states of the evidence nodes; setting the states of the evidence nodes to states corresponding to the plurality of samples of the evidence states, and propagating the evidence states back up the causal dependency links to the conclusion nodes, to obtain a plurality of probabilities of the resulting states of the conclusion nodes; and outputting a representation of the plurality of the probabilities of the resulting states of the conclusion nodes. 31. An apparatus for automatically evaluating Bayesian network models for decision support as set forth in claim 17 , wherein the conclusion nodes are weighted by weights representing their importance; whereby an accuracy of the BN model's propensity to yield proper conclusions may be weighted for particular conclusions based on their relative importance. | 0.604213 |
8,239,562 | 3 | 5 | 3. The method of claim 1 , wherein at least one context entry in the context store comprises a context entry metadata element defining restrictions on the use of the at least one context entry. | 3. The method of claim 1 , wherein at least one context entry in the context store comprises a context entry metadata element defining restrictions on the use of the at least one context entry. 5. The method of claim 3 , wherein the restrictions on the use of the at least one context entry include at least one restriction based on a resource address. | 0.5 |
9,251,172 | 7 | 12 | 7. A non-transitory computer-readable medium encoded with a computer program to provide digital assets in response to a search for digital assets, the computer program including instructions to perform a method comprising: receiving a search query from a user to locate at least one digital asset from a collection of digital assets, wherein each digital asset in the collection of digital assets has associated therewith at least one keyword, wherein the associated keywords are included in a collection of keywords organized by their ancestor, descendant, or sibling relationships to each other, and wherein the search query is conformed to one of the keywords in the collection of keywords; determining a first set of digital assets related to the conformed search query, wherein each digital asset has associated therewith a keyword that matches the conformed search query, wherein determining the first set of digital assets further comprises determining first suggested keywords from the collection of keywords, and wherein determining the first suggested keywords is based on an ancestor, descendant, or sibling relationship in the collection of keywords between the first suggested keywords and the conformed search query that exists prior to receiving the search query from the user; presenting the first set of digital assets to the user; wherein presenting the first set of digital assets to the user further comprises presenting the first suggested keywords to the user; generating a refinement term based on a selection, received from the user, of a keyword from the first suggested keywords, the refinement term having a concept or subject in common with the selected keyword in the hierarchical structure; determining a second set of digital assets related to the refinement term, wherein each digital asset in the second set of digital assets has associated therewith a keyword from the collection of keywords that matches the refinement term, wherein determining the second set of digital assets further comprises determining second suggested keywords from the collection of keywords, and wherein determining the second suggested keywords from the collection of keywords is based on the first suggested keywords and the refinement term; and presenting the second set of digital images and the second suggested keywords to the user. | 7. A non-transitory computer-readable medium encoded with a computer program to provide digital assets in response to a search for digital assets, the computer program including instructions to perform a method comprising: receiving a search query from a user to locate at least one digital asset from a collection of digital assets, wherein each digital asset in the collection of digital assets has associated therewith at least one keyword, wherein the associated keywords are included in a collection of keywords organized by their ancestor, descendant, or sibling relationships to each other, and wherein the search query is conformed to one of the keywords in the collection of keywords; determining a first set of digital assets related to the conformed search query, wherein each digital asset has associated therewith a keyword that matches the conformed search query, wherein determining the first set of digital assets further comprises determining first suggested keywords from the collection of keywords, and wherein determining the first suggested keywords is based on an ancestor, descendant, or sibling relationship in the collection of keywords between the first suggested keywords and the conformed search query that exists prior to receiving the search query from the user; presenting the first set of digital assets to the user; wherein presenting the first set of digital assets to the user further comprises presenting the first suggested keywords to the user; generating a refinement term based on a selection, received from the user, of a keyword from the first suggested keywords, the refinement term having a concept or subject in common with the selected keyword in the hierarchical structure; determining a second set of digital assets related to the refinement term, wherein each digital asset in the second set of digital assets has associated therewith a keyword from the collection of keywords that matches the refinement term, wherein determining the second set of digital assets further comprises determining second suggested keywords from the collection of keywords, and wherein determining the second suggested keywords from the collection of keywords is based on the first suggested keywords and the refinement term; and presenting the second set of digital images and the second suggested keywords to the user. 12. The computer-readable medium of claim 7 , wherein the second set of digital assets includes digital assets that are not included in the first set of digital assets. | 0.710345 |
8,321,220 | 1 | 7 | 1. A method of generating a spoken language understanding module, the method comprising: a. selecting, via a processor, at least one predicate/argument pair as an intent from a set of a most frequent predicate/argument pairs for a domain associated with a spoken dialog system in a first language; b. labeling training data using mapping rules for the first language associated with the selected at least one predicate/argument pair and that specify rules for selecting a call-type label for an utterance; c. training a call-type classification model using the labeled training data; d. re-labeling the training data using the call-type classification model; and e. iteratively processing steps (c) and (d) until training set labels converge. | 1. A method of generating a spoken language understanding module, the method comprising: a. selecting, via a processor, at least one predicate/argument pair as an intent from a set of a most frequent predicate/argument pairs for a domain associated with a spoken dialog system in a first language; b. labeling training data using mapping rules for the first language associated with the selected at least one predicate/argument pair and that specify rules for selecting a call-type label for an utterance; c. training a call-type classification model using the labeled training data; d. re-labeling the training data using the call-type classification model; and e. iteratively processing steps (c) and (d) until training set labels converge. 7. The method of claim 1 , wherein selecting the at least one predicate/argument pair is processed independent of the domain. | 0.609375 |
8,649,572 | 14 | 20 | 14. A system comprising: one or more processors; a memory resource that stores instructions for execution by the one or more processors; wherein the one or more processors are configured to execute instructions stored in the memory resource in performing operations comprising: analyze an image to detect a portion of the image that corresponds to a person, and to recognize information from the image for the person; determine a set of metadata for the image, wherein the set of metadata includes the recognized information, and data that identifies the portion of the image apart from a remainder of the image; associate a set of permissions with the set of metadata; provide the set of metadata with the image in accordance with the set of permissions; wherein the set of metadata is provided by: enabling the portion of the image depicting the person to be selectable separate from the remainder of the image, and providing the recognized information with the image of the person in response to a user selecting the portion of the image that corresponds to the person. | 14. A system comprising: one or more processors; a memory resource that stores instructions for execution by the one or more processors; wherein the one or more processors are configured to execute instructions stored in the memory resource in performing operations comprising: analyze an image to detect a portion of the image that corresponds to a person, and to recognize information from the image for the person; determine a set of metadata for the image, wherein the set of metadata includes the recognized information, and data that identifies the portion of the image apart from a remainder of the image; associate a set of permissions with the set of metadata; provide the set of metadata with the image in accordance with the set of permissions; wherein the set of metadata is provided by: enabling the portion of the image depicting the person to be selectable separate from the remainder of the image, and providing the recognized information with the image of the person in response to a user selecting the portion of the image that corresponds to the person. 20. The system of claim 14 , wherein the recognized information corresponds to a name, and wherein providing the image for display includes displaying the name of the person as an overlay of the image. | 0.617871 |
10,152,299 | 1 | 21 | 1. A method for reducing response latency of intelligent automated assistants, the method comprising: at an electronic device: receiving, from a user, a speech input containing a user request; transmitting, to a server, a representation of the speech input; receiving, from the server, a domain signal defining a relevant domain of an actionable intent inferred from the user request; determining whether the relevant domain is associated with a predefined action of a set of predefined actions supported by the electronic device; in response to determining that the relevant domain is associated with a predefined action on the electronic device, performing the predefined action; after at least partially performing the predefined action, receiving, from the server, data content relevant to satisfying the user request, wherein the data content is generated according to an executed task flow corresponding to the actionable intent, and wherein performing the predefined action at least partially prepares the electronic device to process the received data content; and outputting a result based on the data content to at least partially satisfy the user request. | 1. A method for reducing response latency of intelligent automated assistants, the method comprising: at an electronic device: receiving, from a user, a speech input containing a user request; transmitting, to a server, a representation of the speech input; receiving, from the server, a domain signal defining a relevant domain of an actionable intent inferred from the user request; determining whether the relevant domain is associated with a predefined action of a set of predefined actions supported by the electronic device; in response to determining that the relevant domain is associated with a predefined action on the electronic device, performing the predefined action; after at least partially performing the predefined action, receiving, from the server, data content relevant to satisfying the user request, wherein the data content is generated according to an executed task flow corresponding to the actionable intent, and wherein performing the predefined action at least partially prepares the electronic device to process the received data content; and outputting a result based on the data content to at least partially satisfy the user request. 21. The method of claim 1 , wherein performing the predefined action does not contribute to the generation of the data content. | 0.883057 |
9,787,830 | 7 | 10 | 7. 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: obtaining a recording of a particular user speaking a name of a contact; receiving a voice dialing command including an utterance of the name of the contact by the particular user; and in response to receiving the voice dialing command including the utterance of the name of the contact by the particular user, providing, for output, the recording of the particular user speaking the name of the contact or a text-to-speech audio output of the name, and initiating a voice dialing operation between the particular user and the contact. | 7. 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: obtaining a recording of a particular user speaking a name of a contact; receiving a voice dialing command including an utterance of the name of the contact by the particular user; and in response to receiving the voice dialing command including the utterance of the name of the contact by the particular user, providing, for output, the recording of the particular user speaking the name of the contact or a text-to-speech audio output of the name, and initiating a voice dialing operation between the particular user and the contact. 10. The system of claim 7 , wherein obtaining a recording of a particular user speaking a name of a contact comprises: recording the particular user speaking the name of the contact. | 0.697674 |
7,765,574 | 1 | 2 | 1. A method for automatically transforming a representation of a multimedia presentation having multiple information streams contained therein, the multiple information streams representing a plurality of multimedia presentation sources, the method comprising the steps of: (a) developing by a computer a set of presentation models, each presentation model associated with a class of multimedia presentations, each model defining expected event cues within at least one information stream of the multimedia presentation for a class of presentations to which a specific multimedia presentation belongs, the model being a finite state automaton having states corresponding to segments of the presentation class, and having state transitions corresponding to expected event cues, each model thereby also specifying an expected time sequence of state transitions between event cues for the class of presentations to which it relates; and” (b) determining by a computer that transforming the representation of the multimedia presentation belongs to a particular multimedia presentation class based upon the results of matching observed event cues against the set of presentation models. | 1. A method for automatically transforming a representation of a multimedia presentation having multiple information streams contained therein, the multiple information streams representing a plurality of multimedia presentation sources, the method comprising the steps of: (a) developing by a computer a set of presentation models, each presentation model associated with a class of multimedia presentations, each model defining expected event cues within at least one information stream of the multimedia presentation for a class of presentations to which a specific multimedia presentation belongs, the model being a finite state automaton having states corresponding to segments of the presentation class, and having state transitions corresponding to expected event cues, each model thereby also specifying an expected time sequence of state transitions between event cues for the class of presentations to which it relates; and” (b) determining by a computer that transforming the representation of the multimedia presentation belongs to a particular multimedia presentation class based upon the results of matching observed event cues against the set of presentation models. 2. A method as in claim 1 wherein the expected event cues for a given presentation class further comprise a plurality of event cues of at least two different types. | 0.637168 |
8,005,665 | 35 | 36 | 35. A tangible computer readable medium having instructions stored thereon, the instructions configured to cause a computing device to perform operations comprising: receiving at least a verbosity score, a threshold score, and a sequence threshold score from a user input; accessing a memory to read at least a sequence of words from the document; extracting the sequence of words from the document based upon a determination that the sequence includes a number of words greater than or equal to the verbosity score and a number of words having a score greater than or equal to the threshold score is greater than or equal to the sequence threshold score; searching the abstract to determine whether the sequence of words is included in the abstract; and adding the sequence of words to the abstract in response to determining that the sequence was not included in the abstract. | 35. A tangible computer readable medium having instructions stored thereon, the instructions configured to cause a computing device to perform operations comprising: receiving at least a verbosity score, a threshold score, and a sequence threshold score from a user input; accessing a memory to read at least a sequence of words from the document; extracting the sequence of words from the document based upon a determination that the sequence includes a number of words greater than or equal to the verbosity score and a number of words having a score greater than or equal to the threshold score is greater than or equal to the sequence threshold score; searching the abstract to determine whether the sequence of words is included in the abstract; and adding the sequence of words to the abstract in response to determining that the sequence was not included in the abstract. 36. The tangible computer readable medium of claim 35 further comprising self-tuning the verbosity setting to the complexity of the document in response to not receiving a verbosity setting from an input device. | 0.541304 |
8,930,342 | 4 | 7 | 4. The process of claim 1 , wherein the process action of accessing a structured data repository to extract structured data that is available for the original user query comprises the actions of: identifying entities and properties that are either explicitly or implicitly present in the original user query; for each identified entity, querying the structured data repository to identify types of said entity that are possible, and for each identified type of said entity that is possible, querying the structured data repository to identify properties of said type that are possible; and for each identified property, querying the structured data repository to identify entities that could have said property. | 4. The process of claim 1 , wherein the process action of accessing a structured data repository to extract structured data that is available for the original user query comprises the actions of: identifying entities and properties that are either explicitly or implicitly present in the original user query; for each identified entity, querying the structured data repository to identify types of said entity that are possible, and for each identified type of said entity that is possible, querying the structured data repository to identify properties of said type that are possible; and for each identified property, querying the structured data repository to identify entities that could have said property. 7. The process of claim 4 , wherein whenever one or more properties are identified to be either explicitly or implicitly present in the original user query, the process action of providing the extracted structured data in the form of a hierarchical menu for use in generating a revised user query comprises the actions of: providing a first user-selectable menu of the identified properties; upon receiving a user selection of a property from the first user-selectable menu, providing a second user-selectable menu of the identified entities that could have the selected property; and upon receiving a user selection of an entity that could have the selected property from the second user-selectable menu, using the selected property and the selected entity that could have said property to generate the revised user query. | 0.604327 |
9,846,731 | 1 | 6 | 1. A method of matching a plurality of imported data entities to a plurality of existing data entities in a database comprising: receiving first input specifying a first matching criteria that is based at least in part on a first subset of one or more properties of the imported data entities, and specifying a first matching technique to use as part of the first matching criteria; receiving second input specifying a second matching criteria that is different from the first matching criteria and that is based at least in part on a second subset of the one or more properties of the imported data entities, wherein the second subset of the one or more properties is different than the first subset of one or more properties, and specifying a second matching technique that is different than the first matching technique and to use as part of the second matching criteria; receiving third input specifying a particular one of the imported data entities and signaling a request to resolve that particular one of the imported data entities in relation to the existing data entities; matching the particular one of the imported data entities to a first subset of the existing data entities using the first matching criteria and using the first matching technique; matching the particular one of the imported data entities to a second subset of the existing data entities using the second matching criteria and using the second matching technique; causing display of a first result of matching the particular one imported data entity to the first subset of the existing data entities and a second result of matching the particular one imported data entity to the second subset of the existing data entities; receiving, in response to the display, a selection of one or more of continuing resolving the particular one imported data entity, resolving others of the imported data entities, and consolidating the particular one imported data entity into the existing data entities, the consolidating comprising adding at least one value from the particular one imported data entity to one of the first subset of the existing data entities or one of the second subset of the existing data entities; performing further resolution or consolidation based on the selection, wherein the method is performed by one or more computing devices. | 1. A method of matching a plurality of imported data entities to a plurality of existing data entities in a database comprising: receiving first input specifying a first matching criteria that is based at least in part on a first subset of one or more properties of the imported data entities, and specifying a first matching technique to use as part of the first matching criteria; receiving second input specifying a second matching criteria that is different from the first matching criteria and that is based at least in part on a second subset of the one or more properties of the imported data entities, wherein the second subset of the one or more properties is different than the first subset of one or more properties, and specifying a second matching technique that is different than the first matching technique and to use as part of the second matching criteria; receiving third input specifying a particular one of the imported data entities and signaling a request to resolve that particular one of the imported data entities in relation to the existing data entities; matching the particular one of the imported data entities to a first subset of the existing data entities using the first matching criteria and using the first matching technique; matching the particular one of the imported data entities to a second subset of the existing data entities using the second matching criteria and using the second matching technique; causing display of a first result of matching the particular one imported data entity to the first subset of the existing data entities and a second result of matching the particular one imported data entity to the second subset of the existing data entities; receiving, in response to the display, a selection of one or more of continuing resolving the particular one imported data entity, resolving others of the imported data entities, and consolidating the particular one imported data entity into the existing data entities, the consolidating comprising adding at least one value from the particular one imported data entity to one of the first subset of the existing data entities or one of the second subset of the existing data entities; performing further resolution or consolidation based on the selection, wherein the method is performed by one or more computing devices. 6. The method of claim 1 , wherein the first subset and the second subset each have two or more properties. | 0.901654 |
7,523,137 | 7 | 8 | 7. The event analysis system of claim 2 , where the event detection engine is operable to: apply a filter to determine whether the event object specifies an entity in the environment model. | 7. The event analysis system of claim 2 , where the event detection engine is operable to: apply a filter to determine whether the event object specifies an entity in the environment model. 8. The event analysis system of claim 7 , where the event detection engine is further operable to: apply a classification algorithm to the event object to determine the event type represented in the event object. | 0.5 |
7,676,743 | 33 | 39 | 33. A method of fitting graphical objects within a plurality of separate graphical frames in a document, each frame being associated with at least one fitting attribute with a value for fitting one or more of the graphical objects in the frame, comprising: using an algorithm to automatically determine a common scaling factor for the value of the at least one fitting attribute in each of the separate frames; and applying the common scaling factor to scale at least one value in each frame of the plurality of separate graphical frames to fit one or more of the graphical objects in each of the frames, wherein said applying modifies the size of at least one graphical object in each of the plurality of separate graphical frames, wherein said applying is performed without modifying the size of the frames of said plurality of separate graphical frames, wherein at least one of the scaled values is different than another one of the scaled values. | 33. A method of fitting graphical objects within a plurality of separate graphical frames in a document, each frame being associated with at least one fitting attribute with a value for fitting one or more of the graphical objects in the frame, comprising: using an algorithm to automatically determine a common scaling factor for the value of the at least one fitting attribute in each of the separate frames; and applying the common scaling factor to scale at least one value in each frame of the plurality of separate graphical frames to fit one or more of the graphical objects in each of the frames, wherein said applying modifies the size of at least one graphical object in each of the plurality of separate graphical frames, wherein said applying is performed without modifying the size of the frames of said plurality of separate graphical frames, wherein at least one of the scaled values is different than another one of the scaled values. 39. The method of claim 33 , wherein the algorithm determines a best-individual-fit for the at least one value for each frame individually. | 0.691111 |
10,083,379 | 1 | 5 | 1. A method comprising, by one or more computing systems: receiving, from a plurality of client systems of a plurality of users, a plurality of search queries, each search query comprising one or more n-grams; identifying a subset of search queries from the plurality of search queries as being queries for visual-media items, each of the search queries in the subset of search queries being identified based on one or more n-grams of the search query being associated with visual-media content; calculating, for each of the n-grams of the search queries of the subset of search queries, a popularity-score based on a count of the search queries in the subset of search queries that include the n-gram, wherein, for each of one or more of the n-grams of the search queries of the subset of search queries, the count of the search queries including the n-gram is a weighted count that weights an occurrence of each search query based on a degree of confidence with which the search query is identified as being a query for visual-media items; determining one or more popular n-grams, wherein each of the popular n-grams is an n-gram of the search queries of the subset of search queries having a popularity-score greater than a threshold popularity-score; and selecting one or more of the popular n-grams for training a visual-concept recognition system, wherein each of the popular n-grams is selected based on whether it is associated with one or more visual concepts. | 1. A method comprising, by one or more computing systems: receiving, from a plurality of client systems of a plurality of users, a plurality of search queries, each search query comprising one or more n-grams; identifying a subset of search queries from the plurality of search queries as being queries for visual-media items, each of the search queries in the subset of search queries being identified based on one or more n-grams of the search query being associated with visual-media content; calculating, for each of the n-grams of the search queries of the subset of search queries, a popularity-score based on a count of the search queries in the subset of search queries that include the n-gram, wherein, for each of one or more of the n-grams of the search queries of the subset of search queries, the count of the search queries including the n-gram is a weighted count that weights an occurrence of each search query based on a degree of confidence with which the search query is identified as being a query for visual-media items; determining one or more popular n-grams, wherein each of the popular n-grams is an n-gram of the search queries of the subset of search queries having a popularity-score greater than a threshold popularity-score; and selecting one or more of the popular n-grams for training a visual-concept recognition system, wherein each of the popular n-grams is selected based on whether it is associated with one or more visual concepts. 5. The method of claim 1 , wherein each of one or more of the search queries in the subset of search queries is further identified based on whether it is a bounded search query that specifically filters for search results having visual-media content. | 0.860491 |
4,849,732 | 1 | 12 | 1. An input device operated by a single hand and used to transmit information between the operator of said device and an electronic apparatus in communication with said device, comprising: a housing; a first key array having a plurality of input means mounted to said housing and operable by the thumb of the hand; a second key array having a plurality of input means mounted to said housing, said second array disposed on an array axis which is aligned along a longitudinal axis of and operable by the index finger of the hand when the thumb of the hand is operably positioned proximal to said first array; a third key array having a plurality of input means mounted to said housing, said third array disposed on an array axis which is aligned along a longitudinal axis of and operable by the middle finger of the hand when the thumb and the first finger of the hand are operably positioned proximal to said first and second arrays, respectively; a fourth key array having a plurality of input means mounted to said housing, said fourth array disposed on an array axis which is aligned along a longitudinal axis of and operable by the fourth finger of the hand when the thumb and the first finger are operably positioned proximal to said first and second arrays, respectively; a fifth key array having a plurality of input means mounted to said housing, said fifth array disposed on an array axis which is aligned along a longitudinal axis of and operable by the fifth finger of the hand when the thumb and the first finger are operably positioned proximal to said first and second arrays; and label means disposed in close association with a corresponding key, laterally offset from said corresponding key and outwardly disposed from said key array axis, said label means being viewable while the fingers are in contact with said corresponding key, wherein said first, second, third, fourth and fifth key arrays are disposed to conform to the positions, motion and range of the respective fingers of the hand allowing activation of the keys without movement of the hand relative to the housing and without movement of said fingers to other of said key arrays, and each said key array includes an axis being non-parallel to the axis of other key arrays. | 1. An input device operated by a single hand and used to transmit information between the operator of said device and an electronic apparatus in communication with said device, comprising: a housing; a first key array having a plurality of input means mounted to said housing and operable by the thumb of the hand; a second key array having a plurality of input means mounted to said housing, said second array disposed on an array axis which is aligned along a longitudinal axis of and operable by the index finger of the hand when the thumb of the hand is operably positioned proximal to said first array; a third key array having a plurality of input means mounted to said housing, said third array disposed on an array axis which is aligned along a longitudinal axis of and operable by the middle finger of the hand when the thumb and the first finger of the hand are operably positioned proximal to said first and second arrays, respectively; a fourth key array having a plurality of input means mounted to said housing, said fourth array disposed on an array axis which is aligned along a longitudinal axis of and operable by the fourth finger of the hand when the thumb and the first finger are operably positioned proximal to said first and second arrays, respectively; a fifth key array having a plurality of input means mounted to said housing, said fifth array disposed on an array axis which is aligned along a longitudinal axis of and operable by the fifth finger of the hand when the thumb and the first finger are operably positioned proximal to said first and second arrays; and label means disposed in close association with a corresponding key, laterally offset from said corresponding key and outwardly disposed from said key array axis, said label means being viewable while the fingers are in contact with said corresponding key, wherein said first, second, third, fourth and fifth key arrays are disposed to conform to the positions, motion and range of the respective fingers of the hand allowing activation of the keys without movement of the hand relative to the housing and without movement of said fingers to other of said key arrays, and each said key array includes an axis being non-parallel to the axis of other key arrays. 12. The input device according to claim 1, wherein at least one of said arrays of a plurality of input means comprise character keys. | 0.739216 |
9,391,947 | 14 | 20 | 14. A system comprising: one or more processors; and a memory, the memory storing instructions, which when executed cause one or more processors to: determine a habitual activity of a first user; determine a first context of the habitual activity; identify a time period when the first user is available for an interaction based on the habitual activity and the first context of the habitual activity; categorize consumption of information by the first user as being on a type of communication channel, the type of communication channel including a push-based communication channel, a queue-based communication channel and a pull-based communication channel; identify a second context of a message; determine whether the second context of the message corresponds to the first context of the habitual activity; and provide the message to the first user on a communication channel suitable for delivery of the message and in the time period when the first user is available for the interaction based on the second context of the message corresponding to the first context of the habitual activity. | 14. A system comprising: one or more processors; and a memory, the memory storing instructions, which when executed cause one or more processors to: determine a habitual activity of a first user; determine a first context of the habitual activity; identify a time period when the first user is available for an interaction based on the habitual activity and the first context of the habitual activity; categorize consumption of information by the first user as being on a type of communication channel, the type of communication channel including a push-based communication channel, a queue-based communication channel and a pull-based communication channel; identify a second context of a message; determine whether the second context of the message corresponds to the first context of the habitual activity; and provide the message to the first user on a communication channel suitable for delivery of the message and in the time period when the first user is available for the interaction based on the second context of the message corresponding to the first context of the habitual activity. 20. The system of claim 14 , wherein the instructions further cause the one or more processors to determine a real-time context of the first user and providing the message to the first user based on the real-time context. | 0.650316 |
7,984,371 | 4 | 6 | 4. The method of claim 1 , further comprising displaying a graphical rendering of one or more of said expression hierarchies concurrently within a view, the graphical rendering including text, shapes, and lines, the text including the contents of the formulas represented, by the nodes, the shapes representing the nodes, and the lines representing the edges connecting the nodes within said expression hierarchies. | 4. The method of claim 1 , further comprising displaying a graphical rendering of one or more of said expression hierarchies concurrently within a view, the graphical rendering including text, shapes, and lines, the text including the contents of the formulas represented, by the nodes, the shapes representing the nodes, and the lines representing the edges connecting the nodes within said expression hierarchies. 6. The method of claim 4 , wherein said nodes are graphical rendered using separate physical properties including shape and color to denote different types or values of said operators or operands they represent. | 0.5 |
7,584,457 | 8 | 9 | 8. The apparatus according to claim 7 , further comprising: means for generating a compiler language representation of the generated script code section, the compiler language representation of the generated script code section comprising a second interface and a second class. | 8. The apparatus according to claim 7 , further comprising: means for generating a compiler language representation of the generated script code section, the compiler language representation of the generated script code section comprising a second interface and a second class. 9. The apparatus according to claim 8 , wherein the means for performing usage and semantic checks performs usage and semantic checks on the generated script code section by compiling the compiler language representation of the generated script code section, including the generated second interface and the generated second class. | 0.5 |
7,965,405 | 1 | 2 | 1. An image forming apparatus comprising: a storing section that has a common storage area, the common storage area having a plurality of areas that are coexisting in the common storage area in accordance with a threshold value and are used to generate and store a plurality of pieces of data that have different formats based on electronic data; a language format discriminating section to discriminate a description language format of the electronic data; and a control section to change the threshold value based on the description language format discriminated by the language format discriminating section. | 1. An image forming apparatus comprising: a storing section that has a common storage area, the common storage area having a plurality of areas that are coexisting in the common storage area in accordance with a threshold value and are used to generate and store a plurality of pieces of data that have different formats based on electronic data; a language format discriminating section to discriminate a description language format of the electronic data; and a control section to change the threshold value based on the description language format discriminated by the language format discriminating section. 2. The image forming apparatus of claim 1 , wherein the control section changes the threshold value in a case where it is determined that the description language format has a transparency function, based on the description language format discriminated by the language format discriminating section. | 0.870242 |
8,069,410 | 1 | 2 | 1. A process for retrieving and viewing partial content of a server stored document on a mobile communication device, comprising: extracting informational entities from said document within said server; populating a model of said document within said server with elements corresponding to said informational entities; detecting navigational entities within said informational entities and in response storing within said server source and target destinations associated with said navigational entities; assigning an identifier to each of said source and target destinations within said model; paginating said model within said server into a plurality of segments identified by respective index values, comprising updating each said identifier with an attribute containing a corresponding one of said index values; generating output data for delivery to said mobile communication device by traversing through said elements in said model and recording each element as an equivalent command containing content and document characteristics; sending a first request from the mobile communication device to the server to display said document; in response to receiving said first request transmitting a first segment of said output data from said server to said mobile communication device; parsing said output data within said mobile communication device and executing each said equivalent command to thereby display said content of said first segment of the document according to said document characteristics comprising any of said navigational entities contained within said first segment; in response to user selection of a navigational entity displayed on said mobile communication device sending a further request to said server containing the identifier and index value corresponding to said navigational entity; in response to receiving said further request transmitting a further segment of said output data from said server to said mobile communication device from a location in said model corresponding to said index value; parsing said further segment of output data within said mobile communication device and executing each said equivalent command to thereby display said content of said further segment of the document according to said document characteristics; detecting within said mobile communication device any skipped content between said first and further segment and providing a visual indication of said skipped content on said mobile communication device, wherein said visual indication of said skipped content includes a horizontal bar indicator between said first and further segment displayed on said mobile communication device; and; calculating and displaying size of said skipped content within said horizontal bar indicator. | 1. A process for retrieving and viewing partial content of a server stored document on a mobile communication device, comprising: extracting informational entities from said document within said server; populating a model of said document within said server with elements corresponding to said informational entities; detecting navigational entities within said informational entities and in response storing within said server source and target destinations associated with said navigational entities; assigning an identifier to each of said source and target destinations within said model; paginating said model within said server into a plurality of segments identified by respective index values, comprising updating each said identifier with an attribute containing a corresponding one of said index values; generating output data for delivery to said mobile communication device by traversing through said elements in said model and recording each element as an equivalent command containing content and document characteristics; sending a first request from the mobile communication device to the server to display said document; in response to receiving said first request transmitting a first segment of said output data from said server to said mobile communication device; parsing said output data within said mobile communication device and executing each said equivalent command to thereby display said content of said first segment of the document according to said document characteristics comprising any of said navigational entities contained within said first segment; in response to user selection of a navigational entity displayed on said mobile communication device sending a further request to said server containing the identifier and index value corresponding to said navigational entity; in response to receiving said further request transmitting a further segment of said output data from said server to said mobile communication device from a location in said model corresponding to said index value; parsing said further segment of output data within said mobile communication device and executing each said equivalent command to thereby display said content of said further segment of the document according to said document characteristics; detecting within said mobile communication device any skipped content between said first and further segment and providing a visual indication of said skipped content on said mobile communication device, wherein said visual indication of said skipped content includes a horizontal bar indicator between said first and further segment displayed on said mobile communication device; and; calculating and displaying size of said skipped content within said horizontal bar indicator. 2. The process of claim 1 , wherein said extracting further includes parsing said document using a document distiller. | 0.69898 |
8,004,728 | 13 | 15 | 13. An image scanning device, comprising: a scanning unit that scans an original document with a scanning condition to produce image data; a user setting unit that receives the scanning condition set by a user, the scanning condition being used by the scanning unit for scanning the original document; a storage unit that stores a specific condition used by the scanning unit for scanning a specific document, the specific condition including a limited requirement required by the specific document, and a limited scanning condition conforming to the limited requirement; a first determination unit that determines whether the scanning condition satisfies the limited requirement for the specific document; a control unit that causes the scanning unit to scan the original document with the scanning condition if the first determination unit determines that the scanning condition satisfies the limited requirement for the specific document, the control unit causing the scanning unit to scan the original document with an initial condition to produce initial image data, if the first determination unit determines that the scanning condition does not satisfy the limited requirement for the specific document; and a second determination unit that determines, based on the initial image data, whether the original document is the specific document; wherein the control unit causes the scanning unit to scan the original document with the scanning condition, if the second determination unit determines that the original document is not the specific document; and the control unit reads the specific condition from the first storage unit and then causes the scanning unit to scan the original document with the limited scanning condition if the second determination unit determines that the original document is the specific document. | 13. An image scanning device, comprising: a scanning unit that scans an original document with a scanning condition to produce image data; a user setting unit that receives the scanning condition set by a user, the scanning condition being used by the scanning unit for scanning the original document; a storage unit that stores a specific condition used by the scanning unit for scanning a specific document, the specific condition including a limited requirement required by the specific document, and a limited scanning condition conforming to the limited requirement; a first determination unit that determines whether the scanning condition satisfies the limited requirement for the specific document; a control unit that causes the scanning unit to scan the original document with the scanning condition if the first determination unit determines that the scanning condition satisfies the limited requirement for the specific document, the control unit causing the scanning unit to scan the original document with an initial condition to produce initial image data, if the first determination unit determines that the scanning condition does not satisfy the limited requirement for the specific document; and a second determination unit that determines, based on the initial image data, whether the original document is the specific document; wherein the control unit causes the scanning unit to scan the original document with the scanning condition, if the second determination unit determines that the original document is not the specific document; and the control unit reads the specific condition from the first storage unit and then causes the scanning unit to scan the original document with the limited scanning condition if the second determination unit determines that the original document is the specific document. 15. The image scanning device according to claim 13 , wherein the second determination unit determines whether the initial image data includes natural image related to the specific document, and the second determination unit determines that the original document is the specific document if the second determination unit determines that the initial image data includes the natural image. | 0.512594 |
7,716,219 | 11 | 16 | 11. A database search system comprising: a storage element storing keywords entered by at least one user for a plurality of search terms and information related to converted transactions associated with a plurality of searches, the plurality of searches having been performed on the keywords; and a processing system coupled to the storage element, the processing system operative to perform steps comprising: estimating a general transaction probability; estimating unigram keyword probabilities; determining conditional probability values associated with the keywords based on the converted transactions; estimating keyword transaction probabilities based on the general transaction probability, the unigram keyword probabilities, and the conditional probability values; and generating expected transaction values based on the keyword transaction probabilities, wherein the expected transaction values are generated according to: E ( T ❘ k , S ) = P ( T ❘ k , S ) * ∑ ∀ t R ( t ❘ k , S ) C ( t ❘ k , S ) , where C(t|k,S) is a non-zero value. | 11. A database search system comprising: a storage element storing keywords entered by at least one user for a plurality of search terms and information related to converted transactions associated with a plurality of searches, the plurality of searches having been performed on the keywords; and a processing system coupled to the storage element, the processing system operative to perform steps comprising: estimating a general transaction probability; estimating unigram keyword probabilities; determining conditional probability values associated with the keywords based on the converted transactions; estimating keyword transaction probabilities based on the general transaction probability, the unigram keyword probabilities, and the conditional probability values; and generating expected transaction values based on the keyword transaction probabilities, wherein the expected transaction values are generated according to: E ( T ❘ k , S ) = P ( T ❘ k , S ) * ∑ ∀ t R ( t ❘ k , S ) C ( t ❘ k , S ) , where C(t|k,S) is a non-zero value. 16. The database search system of claim 11 , wherein the processing system is further operative to perform a step of estimating return on investment (ROI) values for the keywords based on the expected transaction values. | 0.621993 |
9,002,810 | 2 | 4 | 2. The method of claim 1 wherein versioning information of a vNode comprises at least one of a start date corresponding to a check-in date of a version of the structured document in which the vNode is first detected, and an end date corresponding to a check-in date of another version of the structured document in which the vNode no longer exists in the structured document. | 2. The method of claim 1 wherein versioning information of a vNode comprises at least one of a start date corresponding to a check-in date of a version of the structured document in which the vNode is first detected, and an end date corresponding to a check-in date of another version of the structured document in which the vNode no longer exists in the structured document. 4. The method of claim 2 wherein the versioned function is a “document-at-date-range” function and the at least one argument of the versioned function is a “range-start-date” argument that specifies a first date and a “range-end-date” argument that specifies a second date, and wherein the identified version of the structured document is a version that at least one of exists on the first date and is checked-in on a date between the first date and the second date, and that includes an object represented by a vNode satisfying the query. | 0.5 |
8,332,777 | 25 | 27 | 25. A method, comprising: displaying a user interface on a display device, wherein the user interface includes one or more selections; activating one of the one or more selections; and displaying a data entry method, wherein the data entry method is context and language specific to the activated selection by displaying one or more virtual keys for a user to enter data required by the activated selection, wherein the activated selection requires the user to enter data into a plurality of simultaneously displayed data entry boxes, of which at least one data entry box requires alphabetic input and at least one data entry box requires numerical data, wherein a virtual alphabetic keyboard is displayed in the data entry method on the display device when alphabetic user input is required by the activated selection in the data entry box requiring alphabetic input, and a virtual numeric keypad is displayed in the data entry method on the display device when numeric user input is required by the activated selection in the data entry box requiring numeric input. | 25. A method, comprising: displaying a user interface on a display device, wherein the user interface includes one or more selections; activating one of the one or more selections; and displaying a data entry method, wherein the data entry method is context and language specific to the activated selection by displaying one or more virtual keys for a user to enter data required by the activated selection, wherein the activated selection requires the user to enter data into a plurality of simultaneously displayed data entry boxes, of which at least one data entry box requires alphabetic input and at least one data entry box requires numerical data, wherein a virtual alphabetic keyboard is displayed in the data entry method on the display device when alphabetic user input is required by the activated selection in the data entry box requiring alphabetic input, and a virtual numeric keypad is displayed in the data entry method on the display device when numeric user input is required by the activated selection in the data entry box requiring numeric input. 27. The method of claim 25 , wherein the display device is a mobile computing device. | 0.724026 |
8,640,026 | 15 | 17 | 15. A word correction system, comprising: a multi-touch device comprising a user interface, wherein the multi-touch device is configured to receive touch input from a user to interact with the user interface; and a word correction engine, configured to: detect a selection by the user of a word displayed in the user interface; break the word into logical segments, wherein at least one of the logical segments comprises a plurality of characters; present the logical segments in the user interface; detect a user-selected segment of one of the logical segments; display at least one alternative segment for the user-selected segment in the user interface; and alter the selected segment in response to receiving a user-selected replacement from the at least one alternative segment. | 15. A word correction system, comprising: a multi-touch device comprising a user interface, wherein the multi-touch device is configured to receive touch input from a user to interact with the user interface; and a word correction engine, configured to: detect a selection by the user of a word displayed in the user interface; break the word into logical segments, wherein at least one of the logical segments comprises a plurality of characters; present the logical segments in the user interface; detect a user-selected segment of one of the logical segments; display at least one alternative segment for the user-selected segment in the user interface; and alter the selected segment in response to receiving a user-selected replacement from the at least one alternative segment. 17. The system of claim 15 , wherein the word correction engine is further configured to: determine a plurality of alternative segments for the user-selected segment, wherein each alternative segment comprises at least one letter difference than the user-selected segment; and display the plurality of alternative segments in the user interface. | 0.57196 |
8,694,539 | 2 | 3 | 2. The method according to claim 1 , wherein the dimension is an ordered dimension, and each of the dimension members represent a portion of a continuous measurement. | 2. The method according to claim 1 , wherein the dimension is an ordered dimension, and each of the dimension members represent a portion of a continuous measurement. 3. The method according to claim 2 , wherein the ordered dimension is a time dimension with a member having a start time and an end time. | 0.5 |
7,496,497 | 5 | 6 | 5. A system to allow a user to select a web site home page in a desired language comprising: a processor in communication with a memory, said processor operable to execute code for: identifying within a web address request to said web site a directional information item by extracting from said request a site language cookie stored in said users access device; providing a web page associated with said web address to a second web site corresponding to said directional information item, wherein said second web site includes a language translator; translating information on said web page in accordance with said language translator; and returning said translated web page to said user. | 5. A system to allow a user to select a web site home page in a desired language comprising: a processor in communication with a memory, said processor operable to execute code for: identifying within a web address request to said web site a directional information item by extracting from said request a site language cookie stored in said users access device; providing a web page associated with said web address to a second web site corresponding to said directional information item, wherein said second web site includes a language translator; translating information on said web page in accordance with said language translator; and returning said translated web page to said user. 6. The system as recited in claim 5 , wherein said processor is further operable to execute code for: accessing a control table to determine a status of said web page; and accessing a version of said web page stored locally on said second site, when said status indicates said web page is locally stored and valid; otherwise obtaining a current version of said web page; and translating said obtained web page. | 0.5 |
9,514,216 | 11 | 15 | 11. An apparatus comprising: a memory having stored therein one or more digital signals to represent at least one file for a particular displayable web page to comprise at least two of a plurality of segmented portions; at least one processing unit coupled to the memory and programmed with instructions to: access the plurality of segmented portions of the at least one displayable web page, and use one or more machine learned models to: identify one or more feature properties of the plurality of segmented portions within the one or more files, or otherwise to be inferable from the one or more files, classify the at least two of the plurality of segmented portions as at least one of a plurality of segment types to be based, at least in part, on the one or more feature properties to be identified, the one or more feature properties to be identified are to comprise at least language feature properties of language model of content to be displayed in one or more of the at least two of the plurality of segmented portions, and determine content quality scores for at least two of the plurality of segmented portions of at least the particular displayable web page; and establish an index in the memory, the index to be established for the plurality of segmented portions and to be based, at least in part, on the segment type, the index to indicate the content quality scores. | 11. An apparatus comprising: a memory having stored therein one or more digital signals to represent at least one file for a particular displayable web page to comprise at least two of a plurality of segmented portions; at least one processing unit coupled to the memory and programmed with instructions to: access the plurality of segmented portions of the at least one displayable web page, and use one or more machine learned models to: identify one or more feature properties of the plurality of segmented portions within the one or more files, or otherwise to be inferable from the one or more files, classify the at least two of the plurality of segmented portions as at least one of a plurality of segment types to be based, at least in part, on the one or more feature properties to be identified, the one or more feature properties to be identified are to comprise at least language feature properties of language model of content to be displayed in one or more of the at least two of the plurality of segmented portions, and determine content quality scores for at least two of the plurality of segmented portions of at least the particular displayable web page; and establish an index in the memory, the index to be established for the plurality of segmented portions and to be based, at least in part, on the segment type, the index to indicate the content quality scores. 15. The apparatus as recited in claim 11 , wherein the at least one processing unit is to be programmed with instructions to identify the plurality of segmented portions to be based, at least in part, on an initial set of properties to be identifiable in the at least one file. | 0.696937 |
8,004,392 | 11 | 12 | 11. A voice acquisition system for a vehicle, said voice acquisition system comprising: an interior rearview mirror assembly attached at an inner portion of the windshield of a vehicle equipped with said interior rearview mirror assembly; wherein said interior rearview mirror assembly includes at least one microphone for receiving audio signals within a cabin of the vehicle and generating an output indicative of said audio signals; a control in the vehicle, said control responsive to said output from said at least one microphone, said control at least partially distinguishing vocal signals from non-vocal signals present in said output; wherein said at least one microphone provides sound capture for (a) a wireless communication system and (b) at least one accessory present in the equipped vehicle; wherein said at least one accessory is controlled responsive to a voice command captured by said at least one microphone; and wherein said wireless communication system wirelessly communicates between the vehicle and a service provider located external and remote from the equipped vehicle. | 11. A voice acquisition system for a vehicle, said voice acquisition system comprising: an interior rearview mirror assembly attached at an inner portion of the windshield of a vehicle equipped with said interior rearview mirror assembly; wherein said interior rearview mirror assembly includes at least one microphone for receiving audio signals within a cabin of the vehicle and generating an output indicative of said audio signals; a control in the vehicle, said control responsive to said output from said at least one microphone, said control at least partially distinguishing vocal signals from non-vocal signals present in said output; wherein said at least one microphone provides sound capture for (a) a wireless communication system and (b) at least one accessory present in the equipped vehicle; wherein said at least one accessory is controlled responsive to a voice command captured by said at least one microphone; and wherein said wireless communication system wirelessly communicates between the vehicle and a service provider located external and remote from the equipped vehicle. 12. The voice acquisition system of claim 11 , wherein said at least one accessory is selected from the group consisting of a radio, an alarm system, a cruise control, a window, a phone, a recorder, a windshield wiper and a rain sensor. | 0.825185 |
9,842,308 | 2 | 4 | 2. The method of claim 1 further comprising: constructing, by said processor-based system for said user, at least one additional shipping processing rule based on preferences of another user. | 2. The method of claim 1 further comprising: constructing, by said processor-based system for said user, at least one additional shipping processing rule based on preferences of another user. 4. The method of claim 2 further comprising: selecting said at least one additional shipping processing rule constructed based on said preferences of said another user in said set of shipping processing rules for generating postage indicia for said user. | 0.52963 |
9,501,264 | 1 | 7 | 1. A system, including a mobile device, including a processor and memory maintaining instructions, the instructions being interpretable by the processor to present display elements having a first human-language meaning to a user of the mobile device; a development device, including a development environment suitable to create an app by a designer or programmer, the app including at least some of the instructions, and suitable to distribute the app to the mobile device, the app including at least some of the instructions interpretable by the processor to present the display elements in a form having a second human-language meaning to the user; the mobile device including a communication link responsive to one or more signals delivering the app to the mobile device, the communication link being responsive to the user and suitable to present messages regarding the second human-language meaning from the user to the designer or programmer, the messages including a relation between the second human-language meaning and the first human-language meaning; the app including communication link being responsive to the user to send information to the developer or programmer; the app including a first mode in which it performs a first designated function; instructions executable or interpretable by the processor to receive a signal from the user when performing the first designated function, the signal directing the app to enter a state in which it performs a second designated function; the second designated function including a user interface in which the app receives input from the user and communicates that input to the developer or programmer. | 1. A system, including a mobile device, including a processor and memory maintaining instructions, the instructions being interpretable by the processor to present display elements having a first human-language meaning to a user of the mobile device; a development device, including a development environment suitable to create an app by a designer or programmer, the app including at least some of the instructions, and suitable to distribute the app to the mobile device, the app including at least some of the instructions interpretable by the processor to present the display elements in a form having a second human-language meaning to the user; the mobile device including a communication link responsive to one or more signals delivering the app to the mobile device, the communication link being responsive to the user and suitable to present messages regarding the second human-language meaning from the user to the designer or programmer, the messages including a relation between the second human-language meaning and the first human-language meaning; the app including communication link being responsive to the user to send information to the developer or programmer; the app including a first mode in which it performs a first designated function; instructions executable or interpretable by the processor to receive a signal from the user when performing the first designated function, the signal directing the app to enter a state in which it performs a second designated function; the second designated function including a user interface in which the app receives input from the user and communicates that input to the developer or programmer. 7. A system as in claim 1 , wherein the display elements include one or more of: text, drawings, photographs, animation, video images. | 0.870155 |
4,802,223 | 1 | 2 | 1. A speech encoding apparatus comprising: input means for receiving speech including one or more words of human language; analysis means connected to said input means for analyzing said received speech, generating a sequence of phonological linguistic unit indicia corresponding to said received speech, grouping said phonological linguistic unit indicia into syllables, and generating pitch track data corresponding to said received speech: pitch pattern memory means storing a plurality of predetermined pitch patterns; pitch pattern recognizer means connected to said analysis means and to said pitch pattern memory means for selecting a pitch pattern from said plurality of predetermined pitch patterns for each syllable grouping of phonological linguistic unit indicia as generated by said analysis means, said pitch pattern being selected in dependence upon said pitch track data corresponding to each syllable grouping of phonological linguistic unit indicia; and transmission means connected to said analysis means and said pitch pattern recognizer means for transmitting said phonological linguistic unit indicia and pitch pattern indicia corresponding to said selected pitch patterns. | 1. A speech encoding apparatus comprising: input means for receiving speech including one or more words of human language; analysis means connected to said input means for analyzing said received speech, generating a sequence of phonological linguistic unit indicia corresponding to said received speech, grouping said phonological linguistic unit indicia into syllables, and generating pitch track data corresponding to said received speech: pitch pattern memory means storing a plurality of predetermined pitch patterns; pitch pattern recognizer means connected to said analysis means and to said pitch pattern memory means for selecting a pitch pattern from said plurality of predetermined pitch patterns for each syllable grouping of phonological linguistic unit indicia as generated by said analysis means, said pitch pattern being selected in dependence upon said pitch track data corresponding to each syllable grouping of phonological linguistic unit indicia; and transmission means connected to said analysis means and said pitch pattern recognizer means for transmitting said phonological linguistic unit indicia and pitch pattern indicia corresponding to said selected pitch patterns. 2. A speech encoding apparatus as claimed in claim 1, wherein: said analysis means generated phonological linguistic unit indicia corresponding to phonemes of said received speech. | 0.86627 |
9,922,117 | 1 | 10 | 1. A system for providing a contextual search tool that improves search results presented to a user based on advisor input, the system comprising: one or more memory devices; and one or more processing devices operatively coupled to the one or more memory devices, wherein the processing device is configured to execute computer-readable program code to: receive a search from the user through a contextual search interface, wherein the search is received through a user computer system; determine search results and dynamic contextual information based on the search from the user, wherein the dynamic contextual information comprises one or more dynamic contextual questions; display the search results in a search results section, content in a content section for at least one of the search results from the search results section, and the dynamic contextual information in a dynamic contextual information section of the contextual search interface, wherein the search results section, the content section, and the dynamic contextual information section are different sections, wherein the contextual search interface is displayed through the user computer system; determine a notification request for a communication with an advisor type based at least on the search from the user; display the notification request to the user, wherein the notification request is displayed through the user computer system; receive an indication from the user to communicate with the advisor type, wherein the indication is received through the user computer system; initiate a communication between the user and an advisor based on the indication from the user to communicate with the advisor type, wherein the communication is initiated through the user computer system and an advisor system; display the contextual search interface of the user to the advisor by sharing the contextual search interface from the user computer system with the advisor system; receive contextual input from the advisor for the search, wherein the contextual input from the advisor is received through the contextual search interface of the user displayed to the advisor on the advisor system; receive contextual input from the user for the search, wherein the contextual input from the user is received through the user computer system; determine updated search results, updated content, and updated dynamic contextual information based on the contextual input from the advisor and the contextual input from the user, wherein the updated dynamic contextual information comprises one or more updated dynamic contextual questions; and display the updated search results in the search results section, the updated content for at least one of the updated search results in the content section, and the updated dynamic contextual information in the dynamic contextual information section of the contextual search interface on both the user computer system and the advisor system; wherein the updated dynamic contextual information changes based on changes to the search, the contextual input from the advisor, and the contextual input from the user, and wherein the contextual search interface improves accuracy and efficiency of displaying the search results and updated search results to the user. | 1. A system for providing a contextual search tool that improves search results presented to a user based on advisor input, the system comprising: one or more memory devices; and one or more processing devices operatively coupled to the one or more memory devices, wherein the processing device is configured to execute computer-readable program code to: receive a search from the user through a contextual search interface, wherein the search is received through a user computer system; determine search results and dynamic contextual information based on the search from the user, wherein the dynamic contextual information comprises one or more dynamic contextual questions; display the search results in a search results section, content in a content section for at least one of the search results from the search results section, and the dynamic contextual information in a dynamic contextual information section of the contextual search interface, wherein the search results section, the content section, and the dynamic contextual information section are different sections, wherein the contextual search interface is displayed through the user computer system; determine a notification request for a communication with an advisor type based at least on the search from the user; display the notification request to the user, wherein the notification request is displayed through the user computer system; receive an indication from the user to communicate with the advisor type, wherein the indication is received through the user computer system; initiate a communication between the user and an advisor based on the indication from the user to communicate with the advisor type, wherein the communication is initiated through the user computer system and an advisor system; display the contextual search interface of the user to the advisor by sharing the contextual search interface from the user computer system with the advisor system; receive contextual input from the advisor for the search, wherein the contextual input from the advisor is received through the contextual search interface of the user displayed to the advisor on the advisor system; receive contextual input from the user for the search, wherein the contextual input from the user is received through the user computer system; determine updated search results, updated content, and updated dynamic contextual information based on the contextual input from the advisor and the contextual input from the user, wherein the updated dynamic contextual information comprises one or more updated dynamic contextual questions; and display the updated search results in the search results section, the updated content for at least one of the updated search results in the content section, and the updated dynamic contextual information in the dynamic contextual information section of the contextual search interface on both the user computer system and the advisor system; wherein the updated dynamic contextual information changes based on changes to the search, the contextual input from the advisor, and the contextual input from the user, and wherein the contextual search interface improves accuracy and efficiency of displaying the search results and updated search results to the user. 10. The system of claim 1 , wherein receiving contextual input from the advisor for the search comprises dragging and dropping content into the search results section or the content section of the contextual search interface; or dragging and dropping a dynamic contextual question into the dynamic contextual information section. | 0.647752 |
7,698,351 | 1 | 20 | 1. A system comprising: a namespace and storage management server having an integrated management framework executing program instructions for facilitating configuration of and management of pathnames in a logical namespace, and creating a layer of abstraction that presents to a client the logical namespace that is accessible via a particular storage access protocol, and extracting logical views and pathnames from the namespaces exported by heterogeneous services, and configuring the pathnames so that they are accessible in the logical namespace via the storage access protocols; a namespace and storage management console having a computer screen; and a namespace and storage management application executing on the management console, the namespace and storage management application configured to initiate performance of commands directed to managed objects including facilitating configuration and management of pathnames in a logical namespace, and configured to spawn a graphical user interface thread for use by a GUI toolkit, the GUI toolkit configured to produce reusable GUI components, the GUI components including a navigation frame having a plurality of navigation panels simultaneously displayed on the computer screen, the navigation panels including a hierarchy panel, an operations panel, a view panel and a display panel to allow a user to manage various said pathnames exported by heterogeneous namespace services and protocol implementations within the logical namespace, said GUI toolkit supporting reusable templates that facilitate reuse of the GUI components within one of the management application and other applications. | 1. A system comprising: a namespace and storage management server having an integrated management framework executing program instructions for facilitating configuration of and management of pathnames in a logical namespace, and creating a layer of abstraction that presents to a client the logical namespace that is accessible via a particular storage access protocol, and extracting logical views and pathnames from the namespaces exported by heterogeneous services, and configuring the pathnames so that they are accessible in the logical namespace via the storage access protocols; a namespace and storage management console having a computer screen; and a namespace and storage management application executing on the management console, the namespace and storage management application configured to initiate performance of commands directed to managed objects including facilitating configuration and management of pathnames in a logical namespace, and configured to spawn a graphical user interface thread for use by a GUI toolkit, the GUI toolkit configured to produce reusable GUI components, the GUI components including a navigation frame having a plurality of navigation panels simultaneously displayed on the computer screen, the navigation panels including a hierarchy panel, an operations panel, a view panel and a display panel to allow a user to manage various said pathnames exported by heterogeneous namespace services and protocol implementations within the logical namespace, said GUI toolkit supporting reusable templates that facilitate reuse of the GUI components within one of the management application and other applications. 20. The system of claim 1 wherein said GUI toolkit further comprises one or more wizard pages configured to collect information including at least one of a name of a machine or server, a type of machine or server, a share name of a share to be created, a directory where a share resides, and host agent information. | 0.524169 |
7,664,734 | 8 | 9 | 8. The method of claim 5 , wherein identifying the plurality of user-context attributes further comprises generating a term measure based on at least a first frequency that the extracted term occurs in at least one of the one or more words and an index of content. | 8. The method of claim 5 , wherein identifying the plurality of user-context attributes further comprises generating a term measure based on at least a first frequency that the extracted term occurs in at least one of the one or more words and an index of content. 9. The method of claim 8 , wherein generating the plurality of implicit search queries comprising terms further comprises generating a plurality of implicit search queries comprising terms selected responsive at least in part to the term measure. | 0.5 |
8,725,518 | 1 | 10 | 1. A system for providing quality management related to an accent of a call responder handling a call in a contact center, comprising: a statistical model database with statistical accent models, each statistical accent model associated with an accent, based on accent related details from collections of speech instances that are further normalized relative to differences therebetween for accent conformity, and with a model accent score representing the conformity of the statistical accent model to the associated accent, and created from speech data; a recording system for recordings a speech sample of a call responder having a call responder accent; a speech analysis system for receiving said speech sample; associating a score with the call responder accent by analyzing said speech sample relative to the statistical accent models in said statistical model database, and indicating a specific model of the statistical accent models to which the speech sample is closest, and automatically amending in said speech sample by replacement waveforms, sections determined as having known errors, whereby the amended speech sample replaces said speech sample to conform to the specific accent model; and providing during the call conducted by the call responder an immediate visual feedback indicating the level of deviation of the agent from the required accent. | 1. A system for providing quality management related to an accent of a call responder handling a call in a contact center, comprising: a statistical model database with statistical accent models, each statistical accent model associated with an accent, based on accent related details from collections of speech instances that are further normalized relative to differences therebetween for accent conformity, and with a model accent score representing the conformity of the statistical accent model to the associated accent, and created from speech data; a recording system for recordings a speech sample of a call responder having a call responder accent; a speech analysis system for receiving said speech sample; associating a score with the call responder accent by analyzing said speech sample relative to the statistical accent models in said statistical model database, and indicating a specific model of the statistical accent models to which the speech sample is closest, and automatically amending in said speech sample by replacement waveforms, sections determined as having known errors, whereby the amended speech sample replaces said speech sample to conform to the specific accent model; and providing during the call conducted by the call responder an immediate visual feedback indicating the level of deviation of the agent from the required accent. 10. The system according to claim 1 , further comprising assigning the call responder with an accent score corresponding to the model accent score associated with the specific model. | 0.725076 |
7,966,280 | 11 | 13 | 11. A method for controlling an automotive air conditioner, said air conditioner comprising an air-conditioning unit for supplying conditioned air into a vehicle, an information acquiring unit for acquiring state information indicating a state related to said vehicle, a storage unit, a control information correcting unit for having at least one probabilistic model associated with a specific setting operation, calculating the probability of said specific operation by entering said state information into said probabilistic model, and correcting setting information or control information related to the setting operation of a vehicle occupant in accordance with said calculated probability so as to achieve said specific setting operation, and an air-conditioning control unit for controlling said air-conditioning unit in accordance with said corrected setting information or control information, the method comprising: storing said state information as learned information in said storage unit; selecting a plurality of learned data from said learned data stored in said storage unit; classifying said plurality of learned data stored in said storage unit into at least a first cluster and a second cluster, and determining a first range for a value of said state information from the learned data included in said first cluster and a second range for the value of said state information from the learned data included in said second cluster; and constructing said probabilistic model associated with said specific setting operation by determining the probability of occurrence of said state information contained in said first range and the probability of occurrence of said state information contained in said second range. | 11. A method for controlling an automotive air conditioner, said air conditioner comprising an air-conditioning unit for supplying conditioned air into a vehicle, an information acquiring unit for acquiring state information indicating a state related to said vehicle, a storage unit, a control information correcting unit for having at least one probabilistic model associated with a specific setting operation, calculating the probability of said specific operation by entering said state information into said probabilistic model, and correcting setting information or control information related to the setting operation of a vehicle occupant in accordance with said calculated probability so as to achieve said specific setting operation, and an air-conditioning control unit for controlling said air-conditioning unit in accordance with said corrected setting information or control information, the method comprising: storing said state information as learned information in said storage unit; selecting a plurality of learned data from said learned data stored in said storage unit; classifying said plurality of learned data stored in said storage unit into at least a first cluster and a second cluster, and determining a first range for a value of said state information from the learned data included in said first cluster and a second range for the value of said state information from the learned data included in said second cluster; and constructing said probabilistic model associated with said specific setting operation by determining the probability of occurrence of said state information contained in said first range and the probability of occurrence of said state information contained in said second range. 13. The method according to claim 11 , wherein when the number of times that said specific setting operation has been performed reaches a predetermined number of times, said selecting a plurality of learned data selects said plurality of learned data related to said specific setting operation. | 0.73703 |
8,046,350 | 1 | 8 | 1. A method performed by one or more server devices, the method comprising: receiving, at one or more processors of the one or more server devices, a query, from a client device, that includes one or more terms; determining, by one or more processors of the one or more server devices, whether the query is a commercial query by: determining whether the one or more terms of the query, in any particular order, matches a commercial query pattern in a list of commercial query patterns, where the list of commercial query patterns includes patterns associated with one or more host names or domain names that include more than a particular number of hyphens, and identifying the query as a commercial query when the one or more terms of the query, in any particular order, matches the commercial query pattern in the list of commercial query patterns; processing, by one or more processors of the one or more server devices, the query in a first processing manner when the query is not determined to be a commercial query, where processing the query in the first processing manner includes ranking documents in a first ranking manner; and processing, by one or more processors of the one or more server devices, the query in a second, different processing manner in response to determining that the query is a commercial query, where processing the query in the second processing manner includes ranking documents in a second, different ranking manner. | 1. A method performed by one or more server devices, the method comprising: receiving, at one or more processors of the one or more server devices, a query, from a client device, that includes one or more terms; determining, by one or more processors of the one or more server devices, whether the query is a commercial query by: determining whether the one or more terms of the query, in any particular order, matches a commercial query pattern in a list of commercial query patterns, where the list of commercial query patterns includes patterns associated with one or more host names or domain names that include more than a particular number of hyphens, and identifying the query as a commercial query when the one or more terms of the query, in any particular order, matches the commercial query pattern in the list of commercial query patterns; processing, by one or more processors of the one or more server devices, the query in a first processing manner when the query is not determined to be a commercial query, where processing the query in the first processing manner includes ranking documents in a first ranking manner; and processing, by one or more processors of the one or more server devices, the query in a second, different processing manner in response to determining that the query is a commercial query, where processing the query in the second processing manner includes ranking documents in a second, different ranking manner. 8. The method of claim 1 , where the patterns associated with the one or more host names or domain names that include more than a particular number of hyphens include patterns generated from the one or more host names or domain names that include more than a particular number of hyphens. | 0.787297 |
7,634,469 | 1 | 2 | 1. A system for searching information and displaying search results, the system comprising: a web server comprising an inputting module that receives one or more keywords input from one or more client computers; and a search server comprising: an obtaining module that obtains search results according to the one or more keywords from a cache of the search server or from an index database, the search results comprising one or more documents; a calculating module that calculates a weight of each word of the documents in the search results, calculates a correlation between each cluster name and each document in the search results, and calculates a probability of each document occurring in each language module; a confirming module that confirms at least one cluster name according to the search results by comparing each weight and a defined cluster-name threshold, selecting the words that reach the defined cluster-name threshold, and deleting punctuations in the words that reach the defined cluster-name threshold according to a longest-word principle, and clusters each of the one or more documents in the search results into a corresponding cluster name according to the correlation, classifies each document in the search results into a corresponding field according to the probability, and thus obtains classified search results; a generating module that generates a cluster diagram according to the at least one cluster name and the clustered documents, and generates a cluster-classification diagram according to the classified search results and the generated cluster diagram; the web server further comprising an outputting module that outputs the generated cluster-classification diagram to the one or more client computers. | 1. A system for searching information and displaying search results, the system comprising: a web server comprising an inputting module that receives one or more keywords input from one or more client computers; and a search server comprising: an obtaining module that obtains search results according to the one or more keywords from a cache of the search server or from an index database, the search results comprising one or more documents; a calculating module that calculates a weight of each word of the documents in the search results, calculates a correlation between each cluster name and each document in the search results, and calculates a probability of each document occurring in each language module; a confirming module that confirms at least one cluster name according to the search results by comparing each weight and a defined cluster-name threshold, selecting the words that reach the defined cluster-name threshold, and deleting punctuations in the words that reach the defined cluster-name threshold according to a longest-word principle, and clusters each of the one or more documents in the search results into a corresponding cluster name according to the correlation, classifies each document in the search results into a corresponding field according to the probability, and thus obtains classified search results; a generating module that generates a cluster diagram according to the at least one cluster name and the clustered documents, and generates a cluster-classification diagram according to the classified search results and the generated cluster diagram; the web server further comprising an outputting module that outputs the generated cluster-classification diagram to the one or more client computers. 2. The system according to claim 1 , wherein the search server further comprises: a processing module that preprocesses the search results, the preprocessing comprising defining thresholds; and a classification database that stores language modules of various fields. | 0.5 |
8,073,868 | 20 | 21 | 20. The method of claim 8 , further comprising: obtaining relationships involving said related terms and data entities at different locations in said data network, and organizing said related terms, said relationships, and said data entities in at least one data structure that represents said relationships in said data network, wherein the data structure is organized based on at least one of data network analysis and expert knowledge. | 20. The method of claim 8 , further comprising: obtaining relationships involving said related terms and data entities at different locations in said data network, and organizing said related terms, said relationships, and said data entities in at least one data structure that represents said relationships in said data network, wherein the data structure is organized based on at least one of data network analysis and expert knowledge. 21. The method of claim 20 , wherein the relationships between data entities in said data network are analyzed in accordance with statistical correlations of word frequencies, locations, and dates within the data network. | 0.5 |
9,396,178 | 1 | 6 | 1. A computer implemented method for automated dictionary population, comprising: providing a processor executing instructions for: receiving a message containing words; parsing the words of the message; comparing each word to entries of at least one dictionary to identify new words that are not in said at least one dictionary; storing said new words in a supplementary word list; and parsing a group of adjacent words, wherein if none of said ad adjacent words are found in said at least one dictionary, storing said adjacent words with additional information that allows them to remain linked. | 1. A computer implemented method for automated dictionary population, comprising: providing a processor executing instructions for: receiving a message containing words; parsing the words of the message; comparing each word to entries of at least one dictionary to identify new words that are not in said at least one dictionary; storing said new words in a supplementary word list; and parsing a group of adjacent words, wherein if none of said ad adjacent words are found in said at least one dictionary, storing said adjacent words with additional information that allows them to remain linked. 6. The method of automated dictionary population, as recited in claim 1 , wherein the parsing and comparing of the words is performed as each word is retrieved. | 0.741935 |
6,044,383 | 1 | 8 | 1. A tabulation device comprising: a grid structure retaining means which maintains text strings composing a table and grid structure; text field size threshold providing means for providing at least a value of one of the width and the height at a plurality of discontinuous points output of a line-breaking function on said text strings composing a table, said line breaking function of a text maps a width/height to a height/width of a rectangular area whose height/width is minimum for laying out the text in said rectangular area; text field size retaining means for retaining a relationship between said text string composing said table and the size of a rectangular area provided by said text field size threshold providing means in response to said text; table layout means for acquiring one of said sizes of rectangular area from said text field size threshold providing means, for causing said text field size threshold retaining means to retain the relationship between said text and said one of the sizes of rectangular area acquired by said table lay out means, based on said grid structure; and evaluating means responsive to the result of comparison of the tabulation by said table lay out means with predetermined conditions for directing said table layout means to acquire another one of the sizes of rectangular area from said text field size threshold providing means, for causing said text field size threshold retaining means to retain the relationship between said another one of the sizes of rectangular area and said text. | 1. A tabulation device comprising: a grid structure retaining means which maintains text strings composing a table and grid structure; text field size threshold providing means for providing at least a value of one of the width and the height at a plurality of discontinuous points output of a line-breaking function on said text strings composing a table, said line breaking function of a text maps a width/height to a height/width of a rectangular area whose height/width is minimum for laying out the text in said rectangular area; text field size retaining means for retaining a relationship between said text string composing said table and the size of a rectangular area provided by said text field size threshold providing means in response to said text; table layout means for acquiring one of said sizes of rectangular area from said text field size threshold providing means, for causing said text field size threshold retaining means to retain the relationship between said text and said one of the sizes of rectangular area acquired by said table lay out means, based on said grid structure; and evaluating means responsive to the result of comparison of the tabulation by said table lay out means with predetermined conditions for directing said table layout means to acquire another one of the sizes of rectangular area from said text field size threshold providing means, for causing said text field size threshold retaining means to retain the relationship between said another one of the sizes of rectangular area and said text. 8. A tabulation device according to claim 1, wherein: if another size of rectangular area is provided by said text field size threshold providing means in response to one of said text and said another size is less than the present width/height of said text field size and not more than the maximum height/width of text field sizes of texts which belongs to a column/row including said text, said evaluating means directing said table lay out means to acquire said another size of rectangular area from said text field size threshold providing means, for causing said text field size threshold retaining means to retain the relationship between said text and said another size of rectangular area. | 0.567164 |
8,799,885 | 20 | 21 | 20. A non-transitory computer readable memory comprising program instructions stored therein that, when executed by a processor, cause the processor to implement a method for resolving exceptions thrown by a class loader in a virtual machine environment by: augmenting by a policy class loader of a virtual machine environment an exception message being thrown concurrently by the policy class loader for an unloadable missing class when the policy class loader attempts to load the missing class during a class loading process, wherein the policy class loader comprises one of a plurality of policy class loaders, wherein each policy class loader of the plurality of policy class loaders replaces an original class loader in the class loading process and comprises metadata describing interrelationships between the policy class loader and at least one other policy class loader of the plurality of policy class loaders based on a class loader tree of the original class loaders, wherein the class loading process uses the policy class loaders and metadata instead of the original class loaders and wherein augmenting the exception message comprises adding to the exception message the information obtained from the metadata describing interrelationships between the policy class loader and the at least one other policy class loader; identifying by an exception analyzer of the virtual machine environment a name of the missing class that is unloadable in response to and concurrent with the exception message being thrown by the policy class loader for said unloadable missing class; determining by the exception analyzer and concurrent with the exception message being thrown a sequence of policy class loaders involved in trying to return said missing class based on the name of the identified missing class; determining by a query engine of the virtual machine environment and concurrent with the exception message being thrown if said missing class is loadable from any remaining policy class loader, wherein said remaining policy class loader is not in said determined sequence of policy class loaders, and wherein determining whether the missing class is loadable is based on accessing the metadata from any policy class loader not originally in the sequence of policy class loaders; and recommending by a solution generator of the virtual machine environment and concurrent with the exception message being thrown a configuration change based on said determining if said missing class is loadable from any remaining policy class loader supporting said virtual machine environment. | 20. A non-transitory computer readable memory comprising program instructions stored therein that, when executed by a processor, cause the processor to implement a method for resolving exceptions thrown by a class loader in a virtual machine environment by: augmenting by a policy class loader of a virtual machine environment an exception message being thrown concurrently by the policy class loader for an unloadable missing class when the policy class loader attempts to load the missing class during a class loading process, wherein the policy class loader comprises one of a plurality of policy class loaders, wherein each policy class loader of the plurality of policy class loaders replaces an original class loader in the class loading process and comprises metadata describing interrelationships between the policy class loader and at least one other policy class loader of the plurality of policy class loaders based on a class loader tree of the original class loaders, wherein the class loading process uses the policy class loaders and metadata instead of the original class loaders and wherein augmenting the exception message comprises adding to the exception message the information obtained from the metadata describing interrelationships between the policy class loader and the at least one other policy class loader; identifying by an exception analyzer of the virtual machine environment a name of the missing class that is unloadable in response to and concurrent with the exception message being thrown by the policy class loader for said unloadable missing class; determining by the exception analyzer and concurrent with the exception message being thrown a sequence of policy class loaders involved in trying to return said missing class based on the name of the identified missing class; determining by a query engine of the virtual machine environment and concurrent with the exception message being thrown if said missing class is loadable from any remaining policy class loader, wherein said remaining policy class loader is not in said determined sequence of policy class loaders, and wherein determining whether the missing class is loadable is based on accessing the metadata from any policy class loader not originally in the sequence of policy class loaders; and recommending by a solution generator of the virtual machine environment and concurrent with the exception message being thrown a configuration change based on said determining if said missing class is loadable from any remaining policy class loader supporting said virtual machine environment. 21. The non-transitory computer readable memory of claim 20 , wherein said program instructions further comprises: replacing each class loader in the class loader tree with a policy class loader that is populated with said metadata. | 0.751606 |
9,665,246 | 10 | 12 | 10. A computing device of comprising: at least one processor; and a memory comprising instructions that, when executed, cause the at least one processor to: determine, based on a first input at a graphical keyboard, a first plurality of candidate strings and an initial ranked ordering of the first plurality of candidate character strings, wherein a particular candidate character string from the first plurality of candidate character strings is associated with a highest rank of the initial ranked ordering of the first plurality of candidate character strings; output, for display, based on the initial ranked ordering of the first plurality of candidate character strings, the particular candidate character string in a first text suggestion region from a plurality of text suggestion regions, the first text suggestion region being associated with a highest rank of a ranked ordering of the plurality of text suggestion regions and the second text suggestion region being associated with a second-highest rank of the ranked ordering of the plurality of text suggestion regions; receive a second input that selects the particular candidate character string from the first text suggestion region; determine, based on a third input at the graphical keyboard, a second plurality of candidate strings and a subsequent ranked ordering of the second plurality of candidate character strings, the second plurality of candidate character strings including the particular candidate character string, the particular candidate character string being associated with a second-highest rank of the subsequent ranked ordering of the second plurality of candidate character strings; associate, based on the subsequent ranked ordering of the second plurality of candidate character strings, the particular candidate character string with the second text suggestion region; and responsive to determining that the particular candidate character string was previously selected from the first text suggestion region when the particular candidate character string was previously displayed, output, for display, the particular candidate character string in the first text suggestion region. | 10. A computing device of comprising: at least one processor; and a memory comprising instructions that, when executed, cause the at least one processor to: determine, based on a first input at a graphical keyboard, a first plurality of candidate strings and an initial ranked ordering of the first plurality of candidate character strings, wherein a particular candidate character string from the first plurality of candidate character strings is associated with a highest rank of the initial ranked ordering of the first plurality of candidate character strings; output, for display, based on the initial ranked ordering of the first plurality of candidate character strings, the particular candidate character string in a first text suggestion region from a plurality of text suggestion regions, the first text suggestion region being associated with a highest rank of a ranked ordering of the plurality of text suggestion regions and the second text suggestion region being associated with a second-highest rank of the ranked ordering of the plurality of text suggestion regions; receive a second input that selects the particular candidate character string from the first text suggestion region; determine, based on a third input at the graphical keyboard, a second plurality of candidate strings and a subsequent ranked ordering of the second plurality of candidate character strings, the second plurality of candidate character strings including the particular candidate character string, the particular candidate character string being associated with a second-highest rank of the subsequent ranked ordering of the second plurality of candidate character strings; associate, based on the subsequent ranked ordering of the second plurality of candidate character strings, the particular candidate character string with the second text suggestion region; and responsive to determining that the particular candidate character string was previously selected from the first text suggestion region when the particular candidate character string was previously displayed, output, for display, the particular candidate character string in the first text suggestion region. 12. The computing device of claim 10 , wherein the instructions, when executed, further cause the at least one processor to output the particular candidate character string for display in the first text suggestion region based at least in part on determining that a context of the third input matches a context associated with the particular candidate character string. | 0.623469 |
8,166,080 | 10 | 12 | 10. A computer program product comprising: a non-transitory computer readable storage medium having computer usable program code encoded thereon for diagramming, including instructions which when executed on a computer, cause the computer to: generate a diagram graphically representing a subject model, the subject model having model elements and the diagram being formed of notational elements corresponding to the model elements of the subject model; and in response to a primary edit to the subject model, generate a non-persistent view representative of the primary edit for secondary edits to the diagram, the non-persistent view being contained in a non-persistent container element, that is associated with but detached from a persistent container element of the diagram, said generating including displaying the diagram and the non-persistent view to a user as if the non-persistent view were a persistent part of the diagram by displaying both attributes of the persistent and non-persistent container elements of the diagram; wherein a notation meta-model persists the notational elements with references to the corresponding model elements, the notation meta-model allowing notational elements to be recreated and changed dynamically in a manner free of replacing original notational elements in the diagram by mapping from which persistent and non-persistent container elements to retrieve said attributes, and wherein mapping attributes of the non-persistent container element to the persistent container element transforms the non-persistent view into a persistent view persisting with the diagram. | 10. A computer program product comprising: a non-transitory computer readable storage medium having computer usable program code encoded thereon for diagramming, including instructions which when executed on a computer, cause the computer to: generate a diagram graphically representing a subject model, the subject model having model elements and the diagram being formed of notational elements corresponding to the model elements of the subject model; and in response to a primary edit to the subject model, generate a non-persistent view representative of the primary edit for secondary edits to the diagram, the non-persistent view being contained in a non-persistent container element, that is associated with but detached from a persistent container element of the diagram, said generating including displaying the diagram and the non-persistent view to a user as if the non-persistent view were a persistent part of the diagram by displaying both attributes of the persistent and non-persistent container elements of the diagram; wherein a notation meta-model persists the notational elements with references to the corresponding model elements, the notation meta-model allowing notational elements to be recreated and changed dynamically in a manner free of replacing original notational elements in the diagram by mapping from which persistent and non-persistent container elements to retrieve said attributes, and wherein mapping attributes of the non-persistent container element to the persistent container element transforms the non-persistent view into a persistent view persisting with the diagram. 12. The computer program product as claimed in claim 10 further comprising instruction that causes the computer to: in response to a user directly modifying the displayed non-persistent view, transform the non-persistent view into a persistent view that persists with the diagram by assigning the attributes of the non-persistent container element to the persistent container element. | 0.5 |
8,036,432 | 11 | 12 | 11. A system for saving digital content classified by person-based clustering, comprising: a data structure generation unit located on one or more processors to generate a data structure including a plurality of nodes using a plurality of digital content; a cluster classification unit located on the one or more processors to classify the remaining digital content by the person-based clustering using a face descriptor if a part of the plurality of digital content is deleted; a data structure update unit located on the one or more processors to update the data structure according to the classification; and a database located on the one or more processors to update and save the remaining digital content by reflecting the updated data structure. | 11. A system for saving digital content classified by person-based clustering, comprising: a data structure generation unit located on one or more processors to generate a data structure including a plurality of nodes using a plurality of digital content; a cluster classification unit located on the one or more processors to classify the remaining digital content by the person-based clustering using a face descriptor if a part of the plurality of digital content is deleted; a data structure update unit located on the one or more processors to update the data structure according to the classification; and a database located on the one or more processors to update and save the remaining digital content by reflecting the updated data structure. 12. The system of claim 11 , wherein the data structure update unit updates the data structure of the new digital content and the plurality of the digital content by setting flags of person nodes and face nodes. | 0.531111 |
7,672,007 | 49 | 50 | 49. A computer-readable medium comprising an application program interface, the application program interface configurable to assemble software components of an automated digitizing system configurable to route information identified by content instructions in a document file on a computer to a potential plurality of application programs according to customizable transmission format instructions, said transmission format instructions being customized to requirements of each application program receiving said information. | 49. A computer-readable medium comprising an application program interface, the application program interface configurable to assemble software components of an automated digitizing system configurable to route information identified by content instructions in a document file on a computer to a potential plurality of application programs according to customizable transmission format instructions, said transmission format instructions being customized to requirements of each application program receiving said information. 50. A computer-readable medium as claimed in claim 49 in which at least one of said application programs is a digital archiving program. | 0.767918 |
6,026,396 | 1 | 8 | 1. Apparatus for providing information about a subject matter, including a knowledge base for automatically responding to a user message, the apparatus comprising: a logging means for receiving the user message when the knowledge base does not address the user message; a storage means for storing the logged user message; an output means for providing the logged user message to a subject matter expert; and a receiving means for receiving data input, for updating the knowledge base, from the subject matter expert, but not from other users of the system; said logged means comprises an identifier for the logged user message to associate additional future correspondence with said user related to the logged user message. | 1. Apparatus for providing information about a subject matter, including a knowledge base for automatically responding to a user message, the apparatus comprising: a logging means for receiving the user message when the knowledge base does not address the user message; a storage means for storing the logged user message; an output means for providing the logged user message to a subject matter expert; and a receiving means for receiving data input, for updating the knowledge base, from the subject matter expert, but not from other users of the system; said logged means comprises an identifier for the logged user message to associate additional future correspondence with said user related to the logged user message. 8. The apparatus of claim 1 wherein the user message is a comment. | 0.946254 |
7,983,902 | 12 | 14 | 12. A computer-implemented method, comprising: selecting a topic dictionary comprising topic words related to a topic; determining a topic word divergence value based on a topic word, a document corpus and a topic document corpus, wherein the topic document corpus is a corpus of topic documents related to the topic, and the document corpus is a corpus of documents that includes the topic documents and other documents, and the topic word is a word that is related to the topic; determining a candidate topic word divergence value for a candidate topic word based on the document corpus and the topic document corpus, wherein the candidate topic word is not a topic word in the topic dictionary; and determining whether the candidate topic word is a new topic word for the topic based on the candidate topic word divergence value and the topic word divergence value. | 12. A computer-implemented method, comprising: selecting a topic dictionary comprising topic words related to a topic; determining a topic word divergence value based on a topic word, a document corpus and a topic document corpus, wherein the topic document corpus is a corpus of topic documents related to the topic, and the document corpus is a corpus of documents that includes the topic documents and other documents, and the topic word is a word that is related to the topic; determining a candidate topic word divergence value for a candidate topic word based on the document corpus and the topic document corpus, wherein the candidate topic word is not a topic word in the topic dictionary; and determining whether the candidate topic word is a new topic word for the topic based on the candidate topic word divergence value and the topic word divergence value. 14. The method of claim 12 , wherein determining a topic word divergence value comprises: selecting existing topic words in the topic dictionary; determining an existing topic word divergence values for each of the topic words based on the document corpus and the topic document corpus; and determining the topic word divergence value based on a central tendency of the existing topic word divergence values. | 0.651877 |
3,996,557 | 1 | 10 | 1. An alphanumeric character recognition system for analyzing symbols each written in a sequence of strokes comprising: means for defining a writing area, means to separate said writing area into a minimum number of elongated side-by-side parallel contact areas, means for storing for predetermined symbols said sequence of strokes as to the respective side-by-side areas contacted, writing means for writing symbols in said writing area, said writing means connected to said storing means to feed thereto said sequence of strokes contacting said side-by-side parallel areas when a symbol is being written, comparison means for comparing said stored sequence of strokes of said predetermined symbols with said written sequence of strokes, and utilization means having the output of said comparison means connected thereto. | 1. An alphanumeric character recognition system for analyzing symbols each written in a sequence of strokes comprising: means for defining a writing area, means to separate said writing area into a minimum number of elongated side-by-side parallel contact areas, means for storing for predetermined symbols said sequence of strokes as to the respective side-by-side areas contacted, writing means for writing symbols in said writing area, said writing means connected to said storing means to feed thereto said sequence of strokes contacting said side-by-side parallel areas when a symbol is being written, comparison means for comparing said stored sequence of strokes of said predetermined symbols with said written sequence of strokes, and utilization means having the output of said comparison means connected thereto. 10. The system of claim 1 wherein said elongated side-by-side parallel contact areas are operative together. | 0.871734 |
7,685,191 | 10 | 16 | 10. A computer system, the system comprising: a computer; computer storage device that stores search event data descriptive of search activities of users over a plurality of different search engines; an analyzer that analyzes the search event data to identify search queries submitted to the plurality of different search engines to locate and access a particular document, and to identify usage statistics associated with usage of said search queries to locate the document; a component that uses said search queries and the usage statistics to control automated selection of advertisements displayed on the document wherein the usage statistics identify the search queries used the most frequently over the plurality of different search engines to locate said document, wherein the component further configured: to determine a data variance between content of the particular document and at least one search query used to locate the particular document, wherein the at least one search query was previously not identified with the content of the particular document, wherein the automatic selection is thereafter based at least partly on the at least one search query; to determine whether most referrals or a mathematically significant number of referrals from a particular search engine for the particular document correspond to a search query that is algorithmically relevant to the particular document; to provide advertising based on the search query used in response to a request for the particular document arising from use of the particular search engine and on a predicted user expectation of content as determined by analysis of tracked search activities when the most referrals or the mathematically significant number of referrals from the particular search engine for the particular document are based on search queries that are not algorithmically relevant, wherein the advertising is otherwise irrelevant to the particular document; and to otherwise provide advertising that is algorithmically determined to be relevant to the particular document. | 10. A computer system, the system comprising: a computer; computer storage device that stores search event data descriptive of search activities of users over a plurality of different search engines; an analyzer that analyzes the search event data to identify search queries submitted to the plurality of different search engines to locate and access a particular document, and to identify usage statistics associated with usage of said search queries to locate the document; a component that uses said search queries and the usage statistics to control automated selection of advertisements displayed on the document wherein the usage statistics identify the search queries used the most frequently over the plurality of different search engines to locate said document, wherein the component further configured: to determine a data variance between content of the particular document and at least one search query used to locate the particular document, wherein the at least one search query was previously not identified with the content of the particular document, wherein the automatic selection is thereafter based at least partly on the at least one search query; to determine whether most referrals or a mathematically significant number of referrals from a particular search engine for the particular document correspond to a search query that is algorithmically relevant to the particular document; to provide advertising based on the search query used in response to a request for the particular document arising from use of the particular search engine and on a predicted user expectation of content as determined by analysis of tracked search activities when the most referrals or the mathematically significant number of referrals from the particular search engine for the particular document are based on search queries that are not algorithmically relevant, wherein the advertising is otherwise irrelevant to the particular document; and to otherwise provide advertising that is algorithmically determined to be relevant to the particular document. 16. The system of claim 10 , wherein the advertisements comprise dynamic content items. | 0.85 |
8,522,140 | 1 | 12 | 1. A computer-implemented method for automatically positioning a plurality of text elements in an area of a markup language design of at least a portion of a document, the method comprising: executing, at a computer system, one or more design tools; accessing, by the one or more design tools, the markup language design of the document, the markup language design defining a plurality of text elements each having a defined relative vertical positioning order, and further defining one or more vertical spacing distances, the one or more vertical spacing distances comprising one or more of either or both of a defined vertical spacing distance between adjacent text elements in the markup language design and a defined vertical spacing distance between data within the text elements in the markup language design, the one or more design tools configured to allow a user to specify text content for one or more of the text elements in the markup language design, determine which of the plurality of text elements have specified text content, determine at least the height of each of the determined text elements having specified text content, and based on at least the determined text element heights, the one or more vertical spacing distances, and the defined positioning order, position each of those text elements having specified text content in the area such that each text element in the area is vertically separated from each adjacent text element by a defined spacing distance, whereby the layout of the text elements haying specified text content is determined. | 1. A computer-implemented method for automatically positioning a plurality of text elements in an area of a markup language design of at least a portion of a document, the method comprising: executing, at a computer system, one or more design tools; accessing, by the one or more design tools, the markup language design of the document, the markup language design defining a plurality of text elements each having a defined relative vertical positioning order, and further defining one or more vertical spacing distances, the one or more vertical spacing distances comprising one or more of either or both of a defined vertical spacing distance between adjacent text elements in the markup language design and a defined vertical spacing distance between data within the text elements in the markup language design, the one or more design tools configured to allow a user to specify text content for one or more of the text elements in the markup language design, determine which of the plurality of text elements have specified text content, determine at least the height of each of the determined text elements having specified text content, and based on at least the determined text element heights, the one or more vertical spacing distances, and the defined positioning order, position each of those text elements having specified text content in the area such that each text element in the area is vertically separated from each adjacent text element by a defined spacing distance, whereby the layout of the text elements haying specified text content is determined. 12. The method of claim 1 , wherein the one or more design tools are configured to reside partially on the computer system and partially on one or more server computer systems, and wherein the step of receiving user specified text content for one or more text elements in the markup language design is executed on the computer system and further comprises transferring the received user specified text content to a portion of the one or more design tools executing on the one or more server computer systems, and the steps of determining which of the plurality of text elements have specified text content, determining at least the height of each of the determined text elements having specified text content, and based on at least the determined text element heights, the one or more vertical spacing distances, and the defined positioning order, positioning each of those text elements having specified text content in the area such that each text element in the area is vertically separated from each adjacent text element to generate an updated markup language document are each executed on the one or more server computer systems to generate an updated markup language document. | 0.5 |
9,373,040 | 11 | 15 | 11. A non-transitory computer-readable storage medium having executable computer program instructions embodied therein for creating a motion manifold for determining a similarity between two image patches, actions of the computer program instructions comprising: identifying semantic regions of videos of a set of videos; for each semantic region, identifying patch trajectories by identifying patches corresponding to the semantic region and tracking the patches across consecutive frames of the videos, a patch corresponding to the semantic region including image data for the semantic region; creating a motion manifold indicating different visual representations of a given semantic region by using the patch trajectories identified for the given semantic region, the creating of the motion manifold comprising: clustering the patches into patch clusters according to visual similarity of the patches, each patch cluster representing a subset of the patches having similar visual appearances, the patches of the subset being from one or more patch trajectories, and determining degrees of semantic similarity between pairs of the patch clusters based on degrees to which a first cluster of the pair and a second cluster of the pair have patches from a same patch trajectory; and storing the motion manifold. | 11. A non-transitory computer-readable storage medium having executable computer program instructions embodied therein for creating a motion manifold for determining a similarity between two image patches, actions of the computer program instructions comprising: identifying semantic regions of videos of a set of videos; for each semantic region, identifying patch trajectories by identifying patches corresponding to the semantic region and tracking the patches across consecutive frames of the videos, a patch corresponding to the semantic region including image data for the semantic region; creating a motion manifold indicating different visual representations of a given semantic region by using the patch trajectories identified for the given semantic region, the creating of the motion manifold comprising: clustering the patches into patch clusters according to visual similarity of the patches, each patch cluster representing a subset of the patches having similar visual appearances, the patches of the subset being from one or more patch trajectories, and determining degrees of semantic similarity between pairs of the patch clusters based on degrees to which a first cluster of the pair and a second cluster of the pair have patches from a same patch trajectory; and storing the motion manifold. 15. The non-transitory computer-readable storage medium of claim 11 , wherein creating the motion manifold comprises: forming a cluster matrix, wherein each matrix element is based on the determined degree of semantic similarity between a pair of the patch clusters to which the matrix element corresponds. | 0.5 |
9,357,071 | 1 | 14 | 1. A non-transitory, computer readable medium that controls an executable computer readable program code embodied therein, the executable computer readable program code for implementing a method of analyzing electronic communication data and generating behavioral assessment data therefrom, which method comprises: receiving, by a control processor, an electronic communication in text form from a communicant; analyzing the text of the electronic communication by mining the text of the electronic communication and applying a predetermined linguistic-based psychological behavioral model to the text of the electronic communication; and generating behavioral assessment data including a personality type corresponding to the analyzed text of the electronic communication. | 1. A non-transitory, computer readable medium that controls an executable computer readable program code embodied therein, the executable computer readable program code for implementing a method of analyzing electronic communication data and generating behavioral assessment data therefrom, which method comprises: receiving, by a control processor, an electronic communication in text form from a communicant; analyzing the text of the electronic communication by mining the text of the electronic communication and applying a predetermined linguistic-based psychological behavioral model to the text of the electronic communication; and generating behavioral assessment data including a personality type corresponding to the analyzed text of the electronic communication. 14. The non-transitory, computer readable medium of claim 1 , wherein the personality type comprises an arrangement of all personality types in a plurality of tiers. | 0.903958 |
9,930,092 | 1 | 21 | 1. A system comprising: memory; at least one processor; a third party application user interface; a third party application engine, coupled to the third party application user interface, configured to implement a third party application on a client-side network, wherein the client-side network is client-side relative to a server-side application server, wherein the third party application implemented on the client-side network is not hosted by the server-side application server and is hosted by a remote server that forms part of the client-side network, and the third party application implemented on the client-side network is embedded with a document application program interface enabling the third party application implemented on the client-side network to execute a document editing application hosted by the server-side application server; a file storage repository, coupled to the third party application engine, and configured to maintain a file on the client-side network; a client-side remote communications engine coupled to the third party application engine and configured to communicate with the server-side application server; wherein, in operation: the third party application user interface receives a request from a user to process a modification to the file using the third party application implemented on the client-side network; the third party application engine selects a set of custom parameters influencing presentation of the file; the third party application engine transfers the request and the set of custom parameters to the client-side remote communications engine; the client-side remote communications engine establishes a session to the server-side application server on a server-side network; the client-side remote communications engine transfers the request and the set of custom parameters to the server-side application server; the client-side remote communications engine receives a response to the request from the server-side application server, the response including application data that can be presented by the third party application implemented on the client-side network; the third party application engine displays at least a portion of the file, modified in accordance with the request and the set of custom parameters, at the third party application user interface; the third party application engine instructs the client-side remote communications engine to initiate a procedure to close the session in response to detecting a termination stimulus. | 1. A system comprising: memory; at least one processor; a third party application user interface; a third party application engine, coupled to the third party application user interface, configured to implement a third party application on a client-side network, wherein the client-side network is client-side relative to a server-side application server, wherein the third party application implemented on the client-side network is not hosted by the server-side application server and is hosted by a remote server that forms part of the client-side network, and the third party application implemented on the client-side network is embedded with a document application program interface enabling the third party application implemented on the client-side network to execute a document editing application hosted by the server-side application server; a file storage repository, coupled to the third party application engine, and configured to maintain a file on the client-side network; a client-side remote communications engine coupled to the third party application engine and configured to communicate with the server-side application server; wherein, in operation: the third party application user interface receives a request from a user to process a modification to the file using the third party application implemented on the client-side network; the third party application engine selects a set of custom parameters influencing presentation of the file; the third party application engine transfers the request and the set of custom parameters to the client-side remote communications engine; the client-side remote communications engine establishes a session to the server-side application server on a server-side network; the client-side remote communications engine transfers the request and the set of custom parameters to the server-side application server; the client-side remote communications engine receives a response to the request from the server-side application server, the response including application data that can be presented by the third party application implemented on the client-side network; the third party application engine displays at least a portion of the file, modified in accordance with the request and the set of custom parameters, at the third party application user interface; the third party application engine instructs the client-side remote communications engine to initiate a procedure to close the session in response to detecting a termination stimulus. 21. The system of claim 1 , wherein the third party application user interface enables the user to open the file as part of a file opening routine that includes providing a file opening command to the client-side remote communications engine to send as the request to the server-side application server. | 0.689549 |
9,135,344 | 11 | 20 | 11. A system for providing search results based on user interaction with content, the system comprising: a server of a linking system receiving identification of a plurality of clicks of encoded uniform resource locator (URL) links, the encoded URL links generated by the server of the linking system and linked to content items on destination servers, the plurality of clicks corresponding to clicks performed by a plurality of users via devices on which the encoded URL links are provided for display; a click tracker of the linking system identifying for each of the plurality of clicks, data about a user of the plurality of users who clicked an encoded URL link and traffic data associated with the device from which the user clicked the encoded URL link a database storing a record for each click of the plurality of clicks, the record comprising data about the user and traffic data associated with each click, the traffic data including a referring website on which the encoded URL link was displayed when clicked by the user; a relevancy scorer of the linking system determines based on the records corresponding to the plurality of clicks performed by the plurality of users, a relevancy score for each content item identified from decoding the encoded URL links, the relevancy score for each content item indicating a popularity of the content item based on a number of clicks received by encoded URLs linked to the content item and a number of referring websites; and wherein the server of the linking system responsive to the server of the linking system receiving a request to search content based on a keyword, communicates a set of search results based on the keyword and the respective relevancy scores of the content items included in the set of search results. | 11. A system for providing search results based on user interaction with content, the system comprising: a server of a linking system receiving identification of a plurality of clicks of encoded uniform resource locator (URL) links, the encoded URL links generated by the server of the linking system and linked to content items on destination servers, the plurality of clicks corresponding to clicks performed by a plurality of users via devices on which the encoded URL links are provided for display; a click tracker of the linking system identifying for each of the plurality of clicks, data about a user of the plurality of users who clicked an encoded URL link and traffic data associated with the device from which the user clicked the encoded URL link a database storing a record for each click of the plurality of clicks, the record comprising data about the user and traffic data associated with each click, the traffic data including a referring website on which the encoded URL link was displayed when clicked by the user; a relevancy scorer of the linking system determines based on the records corresponding to the plurality of clicks performed by the plurality of users, a relevancy score for each content item identified from decoding the encoded URL links, the relevancy score for each content item indicating a popularity of the content item based on a number of clicks received by encoded URLs linked to the content item and a number of referring websites; and wherein the server of the linking system responsive to the server of the linking system receiving a request to search content based on a keyword, communicates a set of search results based on the keyword and the respective relevancy scores of the content items included in the set of search results. 20. The system of claim 11 , wherein the relevancy scorer orders search results by relevancy score. | 0.815985 |
9,158,748 | 15 | 21 | 15. Apparatus for accessing electronic documents, the apparatus comprising: a server computer storing a plurality of electronic documents; a plurality of client computers that can view the plurality of electronic documents stored on the host server and can copy text from the plurality of electronic documents; and an annotation service, wherein the annotation service generates a first annotation from a selected portion of text within a first electronic document by: analyzing an unselected portion of text that precedes the selected portion of text within the first electronic document; and identifying a part of the unselected portion of text to replace a part of the selected portion of text; and wherein the annotation service makes the first annotation available to a first client computer in the plurality of client computers when the first client computer copies the selected portion of text, and wherein the first annotation is used to generate a modified selected portion of text that is pasted into a second electronic document different from the first electronic document. | 15. Apparatus for accessing electronic documents, the apparatus comprising: a server computer storing a plurality of electronic documents; a plurality of client computers that can view the plurality of electronic documents stored on the host server and can copy text from the plurality of electronic documents; and an annotation service, wherein the annotation service generates a first annotation from a selected portion of text within a first electronic document by: analyzing an unselected portion of text that precedes the selected portion of text within the first electronic document; and identifying a part of the unselected portion of text to replace a part of the selected portion of text; and wherein the annotation service makes the first annotation available to a first client computer in the plurality of client computers when the first client computer copies the selected portion of text, and wherein the first annotation is used to generate a modified selected portion of text that is pasted into a second electronic document different from the first electronic document. 21. The apparatus of claim 15 , wherein the annotation service allows a user to edit the first annotation. | 0.819113 |
8,095,365 | 9 | 14 | 9. A system for generating a lexicon for use with speech recognition, the system comprising: a processor; a first module configured to cause the processor to receive symbolic input as labeled speech data; a second module configured to cause the processor to overgenerate potential pronunciations based on the symbolic input, wherein the second module further causes the processor to: establish a set of conversion rules; and convert portions of the symbolic input into a number of possible lexical pronunciation variants based on the set of conversion rules; a third module configured to cause the processor to identify potential pronunciations in a speech recognition context to yield identified potential pronunciations; and a fourth module configured to cause the processor to store the identified potential pronunciations in a lexicon. | 9. A system for generating a lexicon for use with speech recognition, the system comprising: a processor; a first module configured to cause the processor to receive symbolic input as labeled speech data; a second module configured to cause the processor to overgenerate potential pronunciations based on the symbolic input, wherein the second module further causes the processor to: establish a set of conversion rules; and convert portions of the symbolic input into a number of possible lexical pronunciation variants based on the set of conversion rules; a third module configured to cause the processor to identify potential pronunciations in a speech recognition context to yield identified potential pronunciations; and a fourth module configured to cause the processor to store the identified potential pronunciations in a lexicon. 14. The system of claim 9 , wherein the second module is further configured to control the processor to model the possible lexical pronunciation variants in one of a weighted network and a list of phoneme lists. | 0.5 |
9,335,982 | 7 | 10 | 7. A method comprising: executing, by a dispatcher via a dispatcher table, a first translated binary, the dispatcher table mapping a subset of instructions from a source binary to corresponding instructions in the first translated binary; upon encountering a branch instruction in the first translated binary with a target that is addressable in the first translated binary, branching, by a processor, to a target address in the first translated binary and executing an instruction at the target address in the first translated binary; upon encountering a branch instruction in the first translated binary with a target that is not addressable in the first translated binary, accessing a second translated binary, the second translated binary including one or more marker values corresponding to a second set of instructions in the second translated binary; wherein the processor is programmed to branch to a target address, in the second translated binary, described by a marker value in a second marker table and execute an instruction at the target address in the second translated binary; and returning to the first translated binary from the second translated binary after reaching a subsequent branch instruction in the second translated binary by branching directly to the dispatcher for every branch instruction that leaves a current function from the second translated binary. | 7. A method comprising: executing, by a dispatcher via a dispatcher table, a first translated binary, the dispatcher table mapping a subset of instructions from a source binary to corresponding instructions in the first translated binary; upon encountering a branch instruction in the first translated binary with a target that is addressable in the first translated binary, branching, by a processor, to a target address in the first translated binary and executing an instruction at the target address in the first translated binary; upon encountering a branch instruction in the first translated binary with a target that is not addressable in the first translated binary, accessing a second translated binary, the second translated binary including one or more marker values corresponding to a second set of instructions in the second translated binary; wherein the processor is programmed to branch to a target address, in the second translated binary, described by a marker value in a second marker table and execute an instruction at the target address in the second translated binary; and returning to the first translated binary from the second translated binary after reaching a subsequent branch instruction in the second translated binary by branching directly to the dispatcher for every branch instruction that leaves a current function from the second translated binary. 10. The method of claim 7 , wherein the source binary is configured to be executed by a source processing architecture, and wherein the first translated binary and the second translated binary are configured to be executed by a target processing architecture. | 0.5 |
7,668,849 | 13 | 16 | 13. The system of claim 11 , wherein the data structure stores the unstructured data and the structured data associated with an email. | 13. The system of claim 11 , wherein the data structure stores the unstructured data and the structured data associated with an email. 16. The system of claim 13 , wherein the data structure stores the unstructured data associated with an email attachment. | 0.5 |
7,526,731 | 13 | 19 | 13. A method for designing a customized user interface, comprising: categorizing a user population into at least two groups, describing the categorized groups, and modeling the described groups using qualitative and quantitative models, the categorizing, describing and modeling being based upon Categorize-Describe-Model (CDM) methodology; applying the models to interface design by analyzing screen flow including a prototypical screen flow; and creating the quantitative models based upon the screen flow analysis. | 13. A method for designing a customized user interface, comprising: categorizing a user population into at least two groups, describing the categorized groups, and modeling the described groups using qualitative and quantitative models, the categorizing, describing and modeling being based upon Categorize-Describe-Model (CDM) methodology; applying the models to interface design by analyzing screen flow including a prototypical screen flow; and creating the quantitative models based upon the screen flow analysis. 19. The method of claim 13 , further comprising: validating targeted user behaviors and user preferences of the model; and tracking design requirements for the validated user behaviors and user preferences. | 0.5 |
8,471,846 | 1 | 5 | 1. A method performed by a computer system for determining a position in an image of an object, comprising: displaying a volume rendering of image data acquired from the object, pointing at a structure of interest displayed in the volume rendering of the image data, generating a viewing ray profile comprising information characterizing a ray miming through said structure of interest, selecting a contextual profile from various contextual profiles, each of said contextual profiles comprising a representative ray profile representing a viewing ray profile of a structure and comprising profile information, and determining a position within said structure of interest based on said profile information of said selected contextual profile in the case that the representative ray profile of said selected contextual profile matches with at least a part of said viewing ray profile. | 1. A method performed by a computer system for determining a position in an image of an object, comprising: displaying a volume rendering of image data acquired from the object, pointing at a structure of interest displayed in the volume rendering of the image data, generating a viewing ray profile comprising information characterizing a ray miming through said structure of interest, selecting a contextual profile from various contextual profiles, each of said contextual profiles comprising a representative ray profile representing a viewing ray profile of a structure and comprising profile information, and determining a position within said structure of interest based on said profile information of said selected contextual profile in the case that the representative ray profile of said selected contextual profile matches with at least a part of said viewing ray profile. 5. The method according to claim 1 , wherein the selection of the contextual profile is based on information characterizing a setup of a medical workstation by means of which the acquisition, display of the image data, or both is controlled. | 0.703202 |
6,101,511 | 12 | 13 | 12. The process as set forth in claim 11, wherein the element descriptor for an element includes an indication of the location of the text content, for each element containing text content, and, for each element, the type name of the element. | 12. The process as set forth in claim 11, wherein the element descriptor for an element includes an indication of the location of the text content, for each element containing text content, and, for each element, the type name of the element. 13. The process as set forth in claim 12, wherein the indication of the parent, child and left sibling elements in each element descriptor is the element identifier of the parent, child and left sibling elements. | 0.5 |
8,296,123 | 1 | 38 | 1. A system comprising: a plurality of machine translation resource servers, each machine translation resource server storing and operable to serve a partition of a collection of machine translation resource data for translation from a source language to a target language, the respective partitions together constituting the collection of machine translation resource data and each respective partition being less than the collection of machine translation resource data; and at least one translation server operable to receive source text in the source language to be translated into the target language, the translation server further operable to obtain machine translation resource data from the plurality of machine translation resource servers and to use the obtained machine translation resource data to translate the source text into the target language, wherein the plurality of machine translation resource servers comprise: a plurality of language model servers each storing and operable to serve a partition of a language model for the target language, each partition being less than the entire language model and the respective partitions together constituting the entire language model, and a translation model server storing and operable to serve to the translation server a translation model for translation between the source language and the target language, and wherein the translation server is operable to: i) obtain translation model data from the translation model server, ii) translate the source text into a set of possible translations based on the translation model data, iii) obtain language model data from at least one of the partitions of the language model based on the set of possible translations, the language model data matching at least one token in at least one possible translation of the set of possible translations, and iv) determine a translation of the source text based on the obtained language model data and the set of possible translations. | 1. A system comprising: a plurality of machine translation resource servers, each machine translation resource server storing and operable to serve a partition of a collection of machine translation resource data for translation from a source language to a target language, the respective partitions together constituting the collection of machine translation resource data and each respective partition being less than the collection of machine translation resource data; and at least one translation server operable to receive source text in the source language to be translated into the target language, the translation server further operable to obtain machine translation resource data from the plurality of machine translation resource servers and to use the obtained machine translation resource data to translate the source text into the target language, wherein the plurality of machine translation resource servers comprise: a plurality of language model servers each storing and operable to serve a partition of a language model for the target language, each partition being less than the entire language model and the respective partitions together constituting the entire language model, and a translation model server storing and operable to serve to the translation server a translation model for translation between the source language and the target language, and wherein the translation server is operable to: i) obtain translation model data from the translation model server, ii) translate the source text into a set of possible translations based on the translation model data, iii) obtain language model data from at least one of the partitions of the language model based on the set of possible translations, the language model data matching at least one token in at least one possible translation of the set of possible translations, and iv) determine a translation of the source text based on the obtained language model data and the set of possible translations. 38. The system of claim 1 , further comprising: a communication network with which the machine translation resource servers and the translation server are in communication, the communication network operable to direct the source text from a client computer in the communication network to the translation server for translation. | 0.817168 |
8,775,640 | 23 | 24 | 23. The system according to claim 19 , wherein the service is a subscription-based service, and the machine-readable service description comprises a specification of a type of event to be considered within the subscription-based service. | 23. The system according to claim 19 , wherein the service is a subscription-based service, and the machine-readable service description comprises a specification of a type of event to be considered within the subscription-based service. 24. The system according to claim 23 , wherein the machine-readable service description comprises a specification of a notification mode of the subscription-based service. | 0.5 |
8,477,095 | 9 | 10 | 9. The system of claim 5 wherein: said human-audible output comprises repeating a previous human-audible output. | 9. The system of claim 5 wherein: said human-audible output comprises repeating a previous human-audible output. 10. The system of claim 9 wherein said pen based computer system comprises a memory capable of storing audio content corresponding to a first and a second children's books. | 0.689531 |
7,966,280 | 1 | 2 | 1. An automotive air conditioner comprising: an air-conditioning unit for supplying conditioned air into a vehicle; an information acquiring unit for acquiring state information indicating a state related to said vehicle; a storage unit for storing a plurality of pieces of said state information as respective learned data; a learning unit, by using said learned data, for constructing a probabilistic model into which said state information is entered in order to calculate the probability of a vehicle occupant performing a specific setting operation; a control information correcting unit for calculating said probability by entering said state information into the probabilistic model constructed by said learning unit, and for correcting setting information or control information related to the setting operation of said occupant in accordance with said calculated probability so as to achieve said specific setting operation; and an air-conditioning control unit for controlling said air-conditioning unit in accordance with said corrected setting information or control information, wherein said learning unit comprises: a clustering subunit for classifying said plurality of learned data stored in said storage unit into at least a first cluster and a second cluster, and for determining a first range for a value of said state information from the learned data included in said first cluster and a second range for the value of said state information from the learned data included in said second cluster; and a probabilistic model constructing subunit for constructing said probabilistic model associated with said specific setting operation by determining the probability of occurrence of the value of said state information contained in said first range and the probability of occurrence of the value of said state information contained in said second range. | 1. An automotive air conditioner comprising: an air-conditioning unit for supplying conditioned air into a vehicle; an information acquiring unit for acquiring state information indicating a state related to said vehicle; a storage unit for storing a plurality of pieces of said state information as respective learned data; a learning unit, by using said learned data, for constructing a probabilistic model into which said state information is entered in order to calculate the probability of a vehicle occupant performing a specific setting operation; a control information correcting unit for calculating said probability by entering said state information into the probabilistic model constructed by said learning unit, and for correcting setting information or control information related to the setting operation of said occupant in accordance with said calculated probability so as to achieve said specific setting operation; and an air-conditioning control unit for controlling said air-conditioning unit in accordance with said corrected setting information or control information, wherein said learning unit comprises: a clustering subunit for classifying said plurality of learned data stored in said storage unit into at least a first cluster and a second cluster, and for determining a first range for a value of said state information from the learned data included in said first cluster and a second range for the value of said state information from the learned data included in said second cluster; and a probabilistic model constructing subunit for constructing said probabilistic model associated with said specific setting operation by determining the probability of occurrence of the value of said state information contained in said first range and the probability of occurrence of the value of said state information contained in said second range. 2. The automotive air conditioner according to claim 1 , wherein said clustering subunit has a first clustering condition and a second clustering condition that define different ranges for the value of said state information, and generates said clusters after determining the ranges of the clusters to which said respective learned data belong by using said plurality of learned data and said first and second clustering conditions. | 0.859283 |
9,342,501 | 1 | 4 | 1. A method, comprising: receiving, at an input component of an information handling device, user input comprising one or more words; identifying, using a processor of the information handling device, an emotion associated with the one or more words; creating, using the processor, an emotion tag including the emotion associated with the one or more words; storing the emotion tag in a memory; analyzing one or more emotion tags; and modifying the user input based on the analyzing, wherein modifying comprises changing a visual rendering of the user input. | 1. A method, comprising: receiving, at an input component of an information handling device, user input comprising one or more words; identifying, using a processor of the information handling device, an emotion associated with the one or more words; creating, using the processor, an emotion tag including the emotion associated with the one or more words; storing the emotion tag in a memory; analyzing one or more emotion tags; and modifying the user input based on the analyzing, wherein modifying comprises changing a visual rendering of the user input. 4. The method of claim 1 , wherein: the user input comprises speech input; and the identifying an emotion associated with the one or more words comprises using an acoustic characteristic of the speech input to identify an emotion. | 0.5 |
9,129,305 | 1 | 6 | 1. A system for generating targeted advertisement recommendations, the system comprising: under control of a hardware processor: a data aggregation module configured to obtain a plurality of words from a social network; a relationship mining module in communication with the data aggregation module, the relationship mining module configured to create word relationships between selected ones of the plurality of words to produce relationship data, each of the word relationships reflecting a degree of association between two or more of the selected words, wherein the degree of association is based at least in part on an amount of social momentum between said selected words; and a recommender configured to generate targeted advertising based at least in part on said relationship data, wherein the recommender module is further configured to generate the targeted advertising by at least accessing user data to identify one or more first words in the relationship data, identifying one or more second words in the relationship data that have one or more of the word relationships with the one or more first words, and identifying one or more advertisements having at least one keyword that corresponds to the one or more second words. | 1. A system for generating targeted advertisement recommendations, the system comprising: under control of a hardware processor: a data aggregation module configured to obtain a plurality of words from a social network; a relationship mining module in communication with the data aggregation module, the relationship mining module configured to create word relationships between selected ones of the plurality of words to produce relationship data, each of the word relationships reflecting a degree of association between two or more of the selected words, wherein the degree of association is based at least in part on an amount of social momentum between said selected words; and a recommender configured to generate targeted advertising based at least in part on said relationship data, wherein the recommender module is further configured to generate the targeted advertising by at least accessing user data to identify one or more first words in the relationship data, identifying one or more second words in the relationship data that have one or more of the word relationships with the one or more first words, and identifying one or more advertisements having at least one keyword that corresponds to the one or more second words. 6. The system of claim 1 , wherein the user data includes at least one of user behavioral data and user tracking data. | 0.824926 |
8,543,404 | 9 | 13 | 9. A computer program product comprising a computer usable medium embodying computer usable program code that when executed by a processor performs a method for proactively completing empty fields for voice enabling a Web page, the method comprising: locating an empty input field in the Web page; determining whether or not a speech grammar exists for the empty input field; and if it is determined that the speech grammar does not exist for the empty input field: generating a speech grammar for the empty input field based upon permitted terms in a core attribute of the empty input field to obtain a generated speech grammar and prompting for first speech input for the empty input field; receiving the first speech input for the empty input field in response to the prompting, posting the received first speech input and the speech grammar to an automatic speech recognition (ASR) engine; and inserting a textual equivalent to the received first speech input into the empty input field, wherein the textual equivalent is provided by the ASR engine. | 9. A computer program product comprising a computer usable medium embodying computer usable program code that when executed by a processor performs a method for proactively completing empty fields for voice enabling a Web page, the method comprising: locating an empty input field in the Web page; determining whether or not a speech grammar exists for the empty input field; and if it is determined that the speech grammar does not exist for the empty input field: generating a speech grammar for the empty input field based upon permitted terms in a core attribute of the empty input field to obtain a generated speech grammar and prompting for first speech input for the empty input field; receiving the first speech input for the empty input field in response to the prompting, posting the received first speech input and the speech grammar to an automatic speech recognition (ASR) engine; and inserting a textual equivalent to the received first speech input into the empty input field, wherein the textual equivalent is provided by the ASR engine. 13. The computer program product of claim 9 , wherein generating a speech grammar for the empty input field comprises generating a speech grammar for each empty input field in the Web page based upon terms in a core attribute of the each empty input field. | 0.788779 |
9,633,048 | 13 | 15 | 13. A system for converting a text sentence into an image sentence, the system comprising: at least one processor; a text sentence analyzer configured for: receiving a text sentence comprising a plurality of text words, the plurality of text words including at least one verb phrase; identifying at least one semantic role associated with the at least one verb phrase; splitting the text sentence into a first sentence fragment and a second sentence fragment, each of the first sentence fragment and the second sentence fragment associated with at least one semantic role; an image database configured for storing images and corresponding information describing semantic roles of the stored images; a text/image comparison module configured for: receiving the text sentence; determining at least one semantic role associated with the at least one verb phrase; querying the image database for a single image associated with information matching the semantic roles of the at least one verb phrase, the querying including generating a feature vector of a candidate image in the image database and comparing the feature vector of the candidate image to the semantic roles associated with the at least one verb phrase; and responsive to determining that no single image is associated with information matching the semantic roles of the at least one verb phrase, instructing the text sentence analyzer to split the text sentence into the first sentence fragment and the second sentence fragment. | 13. A system for converting a text sentence into an image sentence, the system comprising: at least one processor; a text sentence analyzer configured for: receiving a text sentence comprising a plurality of text words, the plurality of text words including at least one verb phrase; identifying at least one semantic role associated with the at least one verb phrase; splitting the text sentence into a first sentence fragment and a second sentence fragment, each of the first sentence fragment and the second sentence fragment associated with at least one semantic role; an image database configured for storing images and corresponding information describing semantic roles of the stored images; a text/image comparison module configured for: receiving the text sentence; determining at least one semantic role associated with the at least one verb phrase; querying the image database for a single image associated with information matching the semantic roles of the at least one verb phrase, the querying including generating a feature vector of a candidate image in the image database and comparing the feature vector of the candidate image to the semantic roles associated with the at least one verb phrase; and responsive to determining that no single image is associated with information matching the semantic roles of the at least one verb phrase, instructing the text sentence analyzer to split the text sentence into the first sentence fragment and the second sentence fragment. 15. The system of claim 13 , wherein the text/image comparison module is further configured for: receiving the first sentence fragment and the second sentence fragment from the text sentence analyzer; and querying the image database for a first image associated with information matching the at least one semantic role of the first sentence fragment and a second image associated with information matching the at least one semantic role of the second sentence fragment, the querying including generating a first feature vector for the first image and a second feature vector the second image, and comparing the first feature vector and the second feature vector to the at least one semantic roles of the first sentence fragment and the second sentence fragment, respectively. | 0.5 |
7,805,411 | 1 | 2 | 1. A computer implemented method, comprising: using at least one computer system configured for: receiving a database query language statement and performance information related to the database query language statement; determining whether one or more statistics relating to the database query language statement are available or accurate in the performance information; determining a hint for a missing or an inaccurate statistic in the performance information; creating or improving an estimate of a value of an execution of the query language statement by at least recursively determining whether a predicate selectivity exceeds a threshold, wherein the act of creating or improving the estimate comprises sampling an adjustable portion of data against which the query language statement is to be performed without requiring performance of a full table scan based at least in part upon a relationship between the predicate selectivity and the threshold; and verifying the estimate by executing the query language statement to perform at least the full table scan based at least in part upon the predicate selectivity, wherein the act of verifying the estimate performs a sample of a result of the full table scan to adjust the estimate. | 1. A computer implemented method, comprising: using at least one computer system configured for: receiving a database query language statement and performance information related to the database query language statement; determining whether one or more statistics relating to the database query language statement are available or accurate in the performance information; determining a hint for a missing or an inaccurate statistic in the performance information; creating or improving an estimate of a value of an execution of the query language statement by at least recursively determining whether a predicate selectivity exceeds a threshold, wherein the act of creating or improving the estimate comprises sampling an adjustable portion of data against which the query language statement is to be performed without requiring performance of a full table scan based at least in part upon a relationship between the predicate selectivity and the threshold; and verifying the estimate by executing the query language statement to perform at least the full table scan based at least in part upon the predicate selectivity, wherein the act of verifying the estimate performs a sample of a result of the full table scan to adjust the estimate. 2. The method of claim 1 , further comprising: determining whether each performance statistic in the performance information is accurate; and generating the hint for each inaccurate statistic. | 0.686275 |
9,179,061 | 4 | 8 | 4. A computer-implemented method, comprising: acquiring an image of an object using a camera of a computing device; determining a foreground area and a background area of the image, the foreground area including a representation of the object, applying a color to the background area; cropping the image to remove the background area from the image; analyzing the foreground area to recognize text associated with the object; receiving a selection of at least one text input field; determining a set of words from recognized text that are associated with the at least one text input field; displaying a set of words from the recognized text; and enabling a user of the computing device to select at least one word from the set of words to perform at least one operation. | 4. A computer-implemented method, comprising: acquiring an image of an object using a camera of a computing device; determining a foreground area and a background area of the image, the foreground area including a representation of the object, applying a color to the background area; cropping the image to remove the background area from the image; analyzing the foreground area to recognize text associated with the object; receiving a selection of at least one text input field; determining a set of words from recognized text that are associated with the at least one text input field; displaying a set of words from the recognized text; and enabling a user of the computing device to select at least one word from the set of words to perform at least one operation. 8. The computer-implemented method of claim 4 , wherein at least a portion of the set of words is displayed on an interface that includes a selectable list of at least a subset of the set of words, the subset of the set of words being displayed according to an order that each word of the set of words is recognized from the text. | 0.759825 |
7,827,184 | 17 | 21 | 17. A computer readable medium having executable instructions stored thereon such that upon execution of the instructions, a processing device is operative to: generate a search results page in response to a search request, the search result page including document identifiers for each of a plurality of referenced documents retrieved in response to the search request; monitor user selection of one of the document identifiers, and monitor a page position of the user selected document identifier; determine a perceived relevance factor for the selected document identifier including prior probability calculations based on the page position of the user selected document identifier to determine relevance based on a position of the document identifier on the search results page and an inverse of the probability calculations to determine relevance of the identifier and identifier meta data; and calculate a relevance factor for the selected document identifier based on the perceived relevance factor and a plurality of document attribute based relevant scores. | 17. A computer readable medium having executable instructions stored thereon such that upon execution of the instructions, a processing device is operative to: generate a search results page in response to a search request, the search result page including document identifiers for each of a plurality of referenced documents retrieved in response to the search request; monitor user selection of one of the document identifiers, and monitor a page position of the user selected document identifier; determine a perceived relevance factor for the selected document identifier including prior probability calculations based on the page position of the user selected document identifier to determine relevance based on a position of the document identifier on the search results page and an inverse of the probability calculations to determine relevance of the identifier and identifier meta data; and calculate a relevance factor for the selected document identifier based on the perceived relevance factor and a plurality of document attribute based relevant scores. 21. The computer readable medium of claim 17 wherein each identifier includes a thumbnail. | 0.828897 |
9,020,806 | 10 | 15 | 10. In a computing environment, a system comprising: one or more processors; a sentence filter implemented on the one or more processors, the sentence filter configured to select a sentence for a sentence completion question using an N-gram language model, and an alternates generator implemented on the one or more processors, the alternates generator configured to use a class-based maximum entropy N-gram language model to generate a plurality of candidate alternates and provide the plurality of candidate alternates from which selected alternates are obtained, the selected alternates and a correct answer being output as a set of options for completing the sentence completion question. | 10. In a computing environment, a system comprising: one or more processors; a sentence filter implemented on the one or more processors, the sentence filter configured to select a sentence for a sentence completion question using an N-gram language model, and an alternates generator implemented on the one or more processors, the alternates generator configured to use a class-based maximum entropy N-gram language model to generate a plurality of candidate alternates and provide the plurality of candidate alternates from which selected alternates are obtained, the selected alternates and a correct answer being output as a set of options for completing the sentence completion question. 15. The system of claim 10 wherein the set of options comprises a single correct answer and two or more alternates. | 0.792419 |
9,298,763 | 1 | 4 | 1. A method, comprising: detecting, by a processor, user interaction on a property page, the property page used in accessing a user account of a user; analyzing, by the processor, user interaction at the property page to obtain contextual information of the user interaction; examining, by the processor, user profile data of the user to identify a field of information that needs to be updated, the identified field of information related to the contextual information obtained from the user interaction; generating, by the processor, a query for the field of information that needs updating, the query constructed using the contextual information obtained from the analysis, the query presented in a user interface at a client device used to access the user account, for user action; and updating, by the processor, the field of information within the user profile data with information obtained from the user interface based on the user action to the query, wherein the updating adds to the user profile data of the user. | 1. A method, comprising: detecting, by a processor, user interaction on a property page, the property page used in accessing a user account of a user; analyzing, by the processor, user interaction at the property page to obtain contextual information of the user interaction; examining, by the processor, user profile data of the user to identify a field of information that needs to be updated, the identified field of information related to the contextual information obtained from the user interaction; generating, by the processor, a query for the field of information that needs updating, the query constructed using the contextual information obtained from the analysis, the query presented in a user interface at a client device used to access the user account, for user action; and updating, by the processor, the field of information within the user profile data with information obtained from the user interface based on the user action to the query, wherein the updating adds to the user profile data of the user. 4. The method of claim 1 , wherein the user interaction is obtained from one or more properties hosted within an entity that hosts the property page. | 0.750836 |
8,793,575 | 11 | 12 | 11. One or more non-transitory computer-readable storage media storing computer-readable instructions that, when executed, instruct one or more processors to perform operations comprising: identifying progress of a user through a collection of electronic books, the progress of the user being based at least in part on a number of pages that have been consumed, the collection of electronic books comprising a plurality of electronic books; causing display of a progress bar indicating the progress of the user through the collection of electronic books, the progress bar indicating the progress of the user by visualizing an amount of consumed text with respect to an amount of unconsumed text; identifying a number of sessions of consumption of an electronic book of the collection of electronic books; causing display of information indicating the number of sessions of consumption of the electronic book; identifying an estimated amount of time to complete the electronic book of the collection of electronic books; and causing display of the estimated amount of time to complete the electronic book. | 11. One or more non-transitory computer-readable storage media storing computer-readable instructions that, when executed, instruct one or more processors to perform operations comprising: identifying progress of a user through a collection of electronic books, the progress of the user being based at least in part on a number of pages that have been consumed, the collection of electronic books comprising a plurality of electronic books; causing display of a progress bar indicating the progress of the user through the collection of electronic books, the progress bar indicating the progress of the user by visualizing an amount of consumed text with respect to an amount of unconsumed text; identifying a number of sessions of consumption of an electronic book of the collection of electronic books; causing display of information indicating the number of sessions of consumption of the electronic book; identifying an estimated amount of time to complete the electronic book of the collection of electronic books; and causing display of the estimated amount of time to complete the electronic book. 12. The one or more non-transitory computer-readable storage media of claim 11 , the operations further comprising: causing display of a reading time indicating an amount of time that the user has spent consuming the electronic book during a session. | 0.594156 |
10,057,594 | 12 | 15 | 12. The WTRU of claim 11 , wherein the reference picture list associated with the current prediction unit comprises a plurality of reference pictures, and the processor is further configured to: retrieve a reference picture from the reference picture list associated with the current prediction unit; determine whether a motion vector scaling operation is associated with using the reference picture as a motion vector prediction candidate for performing motion vector prediction; and select the motion vector prediction candidate from the reference picture list associated with the current prediction unit based on the determining. | 12. The WTRU of claim 11 , wherein the reference picture list associated with the current prediction unit comprises a plurality of reference pictures, and the processor is further configured to: retrieve a reference picture from the reference picture list associated with the current prediction unit; determine whether a motion vector scaling operation is associated with using the reference picture as a motion vector prediction candidate for performing motion vector prediction; and select the motion vector prediction candidate from the reference picture list associated with the current prediction unit based on the determining. 15. The WTRU of claim 12 , wherein the processor is further configured to determine that a motion vector scaling operation is not associated with using the reference picture as the motion vector prediction candidate for performing motion vector prediction on a condition that the reference picture has a same POC distance from a picture associated with the current prediction unit as the POC distance between a picture associated with the co-located prediction unit and a reference picture of the co-located prediction unit. | 0.562604 |
7,734,561 | 10 | 11 | 10. The system of claim 1 wherein the learning logic block comprises coupling learning with the policy specifications maintained by the policy specification logic block and reasoning taking place in the reasoning logic block to provide a refined knowledge base pertaining to management of the managed system. | 10. The system of claim 1 wherein the learning logic block comprises coupling learning with the policy specifications maintained by the policy specification logic block and reasoning taking place in the reasoning logic block to provide a refined knowledge base pertaining to management of the managed system. 11. The system of claim 10 wherein learning is done at multiple levels, comprising: a meta specification level; a base specification level; a level covering relations between actions; and a level in which learning from the administrator is achieved. | 0.5 |
9,710,242 | 1 | 4 | 1. A computer-implemented method comprising: receiving a signature of a first language system method call, the first language system method call originating in a first language system, and the receiving performed by a computing device; analyzing the signature of the first language system method call, the analyzing performed by the computing device; determining: zero or more input parameters of the first language system method call, and one or more output parameters of the first language system method call, where: the determining is based on the analyzing, the determining is performed by the computing device, and an output signature of the first language system method call, wherein the output signature of the first language system method call comprises an indication of a number of the one or more output parameters of the first language system method call; and interacting with a second language system, the second language system including a plurality of method implementations, the second language system including a second language, the second language system being distinct with respect to the first language system, and the interacting performed by the computing device; determining an output signature of a second language system method, wherein the output signature of the second language system method comprises an indication of a number of output parameters of the second language system method; calculating fitness values for multiple ones of the plurality of method implementations, each fitness value indicating a fitness of a respective one of the plurality of method implementations relative to the first language system method call; selecting a second language system method implementation from the plurality of method implementations, the selecting based on the interacting, and the selecting performed by the computing device, wherein the selecting is performed based on the calculated fitness values; and wherein the selecting of the second language system method implementation comprises: identifying a parameter type for each output parameter of the output signature of the first language system method call; and for each identified parameter type, determining a type capable of accepting the identified parameter type in the output signature of the second language system method by determining a casting type into which the identified parameter type may be cast without a loss of information; mapping the first language system method call to the selected second language system method, wherein the mapping comprises casting the identified parameter type into the determined casting type, the mapping used when calling the second language system method in response to the first language system method call. | 1. A computer-implemented method comprising: receiving a signature of a first language system method call, the first language system method call originating in a first language system, and the receiving performed by a computing device; analyzing the signature of the first language system method call, the analyzing performed by the computing device; determining: zero or more input parameters of the first language system method call, and one or more output parameters of the first language system method call, where: the determining is based on the analyzing, the determining is performed by the computing device, and an output signature of the first language system method call, wherein the output signature of the first language system method call comprises an indication of a number of the one or more output parameters of the first language system method call; and interacting with a second language system, the second language system including a plurality of method implementations, the second language system including a second language, the second language system being distinct with respect to the first language system, and the interacting performed by the computing device; determining an output signature of a second language system method, wherein the output signature of the second language system method comprises an indication of a number of output parameters of the second language system method; calculating fitness values for multiple ones of the plurality of method implementations, each fitness value indicating a fitness of a respective one of the plurality of method implementations relative to the first language system method call; selecting a second language system method implementation from the plurality of method implementations, the selecting based on the interacting, and the selecting performed by the computing device, wherein the selecting is performed based on the calculated fitness values; and wherein the selecting of the second language system method implementation comprises: identifying a parameter type for each output parameter of the output signature of the first language system method call; and for each identified parameter type, determining a type capable of accepting the identified parameter type in the output signature of the second language system method by determining a casting type into which the identified parameter type may be cast without a loss of information; mapping the first language system method call to the selected second language system method, wherein the mapping comprises casting the identified parameter type into the determined casting type, the mapping used when calling the second language system method in response to the first language system method call. 4. The computer-implemented method of claim 1 , wherein the second language system method is selected based on a method call of the second language system method. | 0.915005 |
10,013,766 | 7 | 8 | 7. A computer-implemented method, comprising: detecting that a target object is within view of a camera associated with a mobile device; determining a duration over which the camera is oriented in a direction of the target object viewed in the camera; determining, based on the duration, an intent of a user to obtain additional information about the target object; capturing an image of the target object using the camera; identifying the target object within the captured image; and performing an action associated with the identified target object based on the intent of the user. | 7. A computer-implemented method, comprising: detecting that a target object is within view of a camera associated with a mobile device; determining a duration over which the camera is oriented in a direction of the target object viewed in the camera; determining, based on the duration, an intent of a user to obtain additional information about the target object; capturing an image of the target object using the camera; identifying the target object within the captured image; and performing an action associated with the identified target object based on the intent of the user. 8. The computer-implemented method of claim 7 , further comprising determining a proximity of the camera to the target object, wherein determining an intent of the user to obtain additional information about the target object comprises determining the intent of the user based on the proximity and the duration. | 0.5 |
9,817,881 | 1 | 6 | 1. A method comprising: receiving, at an external processing unit, speech from a user; processing the speech via an acoustic modeling process and a phoneme evaluation process; scoring Hidden Markov Models (HMMs) in association with the phoneme evaluation process by the following: receiving, at a co-processing unit, HMM information from an external processing unit, wherein the HMM information is derived from a plurality of HMMs, each HMM having a different type of data structure, wherein the different structures comprise Ergodic HMM structures, left-to-right structures, and parallel path left-to-right HMM structures; formatting, with the co-processing unit, the HMM information from each of the plurality of HMMs into a common HMM data structure to access the HMM information based on a priori knowledge of one or more fields and one or more indices in the common HMM data structure, wherein the formatting comprises formatting HMM information from at least one of a plurality of fields of the plurality of HMMs into the common HMM data structure; processing, with the co-processing unit, back pointer data and first HMM state scores for one or more NULL states in the common HMM data structure, each NULL state being a non-emitting state identified by a state-type flag; after processing the back pointer data and the first HMM state scores for each of the one or more NULL states in the common HMM data structure, processing, with the co-processing unit, second HMM state scores for one or more non-NULL states in the common HMM data structure based on at least one predecessor state; transferring the second HMM state scores from the co-processing unit to the external processing unit; and outputting, via the external processing unit, decoded speech based on the second HMM state scores. | 1. A method comprising: receiving, at an external processing unit, speech from a user; processing the speech via an acoustic modeling process and a phoneme evaluation process; scoring Hidden Markov Models (HMMs) in association with the phoneme evaluation process by the following: receiving, at a co-processing unit, HMM information from an external processing unit, wherein the HMM information is derived from a plurality of HMMs, each HMM having a different type of data structure, wherein the different structures comprise Ergodic HMM structures, left-to-right structures, and parallel path left-to-right HMM structures; formatting, with the co-processing unit, the HMM information from each of the plurality of HMMs into a common HMM data structure to access the HMM information based on a priori knowledge of one or more fields and one or more indices in the common HMM data structure, wherein the formatting comprises formatting HMM information from at least one of a plurality of fields of the plurality of HMMs into the common HMM data structure; processing, with the co-processing unit, back pointer data and first HMM state scores for one or more NULL states in the common HMM data structure, each NULL state being a non-emitting state identified by a state-type flag; after processing the back pointer data and the first HMM state scores for each of the one or more NULL states in the common HMM data structure, processing, with the co-processing unit, second HMM state scores for one or more non-NULL states in the common HMM data structure based on at least one predecessor state; transferring the second HMM state scores from the co-processing unit to the external processing unit; and outputting, via the external processing unit, decoded speech based on the second HMM state scores. 6. The method of claim 1 , wherein the processing the second HMM state scores comprises summing a maximum value associated with one or more predecessor states and an observation probability associated with the one or more non-NULL states, wherein the maximum value is based on a state score and a transition probability associated with the one or more predecessor states. | 0.711059 |
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