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9,342,846 | 7 | 8 | 7. A machine-readable hardware storage device having embedded therein a set of instructions which, when executed by a machine, causes execution of the following operations: detecting a numerical rating of a transaction, the numerical rating provided by a user and indicating a negative experience; using a positive sentiment mining tool, mining a sentiment of words in detailed user feedback text that is included with the numerical rating and detecting that the words indicate positive sentiment, responsive to detecting that the words indicate positive sentiment, preparing confirmatory content to present to the user for confirming that the numerical rating indicates a negative experience; displaying the confirmatory content to the user on a first user interface via the Internet; receiving from the user, via the Internet, responsive to displaying the confirmatory content, confirmatory information that confirms that the numerical rating indicates a negative experience; responsive to receiving the confirmatory information, transforming a state of the numerical rating to a state that reconciles the numerical rating and the positive sentiment; using the reconciled numerical rating, preparing content that measures trustworthiness of a seller; and displaying the content that measures trustworthiness of the seller to buyers on a second user interface via the Internet. | 7. A machine-readable hardware storage device having embedded therein a set of instructions which, when executed by a machine, causes execution of the following operations: detecting a numerical rating of a transaction, the numerical rating provided by a user and indicating a negative experience; using a positive sentiment mining tool, mining a sentiment of words in detailed user feedback text that is included with the numerical rating and detecting that the words indicate positive sentiment, responsive to detecting that the words indicate positive sentiment, preparing confirmatory content to present to the user for confirming that the numerical rating indicates a negative experience; displaying the confirmatory content to the user on a first user interface via the Internet; receiving from the user, via the Internet, responsive to displaying the confirmatory content, confirmatory information that confirms that the numerical rating indicates a negative experience; responsive to receiving the confirmatory information, transforming a state of the numerical rating to a state that reconciles the numerical rating and the positive sentiment; using the reconciled numerical rating, preparing content that measures trustworthiness of a seller; and displaying the content that measures trustworthiness of the seller to buyers on a second user interface via the Internet. 8. The machine-readable hardware storage device of claim 7 wherein the positive mining sentiment tool comprises an application for testing words to detect whether the words indicate positive sentiment or negative sentiment. | 0.5 |
8,701,050 | 1 | 16 | 1. A method comprising: outputting, by a computing device and for display at a display device, a graphical keyboard comprising a plurality of character keys; receiving, at the computing device, an indication of a first input gesture, a first portion of the first input gesture indicating a first character key of the plurality of character keys and a second portion of the first input gesture indicating a second character key of the plurality of character keys; determining, by the computing device and based at least in part on the first character key and the second character key, a candidate word; outputting, by the computing device and for display at a region of the display device at which the graphical keyboard is displayed, a gesture completion path extending from the second character key, the second character key being the most recently indicated character key, and the gesture completion path being associated with the candidate word; and selecting, by the computing device and in response to receiving an indication of a second input gesture that substantially traverses the gesture completion path, the candidate word associated with the gesture completion path. | 1. A method comprising: outputting, by a computing device and for display at a display device, a graphical keyboard comprising a plurality of character keys; receiving, at the computing device, an indication of a first input gesture, a first portion of the first input gesture indicating a first character key of the plurality of character keys and a second portion of the first input gesture indicating a second character key of the plurality of character keys; determining, by the computing device and based at least in part on the first character key and the second character key, a candidate word; outputting, by the computing device and for display at a region of the display device at which the graphical keyboard is displayed, a gesture completion path extending from the second character key, the second character key being the most recently indicated character key, and the gesture completion path being associated with the candidate word; and selecting, by the computing device and in response to receiving an indication of a second input gesture that substantially traverses the gesture completion path, the candidate word associated with the gesture completion path. 16. The method of claim 1 , further comprising outputting, by the computing device and for display at the region of the display device at which the graphical keyboard is displayed, a gesture path traced by the first input gesture. | 0.831131 |
9,020,879 | 1 | 6 | 1. A system, comprising: a memory operable to store one or more classification rules; and a processor communicatively coupled to the memory and operable to: retrieve one or more data elements from a data source; identify a structured data element among the one or more data elements; parse the structured data element using one or more filter processes to produce a plurality of tokens; classify the plurality of tokens based at least in part on the one or more classification rules and an ontology, the ontology comprising a plurality of concepts and a plurality of relationships between the concepts; identify a conflict between a first classified token and a second classified token; resolve the conflict by evaluating the first and second classified tokens based at least in part on the ontology; and generate a knowledge assertion comprising the plurality of classified tokens and one or more relationships between the classified tokens. | 1. A system, comprising: a memory operable to store one or more classification rules; and a processor communicatively coupled to the memory and operable to: retrieve one or more data elements from a data source; identify a structured data element among the one or more data elements; parse the structured data element using one or more filter processes to produce a plurality of tokens; classify the plurality of tokens based at least in part on the one or more classification rules and an ontology, the ontology comprising a plurality of concepts and a plurality of relationships between the concepts; identify a conflict between a first classified token and a second classified token; resolve the conflict by evaluating the first and second classified tokens based at least in part on the ontology; and generate a knowledge assertion comprising the plurality of classified tokens and one or more relationships between the classified tokens. 6. The system of claim 1 wherein the processor is further operable to: receive a query comprising a particular classified token; and generate a result comprising: one or more additional classified tokens generated based on information retrieved from the data source; and one or more relationships between the additional classified tokens, wherein each additional classified token has at least one relationship with the particular classified token. | 0.5 |
9,384,267 | 17 | 23 | 17. A non-transitory computer readable storage medium storing one or more programs for execution by one or more processors of a computer system, the one or more programs comprising instructions for: obtaining a partial search query; mapping the partial search query to an entry in a chunk table, the entry in the chunk table having at least one pointer to a complete query in a first language in a token table, wherein an entry in the token table matches a complete query in the first language to a translation of the complete query in a second language; and formatting both a set of complete queries in the first language and the matching translations for display, wherein the set is determined from the pointers for the entry in the chunk table. | 17. A non-transitory computer readable storage medium storing one or more programs for execution by one or more processors of a computer system, the one or more programs comprising instructions for: obtaining a partial search query; mapping the partial search query to an entry in a chunk table, the entry in the chunk table having at least one pointer to a complete query in a first language in a token table, wherein an entry in the token table matches a complete query in the first language to a translation of the complete query in a second language; and formatting both a set of complete queries in the first language and the matching translations for display, wherein the set is determined from the pointers for the entry in the chunk table. 23. The non-transitory computer readable storage medium of claim 17 , the token table further including entries matching complete queries in the first language to expansions in the first language and wherein the one or more programs further comprise instructions for: formatting an expansion of a first complete query in the set of complete queries for display concurrently with a translation of the first complete query. | 0.571283 |
8,090,743 | 10 | 12 | 10. A method for managing documents using a document management system, the document management system comprising a storage unit that stores documents to construct a database and a document processing unit comprising a processor that detects a specific document among newly provided documents and informs the user of an information on the detected document, the method comprising: providing a user with a newly received information service application form that includes a service type section for setting a type of a newly received information service and an informing condition section for detecting a user-concerning document; receiving a newly received information service application input from the user, the newly received information service application input comprising an input that selects the type of the newly received information service from among a general selective dissemination of information service, a legal selective dissemination of information service and a similarity retrieval selective dissemination of information service; monitoring newly received documents in accordance with the newly received information service application input; and informing the user of information on a newly received document that corresponds to an informing condition, wherein if the general selective dissemination of information service is selected as the newly received information service, the document management system receives a retrieval expression from the user as the informing condition, determines whether a newly received document corresponds to the retrieval expression, and informs the user of the information on the newly received document if the newly received document corresponds to the retrieval expression, wherein if the legal selective dissemination of information service is selected as the newly received information service, the document management system receives an input that designates a reference document that was previously stored in the storage unit as the informing condition, extracts a representative value of the reference document, compares the reference document with a corresponding newly received document using the representative value, determines whether a legal status of the reference document is different from that of the corresponding newly received document, and informs the user of the information on the newly received document if the legal status of the reference document is different from that of the corresponding newly received document, wherein if the similarity retrieval selective dissemination of information service is selected as the newly received information service, the document management system receives an input that designates a reference document that was previously stored in the storage unit as the informing condition, determines whether a newly received document is similar to the reference document, and informs the user of the information on the newly received document if the newly received document is similar to the reference document. | 10. A method for managing documents using a document management system, the document management system comprising a storage unit that stores documents to construct a database and a document processing unit comprising a processor that detects a specific document among newly provided documents and informs the user of an information on the detected document, the method comprising: providing a user with a newly received information service application form that includes a service type section for setting a type of a newly received information service and an informing condition section for detecting a user-concerning document; receiving a newly received information service application input from the user, the newly received information service application input comprising an input that selects the type of the newly received information service from among a general selective dissemination of information service, a legal selective dissemination of information service and a similarity retrieval selective dissemination of information service; monitoring newly received documents in accordance with the newly received information service application input; and informing the user of information on a newly received document that corresponds to an informing condition, wherein if the general selective dissemination of information service is selected as the newly received information service, the document management system receives a retrieval expression from the user as the informing condition, determines whether a newly received document corresponds to the retrieval expression, and informs the user of the information on the newly received document if the newly received document corresponds to the retrieval expression, wherein if the legal selective dissemination of information service is selected as the newly received information service, the document management system receives an input that designates a reference document that was previously stored in the storage unit as the informing condition, extracts a representative value of the reference document, compares the reference document with a corresponding newly received document using the representative value, determines whether a legal status of the reference document is different from that of the corresponding newly received document, and informs the user of the information on the newly received document if the legal status of the reference document is different from that of the corresponding newly received document, wherein if the similarity retrieval selective dissemination of information service is selected as the newly received information service, the document management system receives an input that designates a reference document that was previously stored in the storage unit as the informing condition, determines whether a newly received document is similar to the reference document, and informs the user of the information on the newly received document if the newly received document is similar to the reference document. 12. The method according to claim 10 , wherein the informing condition is a retrieval expression, and the step of monitoring comprises detecting the specific document which correspond to the retrieval expression among the newly received documents. | 0.810292 |
9,396,269 | 1 | 6 | 1. A system comprising: one or more processors; a database that stores maps of associations between search-related information and entities that are members of a social network; and memory storing computer-readable instructions by the one or more processors to perform operations including: performing an analysis of at least one of terms or phrases of searches performed by a plurality of members of the social network to infer interests of the plurality of members; determining, based on the analysis, that a first number of the searches is associated with a first interest, the first number of the searches being performed by a first group of members included in the social network; determining, based on the analysis, that a second number of the searches is associated with a second interest, the second number of the searches being performed by a second group of members included in the social network; forming, in the database, a first subnetwork of the social network, the first subnetwork including the first group of members; forming, in the database, a second subnetwork of the social network, the second subnetwork including the second group of members; receiving a search query from a user; determining search results responsive to the search query; returning the determined search results; determining that the search query corresponds with the first interest; and returning, at least partly in response to determining that the search query corresponds with the first interest, a link to at least one member of the first group of members. | 1. A system comprising: one or more processors; a database that stores maps of associations between search-related information and entities that are members of a social network; and memory storing computer-readable instructions by the one or more processors to perform operations including: performing an analysis of at least one of terms or phrases of searches performed by a plurality of members of the social network to infer interests of the plurality of members; determining, based on the analysis, that a first number of the searches is associated with a first interest, the first number of the searches being performed by a first group of members included in the social network; determining, based on the analysis, that a second number of the searches is associated with a second interest, the second number of the searches being performed by a second group of members included in the social network; forming, in the database, a first subnetwork of the social network, the first subnetwork including the first group of members; forming, in the database, a second subnetwork of the social network, the second subnetwork including the second group of members; receiving a search query from a user; determining search results responsive to the search query; returning the determined search results; determining that the search query corresponds with the first interest; and returning, at least partly in response to determining that the search query corresponds with the first interest, a link to at least one member of the first group of members. 6. The system of claim 1 , wherein the operations further include mapping, in the database, an entity of the entities of the social network based at least in part on prior search queries of the entity. | 0.876989 |
8,359,202 | 7 | 8 | 7. The method of claim 1 , wherein generating the audible output comprises using an audio recording. | 7. The method of claim 1 , wherein generating the audible output comprises using an audio recording. 8. The method of claim 7 , wherein the audio recording is an audio recording of a person speaking the selected words. | 0.5 |
9,275,147 | 1 | 7 | 1. A method performed by one or more computers, the method comprising: receiving a search string from a user device; selecting a plurality of candidate query suggestions based on the search string; determining, for each candidate query suggestion, a probability for the candidate query suggestion based on a count in a query log of the number of times that the plurality of candidate query suggestions were submitted as search queries and a count in the query log of the number of times that the candidate query was submitted as a search query; determining a measure of query completeness for the search string based on an aggregation of the determined probabilities, including determining a probability of receiving the N most probable query suggestions for the search string, wherein N is an integer greater than zero; comparing the measure of query completeness to a threshold measure of query completeness; and providing one or more specific query suggestions to the user device, selected from a plurality of specific query suggestions for the search string, when the measure of query completeness exceeds the threshold measure of query completeness; or providing one or more general query suggestions to the user device, selected from a plurality of general query suggestions for the search string, when the measure of query completeness does not exceed the threshold measure of query completeness. | 1. A method performed by one or more computers, the method comprising: receiving a search string from a user device; selecting a plurality of candidate query suggestions based on the search string; determining, for each candidate query suggestion, a probability for the candidate query suggestion based on a count in a query log of the number of times that the plurality of candidate query suggestions were submitted as search queries and a count in the query log of the number of times that the candidate query was submitted as a search query; determining a measure of query completeness for the search string based on an aggregation of the determined probabilities, including determining a probability of receiving the N most probable query suggestions for the search string, wherein N is an integer greater than zero; comparing the measure of query completeness to a threshold measure of query completeness; and providing one or more specific query suggestions to the user device, selected from a plurality of specific query suggestions for the search string, when the measure of query completeness exceeds the threshold measure of query completeness; or providing one or more general query suggestions to the user device, selected from a plurality of general query suggestions for the search string, when the measure of query completeness does not exceed the threshold measure of query completeness. 7. The method of claim 1 , wherein comparing the measure of query completeness to a threshold measure of query completeness comprises comparing an entropy of the probabilities to a threshold sum. | 0.830435 |
9,224,385 | 1 | 8 | 1. A method for providing information to a user, the method comprising: detecting entry in an audio recognition mode by a computing device, the detecting including receiving an audio stream; analyzing, by a processor of the computing device, one or more segments of the audio stream received by the computing device before a complete audio stream is received, wherein analyzing includes: first checking the one or more segments to determine if the audio stream includes speech; and second checking the one or more segments to determine if the audio stream is from a song, wherein at least part of the first checking is performed while the second checking is being performed; determining a first confidence score from the first checking and determining a second confidence score from the second checking; displaying a possible candidate on a display based on a partial identification of the audio stream using the first and second confidence scores while continuing checking additional segments as the audio stream is received until an end of the audio stream or until the first and second confidence scores determine that the audio stream has been identified as speech or music; and presenting results on the display based on the completed identification of the audio stream. | 1. A method for providing information to a user, the method comprising: detecting entry in an audio recognition mode by a computing device, the detecting including receiving an audio stream; analyzing, by a processor of the computing device, one or more segments of the audio stream received by the computing device before a complete audio stream is received, wherein analyzing includes: first checking the one or more segments to determine if the audio stream includes speech; and second checking the one or more segments to determine if the audio stream is from a song, wherein at least part of the first checking is performed while the second checking is being performed; determining a first confidence score from the first checking and determining a second confidence score from the second checking; displaying a possible candidate on a display based on a partial identification of the audio stream using the first and second confidence scores while continuing checking additional segments as the audio stream is received until an end of the audio stream or until the first and second confidence scores determine that the audio stream has been identified as speech or music; and presenting results on the display based on the completed identification of the audio stream. 8. The method as recited in claim 1 , further including: performing, by the computing device, a search when the audio stream has been identified as speech, the search being performed on the identified speech. | 0.666667 |
8,041,746 | 1 | 12 | 1. A computer-implemented method for mapping a first schema to a second schema, the method comprising: identifying a first schema that includes a plurality of first data element definitions, each of the first data element definitions defining a semantic of a data portion in first electronic documents that are generated according to a format of the first schema, wherein each of the first data element definitions in the first schema is uniquely identified by a respective first name; receiving an indication that the first schema is to be mapped to a second schema, the first and second schemas being different from each other such that a computer system configured according to the second schema is unable to semantically interpret the first electronic documents, wherein a naming rule specifies a process to generate a name for a data element from a human-understandable description for the data element by performing linguistic analysis on the human-understandable description for the data element, wherein each of multiple second data element definitions in the second schema is uniquely identified by a respective second name generated using the naming rule, wherein the first names that identify the first data element definitions in the first schema are not generated using the naming rule; generating a new name for each of the first data element definitions from the human-understandable description for each of the first data element definitions by applying the process that is specified by the naming rule to the human-understandable description for each of the first data element definitions, wherein the second names and the new names are defined by Core Components Technical Specification (CCTS) standard, and wherein the first names are not defined by the CCTS standard; and mapping at least one of the first data element definitions in the first schema to a corresponding one of the second data element definitions in the second schema based on the new name for the one of the first data element definitions in the first schema matching the second name of the one of the second data element definition in the second schema. | 1. A computer-implemented method for mapping a first schema to a second schema, the method comprising: identifying a first schema that includes a plurality of first data element definitions, each of the first data element definitions defining a semantic of a data portion in first electronic documents that are generated according to a format of the first schema, wherein each of the first data element definitions in the first schema is uniquely identified by a respective first name; receiving an indication that the first schema is to be mapped to a second schema, the first and second schemas being different from each other such that a computer system configured according to the second schema is unable to semantically interpret the first electronic documents, wherein a naming rule specifies a process to generate a name for a data element from a human-understandable description for the data element by performing linguistic analysis on the human-understandable description for the data element, wherein each of multiple second data element definitions in the second schema is uniquely identified by a respective second name generated using the naming rule, wherein the first names that identify the first data element definitions in the first schema are not generated using the naming rule; generating a new name for each of the first data element definitions from the human-understandable description for each of the first data element definitions by applying the process that is specified by the naming rule to the human-understandable description for each of the first data element definitions, wherein the second names and the new names are defined by Core Components Technical Specification (CCTS) standard, and wherein the first names are not defined by the CCTS standard; and mapping at least one of the first data element definitions in the first schema to a corresponding one of the second data element definitions in the second schema based on the new name for the one of the first data element definitions in the first schema matching the second name of the one of the second data element definition in the second schema. 12. The computer program product of claim 1 , further comprising: presenting the mapping of the at least one of the first data element definitions in the first schema to the corresponding one of the second data element definitions in the second schema to a user as a suggestion which the user can at least accept or reject; and receiving user input that the user accepts the presented mapping; wherein the mapping of the at least one of the first data element definitions in the first schema to the corresponding one of the second data element definitions in the second schema is performed in response to receiving the user input. | 0.5 |
8,352,248 | 17 | 18 | 17. The apparatus of claim 13 , wherein: the speech encoder means includes an analysis-by-synthesis encoder means, which determines an encoder version of speech excitation for the input speech signal; the speech recognizer means determines a recognizer version of speech excitation for the corresponding dictionary speech element; and the difference encoder means calculates excitation differences between the encoder version of the speech excitation and the recognizer version of the speech excitation. | 17. The apparatus of claim 13 , wherein: the speech encoder means includes an analysis-by-synthesis encoder means, which determines an encoder version of speech excitation for the input speech signal; the speech recognizer means determines a recognizer version of speech excitation for the corresponding dictionary speech element; and the difference encoder means calculates excitation differences between the encoder version of the speech excitation and the recognizer version of the speech excitation. 18. The apparatus of claim 17 , wherein: the speech encoder means determines a first set of excitation pulse locations; the speech recognizer means determines a second set of excitation pulse locations; and the difference encoder means calculates, for each excitation pulse in the first set of excitation pulses, a location difference between a first location of the excitation pulse in the first set of excitation pulses and a second location of a corresponding excitation pulse in the second set of excitation pulse locations. | 0.5 |
9,462,355 | 1 | 2 | 1. A method for delivering a media source, the method comprising: determining, by a processor, a first plurality of keywords from a portion of the media source, wherein the first plurality of keywords is generated from a language analysis process on words collected from the portion of the media source; selecting, by the processor, a second keyword from the first plurality of keywords, wherein the selecting the second keyword comprises scoring each of the first plurality of keywords based on a source of each of the first plurality of keywords, wherein the second keyword is determined based upon one or more of the first plurality of keywords that have a score above a threshold; searching, by the processor, a memory to identify a reference item related to the media source based upon the second keyword, wherein the reference item is external to the media source; embedding, by the processor, the reference item into the media source; and delivering, by the processor, the media source embedded with the reference item to a customer premises. | 1. A method for delivering a media source, the method comprising: determining, by a processor, a first plurality of keywords from a portion of the media source, wherein the first plurality of keywords is generated from a language analysis process on words collected from the portion of the media source; selecting, by the processor, a second keyword from the first plurality of keywords, wherein the selecting the second keyword comprises scoring each of the first plurality of keywords based on a source of each of the first plurality of keywords, wherein the second keyword is determined based upon one or more of the first plurality of keywords that have a score above a threshold; searching, by the processor, a memory to identify a reference item related to the media source based upon the second keyword, wherein the reference item is external to the media source; embedding, by the processor, the reference item into the media source; and delivering, by the processor, the media source embedded with the reference item to a customer premises. 2. The method of claim 1 , wherein the determining the first plurality of keywords comprises: determining whether the media source includes a closed caption text; decoding the closed caption text when the media source includes the closed caption text; and extracting an audio signal and performing a speech-to-text conversion on the audio signal that is extracted when the media source does not include the closed caption text. | 0.5 |
9,621,725 | 7 | 8 | 7. The method of claim 5 , further comprising: applying a service layer to fine tune category mapping of said team/department; and generating a model that includes a final category for each team/department name. | 7. The method of claim 5 , further comprising: applying a service layer to fine tune category mapping of said team/department; and generating a model that includes a final category for each team/department name. 8. The method of claim 7 , wherein said category comprises a categories grouping for each team/department name based on edit distance. | 0.5 |
9,471,611 | 8 | 9 | 8. The method of claim 6 , wherein the event notification component is flexibly extended by adding additional components, the additional components being selected from at least one of a fax component, an e-mail component, a voice component, and a policy actions and notifications component. | 8. The method of claim 6 , wherein the event notification component is flexibly extended by adding additional components, the additional components being selected from at least one of a fax component, an e-mail component, a voice component, and a policy actions and notifications component. 9. The method of claim 8 , wherein the content is attached to the notification. | 0.785326 |
10,067,937 | 5 | 6 | 5. The non-transitory computer-readable medium of claim 1 , wherein the translation output further comprises text in the second language for rendering in a user interface of the video messaging application contemporaneously with a corresponding video segment from which the audio data is collected. | 5. The non-transitory computer-readable medium of claim 1 , wherein the translation output further comprises text in the second language for rendering in a user interface of the video messaging application contemporaneously with a corresponding video segment from which the audio data is collected. 6. The non-transitory computer-readable medium of claim 5 , wherein the indicator further comprises an icon in a user interface rendered in a second display associated with the second computing device. | 0.5 |
8,560,449 | 1 | 12 | 1. A method of modifying a set of rules of a payment transaction system, the method comprising: in response to a transaction initiated with a payment card of a user, electronically receiving from a point of sale terminal a transaction request or an authorization request associated with the transaction; responsive to the transaction request or authorization request, electronically transmitting to a first electronic device associated with the user a request for input from the user; using a second computing device associated with an entity different from the user, receiving the input from the user, wherein the second computing device is programmed to apply a set of rules associated with the payment card of the user; applying the set of rules to the transaction request or authorization request; responsive to the received input from the user, automatically modifying, using the second computing device, the set of rules based on the received input from the user for application of the modified set of rules to a future transaction, a future transaction request, or a future authorization request associated with the user; applying the modified set of rules to the future transaction, the future transaction request or the future authorization request associated with the user; and modifying one or more rules from the set of rules based on additional input provided by the user prior to the transaction. | 1. A method of modifying a set of rules of a payment transaction system, the method comprising: in response to a transaction initiated with a payment card of a user, electronically receiving from a point of sale terminal a transaction request or an authorization request associated with the transaction; responsive to the transaction request or authorization request, electronically transmitting to a first electronic device associated with the user a request for input from the user; using a second computing device associated with an entity different from the user, receiving the input from the user, wherein the second computing device is programmed to apply a set of rules associated with the payment card of the user; applying the set of rules to the transaction request or authorization request; responsive to the received input from the user, automatically modifying, using the second computing device, the set of rules based on the received input from the user for application of the modified set of rules to a future transaction, a future transaction request, or a future authorization request associated with the user; applying the modified set of rules to the future transaction, the future transaction request or the future authorization request associated with the user; and modifying one or more rules from the set of rules based on additional input provided by the user prior to the transaction. 12. The method of claim 1 , wherein the user is an account holder of an account associated with the payment card or a card holder of the account associated with the payment card. | 0.763926 |
10,115,440 | 5 | 6 | 5. The apparatus of claim 1 , wherein a connector of the plurality of connectors comprises a first vertical conductor extending between an upper metal interconnect layer and a lower metal interconnect layer for the non-volatile memory, and a second vertical conductor extending between the upper metal interconnect layer and a word line layer exposed at one of the word line contact regions. | 5. The apparatus of claim 1 , wherein a connector of the plurality of connectors comprises a first vertical conductor extending between an upper metal interconnect layer and a lower metal interconnect layer for the non-volatile memory, and a second vertical conductor extending between the upper metal interconnect layer and a word line layer exposed at one of the word line contact regions. 6. The apparatus of claim 5 , wherein a distance between adjacent first vertical conductors is smaller between word line contact regions than within word line contact regions. | 0.5 |
9,740,297 | 16 | 17 | 16. A non-transitory computer-readable storage medium storing instructions that, when executed by a processor, cause a computing device to: receive first image data captured using one or more imaging sensors associated with the computing device; analyze the first image data to determine a first relative orientation between the computing device and at least a first portion of an object represented in the first image data; display a plurality of selectable elements on a display element associated with the computing device; receive second image data captured using the one or more imaging sensors; analyze the second image data to determine a second relative orientation between the computing device and at least a second portion of the object represented in the second image data; determine a first rate associated with a first change in orientation between the first relative orientation and the second relative orientation; display a first movement of a selection element to a first selectable element of the plurality of selectable elements on the display element such that a first direction of the first movement corresponds to the first change in orientation and a second rate of the first movement corresponds to the first rate of the first change in orientation; receive third image data captured using the one or more imaging sensors; analyze the third image data to determine a third relative orientation between the computing device and at least a third portion of the object represented in the third image data; determine a third rate of a second change in orientation between the second relative orientation and the third relative orientation; display a second movement of a second selectable element of the plurality of selectable elements on the display element such that a second direction of the second movement corresponds to the second change in orientation and a fourth rate of the second movement corresponds to the third rate of the second change in orientation; receive a selection of the second selectable element; and perform an action on the computing device associated with the selection of the second selectable element. | 16. A non-transitory computer-readable storage medium storing instructions that, when executed by a processor, cause a computing device to: receive first image data captured using one or more imaging sensors associated with the computing device; analyze the first image data to determine a first relative orientation between the computing device and at least a first portion of an object represented in the first image data; display a plurality of selectable elements on a display element associated with the computing device; receive second image data captured using the one or more imaging sensors; analyze the second image data to determine a second relative orientation between the computing device and at least a second portion of the object represented in the second image data; determine a first rate associated with a first change in orientation between the first relative orientation and the second relative orientation; display a first movement of a selection element to a first selectable element of the plurality of selectable elements on the display element such that a first direction of the first movement corresponds to the first change in orientation and a second rate of the first movement corresponds to the first rate of the first change in orientation; receive third image data captured using the one or more imaging sensors; analyze the third image data to determine a third relative orientation between the computing device and at least a third portion of the object represented in the third image data; determine a third rate of a second change in orientation between the second relative orientation and the third relative orientation; display a second movement of a second selectable element of the plurality of selectable elements on the display element such that a second direction of the second movement corresponds to the second change in orientation and a fourth rate of the second movement corresponds to the third rate of the second change in orientation; receive a selection of the second selectable element; and perform an action on the computing device associated with the selection of the second selectable element. 17. The non-transitory computer-readable storage medium of claim 16 , wherein the instructions, when executed by the processor, further cause the computing device to: determine a relative motion of the first portion of the object over a period of time between capture of the first image data and capture of the second image data. | 0.668347 |
7,668,825 | 1 | 3 | 1. A query processing system for processing a query having one or more query terms using formally represented knowledge against a corpus of documents, the system comprising: a knowledge base containing a plurality of pieces of formally represented knowledge, wherein each piece of formally represented knowledge further comprises an item that has been edited or analyzed, the formally represented knowledge further comprising one or more synsets wherein each synset contains a group of terms that have a same meaning, one or more taxonomies wherein each taxonomy contains one or more synsets in a subject matter area that are organized from a synset having a general meaning to a synset having a specific meaning, one or more ontologies wherein each ontology contains one or more synsets associated with an area of interest and one or more facets wherein each facet is associated with a particular ontology and wherein a document is associated with the facet when the document contains the one or more synsets associated with the facet; and a computer system having one or more software pieces each having a plurality of lines of computer instructions wherein the computer instructions are executed by the computer system, the software pieces further comprising a query engine that expands the one or more query terms of the query using the one or more synsets and the one or more taxonomies in the knowledge base to generate an expanded query, selects an interpretation of a concept from the expanded query and the corpus of documents, selects one or more facets that match the interpretation of the expanded query based on the corpus of documents and performs a deep concept query using the interpretation of the expanded query and the selected one or more facets against the corpus of documents. | 1. A query processing system for processing a query having one or more query terms using formally represented knowledge against a corpus of documents, the system comprising: a knowledge base containing a plurality of pieces of formally represented knowledge, wherein each piece of formally represented knowledge further comprises an item that has been edited or analyzed, the formally represented knowledge further comprising one or more synsets wherein each synset contains a group of terms that have a same meaning, one or more taxonomies wherein each taxonomy contains one or more synsets in a subject matter area that are organized from a synset having a general meaning to a synset having a specific meaning, one or more ontologies wherein each ontology contains one or more synsets associated with an area of interest and one or more facets wherein each facet is associated with a particular ontology and wherein a document is associated with the facet when the document contains the one or more synsets associated with the facet; and a computer system having one or more software pieces each having a plurality of lines of computer instructions wherein the computer instructions are executed by the computer system, the software pieces further comprising a query engine that expands the one or more query terms of the query using the one or more synsets and the one or more taxonomies in the knowledge base to generate an expanded query, selects an interpretation of a concept from the expanded query and the corpus of documents, selects one or more facets that match the interpretation of the expanded query based on the corpus of documents and performs a deep concept query using the interpretation of the expanded query and the selected one or more facets against the corpus of documents. 3. The system of claim 1 , wherein the query engine further comprises a facet display engine that, when a particular synset associated with a particular facet matches a particular query term, triggers the particular facet and displays the particular facet. | 0.645429 |
7,975,223 | 6 | 7 | 6. The method of claim 1 , after moving the portion of content to the second location in the document, further comprising receiving one or more edits to the portion of content after the portion of content has been moved to the second location in the document. | 6. The method of claim 1 , after moving the portion of content to the second location in the document, further comprising receiving one or more edits to the portion of content after the portion of content has been moved to the second location in the document. 7. The method of claim 6 , prior to causing a tracked movement of a portion of content of the document from a first location in the document to a second location in the document, storing data representing a state of the document before a portion of content is moved from a first location in the document to a second location in the document and storing data representing any tracked changes made to the portion of content after the portion of content is moved from a first location in the document to a second location in the document. | 0.5 |
8,989,785 | 8 | 13 | 8. A system for communication comprising: means for receiving an audio voice message from a caller; means for transcribing the audio voice message to produce text; means for providing a text message including the text and an identifier that uniquely identifies the specific audio voice message to link to the specific audio voice message; and means for transmitting the text message to the recipient's mobile telephone. | 8. A system for communication comprising: means for receiving an audio voice message from a caller; means for transcribing the audio voice message to produce text; means for providing a text message including the text and an identifier that uniquely identifies the specific audio voice message to link to the specific audio voice message; and means for transmitting the text message to the recipient's mobile telephone. 13. The system of claim 8 , further comprising means for providing options associated with the specific audio voice message to the recipient in response to the recipient linking to the specific audio voice message via the identifier. | 0.5 |
8,775,420 | 1 | 4 | 1. A method comprising: receiving a search request by at least one server computer, the search request identifying search criteria; cause, by the at least one server computer, a search of geographically referenced information using the search criteria to identify search results, the search results comprising a plurality of result items, each result item of the plurality having associated text for a display of the search results result items and having an associated location; for each result item of the plurality, the at least one server computer determining a distance of the result item from a user's location using the user's location and the result item's associated location; and causing, by the at least one server computer, the display of the search results, wherein the display of the search results comprises the text for each of the plurality of result items, and at least one appearance characteristic of the text varies for at least one result item of the search results based on the at least one result item's distance from the user's location, the result item's distance from the user's location is determined using the user's location and the at least one result item's associated location and one of the plurality of result items closest in distance to the user's location relative to other ones of the plurality of result items is displayed more prominently than the other ones of the plurality of result items, wherein the at least one appearance characteristic is selected from the group consisting of font size, font style, color, shading, three-dimensional height, associated features, and animation. | 1. A method comprising: receiving a search request by at least one server computer, the search request identifying search criteria; cause, by the at least one server computer, a search of geographically referenced information using the search criteria to identify search results, the search results comprising a plurality of result items, each result item of the plurality having associated text for a display of the search results result items and having an associated location; for each result item of the plurality, the at least one server computer determining a distance of the result item from a user's location using the user's location and the result item's associated location; and causing, by the at least one server computer, the display of the search results, wherein the display of the search results comprises the text for each of the plurality of result items, and at least one appearance characteristic of the text varies for at least one result item of the search results based on the at least one result item's distance from the user's location, the result item's distance from the user's location is determined using the user's location and the at least one result item's associated location and one of the plurality of result items closest in distance to the user's location relative to other ones of the plurality of result items is displayed more prominently than the other ones of the plurality of result items, wherein the at least one appearance characteristic is selected from the group consisting of font size, font style, color, shading, three-dimensional height, associated features, and animation. 4. The method of claim 1 , wherein the geographically referenced information comprises other users. | 0.842357 |
7,752,162 | 5 | 6 | 5. The computer system of claim 4 , wherein said conditions on measures comprise any of Boolean conditions, thresholds for outliers, statistical conditions, trends, and comparisons. | 5. The computer system of claim 4 , wherein said conditions on measures comprise any of Boolean conditions, thresholds for outliers, statistical conditions, trends, and comparisons. 6. The system of claim 5 , wherein said conditions on measures are represented as a dependency graph. | 0.5 |
9,667,788 | 1 | 9 | 1. A method for analyzing electronic customer communication data, generating behavioral assessment data and generating a responsive communication, which method comprises: receiving, by a server, electronic customer communication data of two or more types, wherein the server is configured to provide a user interface comprising a web site, web portal, or virtual portal, and wherein at least one of the two or more types of electronic customer communication data comprises social media data, update status, media feed, social media review, social media data stream, social media profile or social media account setup; identify a customer associated with the electronic customer communication data received by the server; analyzing the electronic customer communication data by applying a predetermined linguistic-based psychological behavioral model to the electronic customer communication data for that identified customer; generating behavioral assessment data by the contact center based on said analyzing, the behavioral assessment data providing a personality type for the analyzed electronic customer communication data for that identified customer; generating a responsive communication based on the generated behavioral assessment data; and providing the responsive communication via the user interface. | 1. A method for analyzing electronic customer communication data, generating behavioral assessment data and generating a responsive communication, which method comprises: receiving, by a server, electronic customer communication data of two or more types, wherein the server is configured to provide a user interface comprising a web site, web portal, or virtual portal, and wherein at least one of the two or more types of electronic customer communication data comprises social media data, update status, media feed, social media review, social media data stream, social media profile or social media account setup; identify a customer associated with the electronic customer communication data received by the server; analyzing the electronic customer communication data by applying a predetermined linguistic-based psychological behavioral model to the electronic customer communication data for that identified customer; generating behavioral assessment data by the contact center based on said analyzing, the behavioral assessment data providing a personality type for the analyzed electronic customer communication data for that identified customer; generating a responsive communication based on the generated behavioral assessment data; and providing the responsive communication via the user interface. 9. The method of claim 1 , wherein the responsive communication comprises a responsive e-mail, electronic post, social media feed or telephonic response. | 0.625 |
9,552,398 | 4 | 9 | 4. The method of claim 1 , wherein providing the reordered search results for presentation comprises: determining that the domain has an indicator associated with the domain; and providing, for presentation, the indicator in proximity to a particular search result associated with the domain. | 4. The method of claim 1 , wherein providing the reordered search results for presentation comprises: determining that the domain has an indicator associated with the domain; and providing, for presentation, the indicator in proximity to a particular search result associated with the domain. 9. The method of claim 4 , wherein providing the indicator in proximity to the particular search result for presentation comprises: providing, for presentation, the indicator adjacent to a URL associated with the particular search result. | 0.674863 |
9,819,622 | 1 | 9 | 1. A computer program product embodied on a non-transitory computer readable medium, comprising code executable by a computer having a processor and a graphical user interface and arranged to communicate with at least one audio file messaging software-as-a-service platform, to cause the computer to carry out the following steps: accessing the at least one audio file messaging software-as-a-service platform; communicating to the at least one audio file messaging software-as-a-service platform a set of first information, the set of first information including a message personalized for an intended recipient; selecting, via the graphical user interface, at least one category of pre-existing recording to be retrieved; retrieving, from the at least one audio messaging software-as-a-service platform, at least one pre-existing recording, said pre-existing recording associated with the at least one selected category; selecting, via the graphical user interface, a desired phrase from within a pre-existing recording; communicating the selection of the desired phrase to the at least one audio file messaging software-as-a-service platform in the form of non-audio data identifying a phrase from an audio recording, the at least one audio file messaging software-as-a-service platform comprising an audio extraction engine that (i) receives the non-audio data identifying the phrase together with an instance of the audio recording, (ii) identifies a portion of the audio recording where the phrase is likely to be found at least in part by mapping each word in the phrase to one and only vocal interval determined to exist in the audio recording, (iii) extracts the portion of the audio recording into a short snippet; and (iv) writes the short snippet into a database; and directing the at least one audio file messaging software-as-a-service platform, via the graphical user interface, to generate, output, and deliver an audio message note for the intended recipient, wherein the music message note is based on the short snippet. | 1. A computer program product embodied on a non-transitory computer readable medium, comprising code executable by a computer having a processor and a graphical user interface and arranged to communicate with at least one audio file messaging software-as-a-service platform, to cause the computer to carry out the following steps: accessing the at least one audio file messaging software-as-a-service platform; communicating to the at least one audio file messaging software-as-a-service platform a set of first information, the set of first information including a message personalized for an intended recipient; selecting, via the graphical user interface, at least one category of pre-existing recording to be retrieved; retrieving, from the at least one audio messaging software-as-a-service platform, at least one pre-existing recording, said pre-existing recording associated with the at least one selected category; selecting, via the graphical user interface, a desired phrase from within a pre-existing recording; communicating the selection of the desired phrase to the at least one audio file messaging software-as-a-service platform in the form of non-audio data identifying a phrase from an audio recording, the at least one audio file messaging software-as-a-service platform comprising an audio extraction engine that (i) receives the non-audio data identifying the phrase together with an instance of the audio recording, (ii) identifies a portion of the audio recording where the phrase is likely to be found at least in part by mapping each word in the phrase to one and only vocal interval determined to exist in the audio recording, (iii) extracts the portion of the audio recording into a short snippet; and (iv) writes the short snippet into a database; and directing the at least one audio file messaging software-as-a-service platform, via the graphical user interface, to generate, output, and deliver an audio message note for the intended recipient, wherein the music message note is based on the short snippet. 9. The computer program product of claim 1 , further comprising: receiving an advertisement from a sponsor to be displayed to the sender; displaying the advertisement on the graphical user interface; determining whether the sender has met an exposure threshold for exposure to the advertisement; and debiting a cost associated with generating, outputting, and delivering an audio message note from the sponsor. | 0.5 |
7,606,856 | 21 | 24 | 21. A system for presenting topical information referenced during a communication, the system comprising: a communication interface for communicating with a remote endpoint via a communication network; a topic key phrase recognizer for recognizing a topic key phrase during a communication between a first party and a second party; a topic database for associating a topic descriptor with the topic key phrase; a communication information database for storing information about the communication; a descriptor management processor for identifying the topic descriptor associated with the recognized topic key phrase in the topic database, for determining a topic descriptor weight associated with the identified topic descriptor, for determining a topic descriptor presentation threshold based on a relationship between the first party and the second party retrieved from the communication information database, and for comparing the topic descriptor weight with the determined topic descriptor presentation threshold; and a user interface for presenting the topic descriptor in conjunction with the descriptor management processor based on the comparison. | 21. A system for presenting topical information referenced during a communication, the system comprising: a communication interface for communicating with a remote endpoint via a communication network; a topic key phrase recognizer for recognizing a topic key phrase during a communication between a first party and a second party; a topic database for associating a topic descriptor with the topic key phrase; a communication information database for storing information about the communication; a descriptor management processor for identifying the topic descriptor associated with the recognized topic key phrase in the topic database, for determining a topic descriptor weight associated with the identified topic descriptor, for determining a topic descriptor presentation threshold based on a relationship between the first party and the second party retrieved from the communication information database, and for comparing the topic descriptor weight with the determined topic descriptor presentation threshold; and a user interface for presenting the topic descriptor in conjunction with the descriptor management processor based on the comparison. 24. The system of claim 21 wherein the descriptor management processor is configured to identify the topic descriptor associated with the topic key phrase by performing a lookup in a topic database. | 0.829016 |
9,195,769 | 14 | 22 | 14. A server computer comprising a processor and a non-transitory computer-readable medium, the non-transitory computer-readable medium comprising code executable by the processor to implement a method for evaluation of an entity by a target user based at least on stored data about the target user, wherein the entity is an entity of a set of entities, and evaluation is related to the entity, the method comprising: receiving, at a server computer, entity data relating to a particular entity in the set of entities, wherein the entity data includes a relevance based on a rating and a weight based on a relationship with the target user for a particular user that provided the entity data through a particular data source; determining, by the server computer, a set of entity evaluations to request from the target user based on the weight and the relevance; from the set of entity evaluations to request, generating, at the server computer, a set of predicted entity evaluations for one or more entities relevant to the target user based on the entity data, user data, and relevance; determining an order of relevance of the relevant entities based at least in part on the relevance and the weight to increase accuracy of the predicted entity evaluations; and communicating, from the server computer to the target user, the order of relevance of the one or more relevant entities; after communicating the order of relevance, receiving, from a user device, evaluation data from the target user that is based on an evaluation received through input via the user device; in response to receiving the evaluation data, increasing the accuracy of the predicted entity evaluations by computing a similarity among the target user and the particular user. | 14. A server computer comprising a processor and a non-transitory computer-readable medium, the non-transitory computer-readable medium comprising code executable by the processor to implement a method for evaluation of an entity by a target user based at least on stored data about the target user, wherein the entity is an entity of a set of entities, and evaluation is related to the entity, the method comprising: receiving, at a server computer, entity data relating to a particular entity in the set of entities, wherein the entity data includes a relevance based on a rating and a weight based on a relationship with the target user for a particular user that provided the entity data through a particular data source; determining, by the server computer, a set of entity evaluations to request from the target user based on the weight and the relevance; from the set of entity evaluations to request, generating, at the server computer, a set of predicted entity evaluations for one or more entities relevant to the target user based on the entity data, user data, and relevance; determining an order of relevance of the relevant entities based at least in part on the relevance and the weight to increase accuracy of the predicted entity evaluations; and communicating, from the server computer to the target user, the order of relevance of the one or more relevant entities; after communicating the order of relevance, receiving, from a user device, evaluation data from the target user that is based on an evaluation received through input via the user device; in response to receiving the evaluation data, increasing the accuracy of the predicted entity evaluations by computing a similarity among the target user and the particular user. 22. The server computer of claim 14 , wherein the order of relevance is based at least in part on a frequency in which an entity has been previously queried. | 0.930898 |
8,447,767 | 16 | 18 | 16. A system for multimedia information retrieval comprising: a search engine for querying an associated multimedia collection with a first component of a multimedia query and for querying at least a part of the queried multimedia collection with a second component of the multimedia query; a first comparison component for generating a first comparison measure between the first query component and a respective object in the collection for a first media type; a second comparison component for generating a second comparison measure between the second query component and a respective object in the collection for the second media type; a multimedia scoring component for generating aggregated scores for each of a set of objects in the collection based on the first comparison measure and the second comparison measure for the respective object, the multimedia scoring component applying an aggregating function which aggregates the first and second comparison measure in which a first confidence weighting is applied to the first comparison measure which is independent of the second comparison measure and a second confidence weighting is applied to the second comparison measure which is dependent on the first comparison measure, wherein the aqqreqatinq function is of general format:
s cw ( q,o )=α a N ( s a ( q,o )ƒ( s a ( q,o ), r a ( o,q ),θ a ))+α b N ( s b ( q,o ) g ( s a ( q,o ), r a ( o,q ), s b ( q,o ), r b ( o,q ),θ b ) wherein 0<α a <1, 0<α b <1 and α b =1−α a ; S cw is the aggregated score; a represents the first media type; b represents the second media type; s a (q,o) and s b (q,o) are similarity scores between the query q and the object o for the first and second media types respectively; r a (o,q) and r b (o,q) are rankinqs of the object o given by the respective similarity scores s a (q,o) and s b (q,o), with respect to other objects in the collection; ƒ is a function of at least one of r a (o,q) and s a (q,o) and optionally also of θ a ; g is a function of at least one of r a (o,q) and s a (q,o) and at least one of s b (q,o) and r b (o,q) and optionally also of θ b ; θ a is a set of one or more parameters; θ b is a set of one or more parameters; and N represents an optional normalizing operator; and a processor for implementing the search engine, first and second comparison components, and multimedia scoring component. | 16. A system for multimedia information retrieval comprising: a search engine for querying an associated multimedia collection with a first component of a multimedia query and for querying at least a part of the queried multimedia collection with a second component of the multimedia query; a first comparison component for generating a first comparison measure between the first query component and a respective object in the collection for a first media type; a second comparison component for generating a second comparison measure between the second query component and a respective object in the collection for the second media type; a multimedia scoring component for generating aggregated scores for each of a set of objects in the collection based on the first comparison measure and the second comparison measure for the respective object, the multimedia scoring component applying an aggregating function which aggregates the first and second comparison measure in which a first confidence weighting is applied to the first comparison measure which is independent of the second comparison measure and a second confidence weighting is applied to the second comparison measure which is dependent on the first comparison measure, wherein the aqqreqatinq function is of general format:
s cw ( q,o )=α a N ( s a ( q,o )ƒ( s a ( q,o ), r a ( o,q ),θ a ))+α b N ( s b ( q,o ) g ( s a ( q,o ), r a ( o,q ), s b ( q,o ), r b ( o,q ),θ b ) wherein 0<α a <1, 0<α b <1 and α b =1−α a ; S cw is the aggregated score; a represents the first media type; b represents the second media type; s a (q,o) and s b (q,o) are similarity scores between the query q and the object o for the first and second media types respectively; r a (o,q) and r b (o,q) are rankinqs of the object o given by the respective similarity scores s a (q,o) and s b (q,o), with respect to other objects in the collection; ƒ is a function of at least one of r a (o,q) and s a (q,o) and optionally also of θ a ; g is a function of at least one of r a (o,q) and s a (q,o) and at least one of s b (q,o) and r b (o,q) and optionally also of θ b ; θ a is a set of one or more parameters; θ b is a set of one or more parameters; and N represents an optional normalizing operator; and a processor for implementing the search engine, first and second comparison components, and multimedia scoring component. 18. The system of claim 16 , wherein the system is configured for outputting retrieved objects from the collection based on their aggregated scores. | 0.551515 |
8,380,731 | 1 | 6 | 1. A computer-based searching method comprising: a) receiving, at a computer, a search concept that includes a plurality of principal words; b) determining a set of semantically similar words for at least one of the principal words, wherein the principal words are extracted from the search concept using a natural language processing utility; c) receiving, at the computer, user input for improving the set of semantically similar words and a degree of membership for individual words within the set of semantically similar words to generate improvement in search results, wherein the user input includes an addition of one or more words to the set of semantically similar words; d) calculating, based on user input, a degree of membership for each word that reflects a semantic similarity in meaning to the principal word of the set with which each word is associated; e) performing a search using at least the set of semantically similar words; f) computing a score for each search result based at least on the degrees of membership for each of the semantically similar words used in the search and that at least one of the principal words, wherein computing the score for each search result comprises: determining the degree of membership corresponding to each of the semantically similar words included in the search result and the at least one of the principal words to create a set of membership weights; and determining which membership weight among the determined set of membership weights is a minimum membership weight; selecting the minimum membership weight among the determined set of membership weights to be the score for the search result; and g) sorting and displaying results of the search using the computed scores. | 1. A computer-based searching method comprising: a) receiving, at a computer, a search concept that includes a plurality of principal words; b) determining a set of semantically similar words for at least one of the principal words, wherein the principal words are extracted from the search concept using a natural language processing utility; c) receiving, at the computer, user input for improving the set of semantically similar words and a degree of membership for individual words within the set of semantically similar words to generate improvement in search results, wherein the user input includes an addition of one or more words to the set of semantically similar words; d) calculating, based on user input, a degree of membership for each word that reflects a semantic similarity in meaning to the principal word of the set with which each word is associated; e) performing a search using at least the set of semantically similar words; f) computing a score for each search result based at least on the degrees of membership for each of the semantically similar words used in the search and that at least one of the principal words, wherein computing the score for each search result comprises: determining the degree of membership corresponding to each of the semantically similar words included in the search result and the at least one of the principal words to create a set of membership weights; and determining which membership weight among the determined set of membership weights is a minimum membership weight; selecting the minimum membership weight among the determined set of membership weights to be the score for the search result; and g) sorting and displaying results of the search using the computed scores. 6. The computer-based searching method according to claim 1 wherein determining a set of semantically similar words comprises determining the set of semantically similar words utilizing a computer-based utility. | 0.610701 |
7,882,089 | 17 | 19 | 17. The article of claim 16 , wherein the machine-readable medium has stored thereon further instructions that, if executed, further direct the computing platform to store the collection of digital information by storing a plurality of entries in an XML format. | 17. The article of claim 16 , wherein the machine-readable medium has stored thereon further instructions that, if executed, further direct the computing platform to store the collection of digital information by storing a plurality of entries in an XML format. 19. The article of claim 17 , wherein the machine-readable medium has stored thereon further instructions that, if executed, further direct the computing platform to store the query expression in an XPath format. | 0.502347 |
9,412,362 | 3 | 4 | 3. The method of claim 1 , wherein if the script text is determined to have occurred in the audio data, further comprising: transcribing the utterance containing the script to produce an utterance transcription; comparing the script text to the utterance transcription; determining a script accuracy. | 3. The method of claim 1 , wherein if the script text is determined to have occurred in the audio data, further comprising: transcribing the utterance containing the script to produce an utterance transcription; comparing the script text to the utterance transcription; determining a script accuracy. 4. The method of claim 3 , further comprising evaluating a compliance of the audio data with a script requirement threshold by comparing the determined script accuracy to the script requirement threshold. | 0.5 |
9,600,086 | 9 | 15 | 9. A method of operating an electronic device comprising the steps of: detecting a content entry; receiving a request by a user for a content prediction; identifying a most probable next content prediction by using a personalized and learning database, wherein the personalized and learning database comprises recently used data, said data comprising any of: one or more word associations, one or more context associations, one or more sensitivity associations, one or more Uniform Resource Locators, and one or more electronic mail addresses, and by using content stored in user interface memory, wherein the prediction is a customized depth of prediction, where depth of prediction enables the user to indicate whether a character, word, or phrase is predicted, said identifying comprising: storing the personalized and learning database in memory; storing content and sensitivity associations of entered content in an associations memory; storing one or more language dictionaries as chosen by a user in a main dictionaries memory; receiving, by the personalized and learning database, inputs from the associations memory, the main dictionaries memory, and a recent entries memory; using the inputs, re-sorting said recently used data in the personalized and learning database combined with content used by the user and consequently customizing re-ordering of content based on personalized usage; and using the re-ordered content stored in the personalized and learning database and using content stored in user interface memory to provide a customized depth of prediction in predicting the most probable completion alternative by allowing the user to control the depth of prediction by providing user input that indicates whether the entire prediction or one or more portions of the prediction are accepted and wherein depth of prediction indicates whether a predicted character, predicted word, or predicted words encompassed within a phrase all at once is accepted; displaying the most probable next content prediction; determining whether a user has accepted the most probable next content prediction; and adding the most probable next content prediction to the content entry when the user has accepted the most probable next content prediction; wherein a user interface is provided that comprises a navigation key having a first set of controls and a second set of controls; wherein said first set of controls are configured for acceptance or non-acceptance of the most probable next content prediction currently displayed at the display when in an editing mode and said second set of controls are configured for changing or overriding the most probable next content prediction currently displayed at the display when in the editing mode; wherein said first of controls are configured for scrolling a cursor right one character at a time or scrolling the cursor left one character at a time when said first set of controls are in a navigation mode; wherein said second set of controls are configured for scrolling the cursor down one line at a time or scrolling the cursor up one line at a time, when said second set of controls are in the navigation mode; and wherein: a right control of said first set of controls is configured for, in navigation mode and in a hold and press mode, jumping the cursor to the right one word at a time; a left control of said first set of controls is configured for, in navigation mode and in the hold and press mode, jumping the cursor left one word at a time; the left control being further configured for, in editing mode and in the hold and press mode, dismissing prediction and locking a last key press entry. | 9. A method of operating an electronic device comprising the steps of: detecting a content entry; receiving a request by a user for a content prediction; identifying a most probable next content prediction by using a personalized and learning database, wherein the personalized and learning database comprises recently used data, said data comprising any of: one or more word associations, one or more context associations, one or more sensitivity associations, one or more Uniform Resource Locators, and one or more electronic mail addresses, and by using content stored in user interface memory, wherein the prediction is a customized depth of prediction, where depth of prediction enables the user to indicate whether a character, word, or phrase is predicted, said identifying comprising: storing the personalized and learning database in memory; storing content and sensitivity associations of entered content in an associations memory; storing one or more language dictionaries as chosen by a user in a main dictionaries memory; receiving, by the personalized and learning database, inputs from the associations memory, the main dictionaries memory, and a recent entries memory; using the inputs, re-sorting said recently used data in the personalized and learning database combined with content used by the user and consequently customizing re-ordering of content based on personalized usage; and using the re-ordered content stored in the personalized and learning database and using content stored in user interface memory to provide a customized depth of prediction in predicting the most probable completion alternative by allowing the user to control the depth of prediction by providing user input that indicates whether the entire prediction or one or more portions of the prediction are accepted and wherein depth of prediction indicates whether a predicted character, predicted word, or predicted words encompassed within a phrase all at once is accepted; displaying the most probable next content prediction; determining whether a user has accepted the most probable next content prediction; and adding the most probable next content prediction to the content entry when the user has accepted the most probable next content prediction; wherein a user interface is provided that comprises a navigation key having a first set of controls and a second set of controls; wherein said first set of controls are configured for acceptance or non-acceptance of the most probable next content prediction currently displayed at the display when in an editing mode and said second set of controls are configured for changing or overriding the most probable next content prediction currently displayed at the display when in the editing mode; wherein said first of controls are configured for scrolling a cursor right one character at a time or scrolling the cursor left one character at a time when said first set of controls are in a navigation mode; wherein said second set of controls are configured for scrolling the cursor down one line at a time or scrolling the cursor up one line at a time, when said second set of controls are in the navigation mode; and wherein: a right control of said first set of controls is configured for, in navigation mode and in a hold and press mode, jumping the cursor to the right one word at a time; a left control of said first set of controls is configured for, in navigation mode and in the hold and press mode, jumping the cursor left one word at a time; the left control being further configured for, in editing mode and in the hold and press mode, dismissing prediction and locking a last key press entry. 15. The method of operating an electronic device as defined in claim 9 , further comprising the steps of: retrieving one or more alternate predictive content from the personalized and learning database; displaying the one or more alternate predictive content; and reviewing the one or more alternate predictive content by a user using one or more controls of the navigation key. | 0.5 |
8,184,001 | 1 | 4 | 1. An apparatus comprising: a motion sensor configured to detect motion of an object in a field of view of the apparatus; a wireless communication network interface configured to receive dynamic context-aware content in response to the detection motion; and a user interface output device configured to provide a user interpretable output based on the received context-aware content, wherein the user interface output device shifts from a low-power state to an active state only after presence of the object has been detected with the motion sensor being stationary, and wherein upon the shift from the low-power state to the active state, a request is sent to synchronize local data and obtain profile information. | 1. An apparatus comprising: a motion sensor configured to detect motion of an object in a field of view of the apparatus; a wireless communication network interface configured to receive dynamic context-aware content in response to the detection motion; and a user interface output device configured to provide a user interpretable output based on the received context-aware content, wherein the user interface output device shifts from a low-power state to an active state only after presence of the object has been detected with the motion sensor being stationary, and wherein upon the shift from the low-power state to the active state, a request is sent to synchronize local data and obtain profile information. 4. The apparatus of claim 1 , wherein the display panel is an Organic Light Emitting Diode (OLED). | 0.877805 |
9,124,908 | 1 | 8 | 1. A method, comprising: receiving, by a system including a processor, a plurality of user-generated comments associated with media content, wherein the plurality of user-generated comments are annotated to the media content during presentations of the media content by a group of communication devices; identifying, by the system from the plurality of user-generated comments, a cluster of comments associated with a segment of the media content based on a frequency of the plurality of user-generated comments; filtering, by the system, the cluster of comments based on subject matter to generate a filtered cluster of comments; identifying, by the system, a sample segment according to a range of the segment of the media content that is to be transmitted to a recipient device; and transmitting, by the system, the filtered cluster of comments and the sample segment to the recipient device. | 1. A method, comprising: receiving, by a system including a processor, a plurality of user-generated comments associated with media content, wherein the plurality of user-generated comments are annotated to the media content during presentations of the media content by a group of communication devices; identifying, by the system from the plurality of user-generated comments, a cluster of comments associated with a segment of the media content based on a frequency of the plurality of user-generated comments; filtering, by the system, the cluster of comments based on subject matter to generate a filtered cluster of comments; identifying, by the system, a sample segment according to a range of the segment of the media content that is to be transmitted to a recipient device; and transmitting, by the system, the filtered cluster of comments and the sample segment to the recipient device. 8. The method of claim 1 , comprising transmitting to the recipient device a communication link to the sample segment. | 0.889098 |
9,268,459 | 16 | 19 | 16. The system of claim 15 , wherein identifying the design example comprises: for each of a subset of the plurality of design examples, comparing a transformation cost corresponding to the second set of UI components with a threshold value. | 16. The system of claim 15 , wherein identifying the design example comprises: for each of a subset of the plurality of design examples, comparing a transformation cost corresponding to the second set of UI components with a threshold value. 19. The system of claim 16 , wherein the transformation cost includes a cost associated with geometrically transforming a UI component in the second set to make it substantially identical to a UI component in the first set. | 0.5 |
9,514,109 | 14 | 16 | 14. A computer-implemented system for scoring speech, comprising: one or more data processors; one or more computer-readable mediums encoded with instructions for commanding the one or more data processors to execute steps that include: performing automatic speech recognition on the speech sample with an automatic speech recognizer to generate a transcription of the sample, the automatic speech recognizer comprising a computerized language model and a computerized acoustic model trained based on speech samples from multiple speakers, and storing words of the transcription in a first data structure; associating the words of the transcription with part of speech labels based on an analysis of the words; generating part of speech sequences based on the part of speech labels and storing the part of speech sequences in a second data structure; generating a first vector comprising the part of speech sequences and associated first numerical weights, each first numerical weight indicating a relative frequency of the associated part of speech sequence in the speech sample or a presence of the associated part of speech sequence in the speech sample; calculating a similarity score between the first vector and each of multiple score-level vectors, each score-level vector comprising (i) part of speech sequences occurring in a set of speech samples of a training corpus, each speech sample of the set being assigned a same score, and (ii) associated second numerical weights, each second numerical weight being based on a relative frequency of the associated part of speech sequence in the set and a relative importance of the associated part of speech sequence in differentiating speech samples assigned the score of the set from speech samples assigned different scores; and comparing the similarity scores and scoring the speech sample with a computerized scoring model based on the comparison. | 14. A computer-implemented system for scoring speech, comprising: one or more data processors; one or more computer-readable mediums encoded with instructions for commanding the one or more data processors to execute steps that include: performing automatic speech recognition on the speech sample with an automatic speech recognizer to generate a transcription of the sample, the automatic speech recognizer comprising a computerized language model and a computerized acoustic model trained based on speech samples from multiple speakers, and storing words of the transcription in a first data structure; associating the words of the transcription with part of speech labels based on an analysis of the words; generating part of speech sequences based on the part of speech labels and storing the part of speech sequences in a second data structure; generating a first vector comprising the part of speech sequences and associated first numerical weights, each first numerical weight indicating a relative frequency of the associated part of speech sequence in the speech sample or a presence of the associated part of speech sequence in the speech sample; calculating a similarity score between the first vector and each of multiple score-level vectors, each score-level vector comprising (i) part of speech sequences occurring in a set of speech samples of a training corpus, each speech sample of the set being assigned a same score, and (ii) associated second numerical weights, each second numerical weight being based on a relative frequency of the associated part of speech sequence in the set and a relative importance of the associated part of speech sequence in differentiating speech samples assigned the score of the set from speech samples assigned different scores; and comparing the similarity scores and scoring the speech sample with a computerized scoring model based on the comparison. 16. The system of claim 14 , wherein the steps further comprise providing a feedback about grammatical usage based on the part of speech sequences. | 0.5 |
8,010,526 | 12 | 15 | 12. A method comprising: monitoring entity instances during a first interval, each entity instance being one of a plurality of types of entity instances; determining from the entity instances monitored during the first interval a first ranked list of entity instances in which the types of entity instances are ranked according to the number of times each type of entity instance occurred during the first interval, the first ranked list having a first cardinality of types of entity instances; monitoring entity instances during a second interval, each entity instance being one of the plurality of types of entity instances; determining from the entity instances monitored during the second interval a second ranked list of entity instances in which the types of entity instances are ranked according to the number of times each type of entity instance occurred during the second interval, the second ranked list having the first cardinality of types of entity instances; and merging the first ranked list and the second ranked list into a third ranked list of entities instances in which the types of entity instances are ranked according to the number of times each type of entity instance occurred during the first interval and the second interval; wherein monitoring entity instances during a first interval comprises: entering monitored entity instances in a first table; determining if an entity instance in the first table has a count that is greater than a threshold count; entering the entity instance in a second table if the entity instance in the first table has a count that is greater than the threshold count; determining if the second table has the first cardinality of entries; and ending the first interval if the second table has the first cardinality of entries. | 12. A method comprising: monitoring entity instances during a first interval, each entity instance being one of a plurality of types of entity instances; determining from the entity instances monitored during the first interval a first ranked list of entity instances in which the types of entity instances are ranked according to the number of times each type of entity instance occurred during the first interval, the first ranked list having a first cardinality of types of entity instances; monitoring entity instances during a second interval, each entity instance being one of the plurality of types of entity instances; determining from the entity instances monitored during the second interval a second ranked list of entity instances in which the types of entity instances are ranked according to the number of times each type of entity instance occurred during the second interval, the second ranked list having the first cardinality of types of entity instances; and merging the first ranked list and the second ranked list into a third ranked list of entities instances in which the types of entity instances are ranked according to the number of times each type of entity instance occurred during the first interval and the second interval; wherein monitoring entity instances during a first interval comprises: entering monitored entity instances in a first table; determining if an entity instance in the first table has a count that is greater than a threshold count; entering the entity instance in a second table if the entity instance in the first table has a count that is greater than the threshold count; determining if the second table has the first cardinality of entries; and ending the first interval if the second table has the first cardinality of entries. 15. The method of claim 12 , wherein the measurement interval is defined by the number of entity instance types monitored. | 0.906009 |
7,698,298 | 22 | 23 | 22. A system for electronically managing remote review of documents for legal purposes, the system comprising: a repository of electronically stored documents; a host system including; an export tool, the export tool configured to export: one or more of the documents for remote review by a reviewer lacking access to the repository; and an electronic decision tool for remote use by the reviewer and configured to enable the reviewer to electronically designate discovery categorizations or discovery treatments of the documents, the designated discovery categorizations or discovery treatments assisting a disclosing party receiving a discovery request for document production from a requesting party in identifying documents to be produced to the requesting party in response to a discovery request for document production, such that privileged document content is protected from inadvertent production and waiver of at least one of attorney client privilege and attorney work product doctrine; and an import tool configured to import designations of the reviewer back into the repository thereby enabling electronic integration of remotely made decisions into the repository; the electronic decision tool electronically recording designated discovery categories or discovery treatments and creating an electronic file of the designated discovery categories or discovery treatments, the electronic file of the designated discovery categories or discovery treatments being a stand-alone file independent of the documents and electronic copies of the documents. | 22. A system for electronically managing remote review of documents for legal purposes, the system comprising: a repository of electronically stored documents; a host system including; an export tool, the export tool configured to export: one or more of the documents for remote review by a reviewer lacking access to the repository; and an electronic decision tool for remote use by the reviewer and configured to enable the reviewer to electronically designate discovery categorizations or discovery treatments of the documents, the designated discovery categorizations or discovery treatments assisting a disclosing party receiving a discovery request for document production from a requesting party in identifying documents to be produced to the requesting party in response to a discovery request for document production, such that privileged document content is protected from inadvertent production and waiver of at least one of attorney client privilege and attorney work product doctrine; and an import tool configured to import designations of the reviewer back into the repository thereby enabling electronic integration of remotely made decisions into the repository; the electronic decision tool electronically recording designated discovery categories or discovery treatments and creating an electronic file of the designated discovery categories or discovery treatments, the electronic file of the designated discovery categories or discovery treatments being a stand-alone file independent of the documents and electronic copies of the documents. 23. The system of claim 22 wherein the electronic-file includes fields that match with corresponding fields in document records related to the documents. | 0.5 |
10,147,051 | 9 | 16 | 9. A computer program product comprising a non-transitory computer readable storage medium having a computer readable program stored therein, wherein the computer readable program, when executed on a computing device, causes the computing device to: responsive to identifying an input question as an explanatory question, decompose the explanatory question into one or more explanatory queries; identify one or more passages within a corpus of information that comprise an explanatory clause that provides an explanatory answer to the explanatory question based on pre-determined explanatory clause terms, wherein a passage within the one or more passages within the corpus of information that comprises the explanatory clause is identified by the computer readable program further causing the computing device to: compare each identified clause within a passage to a set of previously identified explanatory clauses; and responsive to the identified clause within a passage corresponding to one of the set of previously identified explanatory clauses, tag the clause within the passage with an ‘EXPLANATORY’ tag; receive hypothesis evidence with one or passages comprising explanatory clauses from the corpus of information; generate one or more candidate explanatory answers based on hypothesis evidence; rank and merge the one or more candidate explanatory answers; and output the one or more candidate explanatory answers. | 9. A computer program product comprising a non-transitory computer readable storage medium having a computer readable program stored therein, wherein the computer readable program, when executed on a computing device, causes the computing device to: responsive to identifying an input question as an explanatory question, decompose the explanatory question into one or more explanatory queries; identify one or more passages within a corpus of information that comprise an explanatory clause that provides an explanatory answer to the explanatory question based on pre-determined explanatory clause terms, wherein a passage within the one or more passages within the corpus of information that comprises the explanatory clause is identified by the computer readable program further causing the computing device to: compare each identified clause within a passage to a set of previously identified explanatory clauses; and responsive to the identified clause within a passage corresponding to one of the set of previously identified explanatory clauses, tag the clause within the passage with an ‘EXPLANATORY’ tag; receive hypothesis evidence with one or passages comprising explanatory clauses from the corpus of information; generate one or more candidate explanatory answers based on hypothesis evidence; rank and merge the one or more candidate explanatory answers; and output the one or more candidate explanatory answers. 16. The computer program product of claim 9 , wherein the computer readable program to identify the passage within the one or more passages within the corpus of information that comprises the explanatory clause further causes the computing device to: append the identified clause to a set of previously identified explanatory clauses. | 0.695811 |
8,423,349 | 15 | 18 | 15. A system comprising: one or more processors; memory; a phrase-generation module, stored in the memory and executable on the one or more processors to generate multiple phrases for association with one or more aspects of user accounts associated with corresponding users, the one or more aspects of the user accounts for executing a payment transaction; a phrase-filtering module, stored in the memory and executable on the one or more processors to filter out one or more of the generated phrases based at least in part on a commonality of one or more words of a phrase; and a phrase-association module, stored in the memory and executable on the one or more processors to associate one phrase that has not been filtered out with an aspect of a user account for executing a payment transaction. | 15. A system comprising: one or more processors; memory; a phrase-generation module, stored in the memory and executable on the one or more processors to generate multiple phrases for association with one or more aspects of user accounts associated with corresponding users, the one or more aspects of the user accounts for executing a payment transaction; a phrase-filtering module, stored in the memory and executable on the one or more processors to filter out one or more of the generated phrases based at least in part on a commonality of one or more words of a phrase; and a phrase-association module, stored in the memory and executable on the one or more processors to associate one phrase that has not been filtered out with an aspect of a user account for executing a payment transaction. 18. A system as recited in claim 15 , wherein the phrase-filtering module filters out: (i) phrases that have previously been associated with users, and (ii) phrases that sound like phrases that have previously been associated with users. | 0.527888 |
9,495,350 | 1 | 15 | 1. A method comprising: associating speakers with respective segments of an audio speech file to yield associated speaker segments; generating, via a processor using automatic speech recognition of audio in the audio speech file, expertise vectors for one or more of the speakers, the expertise vectors comprising scores based on: (i) number of times the speakers have spoken about a topic in the audio speech file by searching the associated speaker segments for a term associated with the topic, and (ii) at least one of word classes, usages, styles, or behaviors of the speakers; and ranking the speakers as experts based on the expertise vectors; presenting, by the processor, the ranking of the speakers as experts based on the expertise vectors; tagging the associated speaker segments having the term with keyword tags; and matching a respective segment from the associated speaker segments with a speaker, the respective segment having a keyword tag. | 1. A method comprising: associating speakers with respective segments of an audio speech file to yield associated speaker segments; generating, via a processor using automatic speech recognition of audio in the audio speech file, expertise vectors for one or more of the speakers, the expertise vectors comprising scores based on: (i) number of times the speakers have spoken about a topic in the audio speech file by searching the associated speaker segments for a term associated with the topic, and (ii) at least one of word classes, usages, styles, or behaviors of the speakers; and ranking the speakers as experts based on the expertise vectors; presenting, by the processor, the ranking of the speakers as experts based on the expertise vectors; tagging the associated speaker segments having the term with keyword tags; and matching a respective segment from the associated speaker segments with a speaker, the respective segment having a keyword tag. 15. The method of claim 1 , further comprising inferring an expertise in a different topic based on an expert rank in the topic. | 0.870183 |
9,477,720 | 11 | 12 | 11. A system, comprising: one or more computers; and a computer-readable medium coupled to the one or more computers having instructions stored thereon which, when executed by the one or more computers, cause the one or more computers to perform operations comprising: receiving, at a computing device, a search query from a first user, the first user associated with a computer-implemented social graph that includes a plurality of members socially connected to the first user through the computer-implemented social graph; receiving, at the computing device, search results responsive to the search query, the search results each associated with a respective electronic document stored in one or more computer-readable storage media; determining that a particular electronic document is associated with a plurality of endorsements; identifying a subset of members of the plurality of members socially connected to the first user through the computer-implemented social graph, each member of the subset of members respectively associated with an endorsement of the plurality of endorsements; identifying an affinity of each member of the subset of the members with respect to the particular electronic document; selecting a subset of the plurality of endorsements based on the affinity of each member of the subset of the members with respect to the particular electronic document; and transmitting instructions to display the search results to the first user, the instructions comprising instructions to display one or more endorsement annotations associated with the subset of the plurality of endorsements proximate to the search result associated with the particular electronic document, the one or more endorsement annotations each including a text snippet describing the endorsement associated with the endorsement annotation, the text snippet including i) an identification of the respective member of the subset of members, ii) text indicating a service used by the respective member of the subset of members to generate the endorsement, and iii) a web-based link associated with the endorsement to direct the first user to the content of the endorsement within the service, wherein the text indicating the service used by the respective member of the subset of members to generate the endorsement is distinct from the web-based link. | 11. A system, comprising: one or more computers; and a computer-readable medium coupled to the one or more computers having instructions stored thereon which, when executed by the one or more computers, cause the one or more computers to perform operations comprising: receiving, at a computing device, a search query from a first user, the first user associated with a computer-implemented social graph that includes a plurality of members socially connected to the first user through the computer-implemented social graph; receiving, at the computing device, search results responsive to the search query, the search results each associated with a respective electronic document stored in one or more computer-readable storage media; determining that a particular electronic document is associated with a plurality of endorsements; identifying a subset of members of the plurality of members socially connected to the first user through the computer-implemented social graph, each member of the subset of members respectively associated with an endorsement of the plurality of endorsements; identifying an affinity of each member of the subset of the members with respect to the particular electronic document; selecting a subset of the plurality of endorsements based on the affinity of each member of the subset of the members with respect to the particular electronic document; and transmitting instructions to display the search results to the first user, the instructions comprising instructions to display one or more endorsement annotations associated with the subset of the plurality of endorsements proximate to the search result associated with the particular electronic document, the one or more endorsement annotations each including a text snippet describing the endorsement associated with the endorsement annotation, the text snippet including i) an identification of the respective member of the subset of members, ii) text indicating a service used by the respective member of the subset of members to generate the endorsement, and iii) a web-based link associated with the endorsement to direct the first user to the content of the endorsement within the service, wherein the text indicating the service used by the respective member of the subset of members to generate the endorsement is distinct from the web-based link. 12. The system of claim 11 , wherein the endorsement annotations each further comprise a thumbnail image of the respective other user. | 0.875233 |
9,600,842 | 1 | 10 | 1. An apparatus, comprising: a device including at least one input device, at least one display, and memory in communication with at least one hardware processor; and a browser installed on the memory of the device for allowing access, utilizing the at least one input device and the at least one hardware processor, to a system including a hardware server, the system configured for: identifying at least parts of a plurality of original documents including a plurality of original values, the plurality of original documents including a first document including first values and a second document including second values; processing at least a part of the first document and at least a part of the second document, resulting in at least one data structure including at least one of the plurality of original values of at least one of the plurality of original documents; receiving one or more indications for one or more of the original values for adding, in connection with at least one computer-readable Extensible Markup Language (XML)-compliant data document, a corresponding one or more computer-readable semantic tags in association with the one or more original values; associating the one or more computer-readable semantic tags with the one or more original values; causing output of a presentation that is based on at least a portion of the at least one data structure, the presentation capable of including at least a portion of the original values including the at least one original value, where the system is configured such that, based on the at least one data structure, a change to the at least one original value results in a corresponding change in a subsequent output of the presentation; and causing output of the at least one computer-readable XML-compliant data document that is eXtensible Business Reporting Language (XBRL)-compliant and is based on at least a portion of at least one data structure, the at least one computer-readable XML-compliant data document capable of including a plurality of line items at least one of which utilizes at least a portion of the original values including the at least one original value and at least some of the one or more computer-readable semantic tags, where the system is configured such that, based on the at least one data structure, a change to the at least one original value results in a corresponding change in a subsequent output of the at least one computer-readable XML-compliant data document; said apparatus configured for: receiving user input utilizing the browser, and displaying the at least one computer-readable XML-compliant data document utilizing the browser, after the user input. | 1. An apparatus, comprising: a device including at least one input device, at least one display, and memory in communication with at least one hardware processor; and a browser installed on the memory of the device for allowing access, utilizing the at least one input device and the at least one hardware processor, to a system including a hardware server, the system configured for: identifying at least parts of a plurality of original documents including a plurality of original values, the plurality of original documents including a first document including first values and a second document including second values; processing at least a part of the first document and at least a part of the second document, resulting in at least one data structure including at least one of the plurality of original values of at least one of the plurality of original documents; receiving one or more indications for one or more of the original values for adding, in connection with at least one computer-readable Extensible Markup Language (XML)-compliant data document, a corresponding one or more computer-readable semantic tags in association with the one or more original values; associating the one or more computer-readable semantic tags with the one or more original values; causing output of a presentation that is based on at least a portion of the at least one data structure, the presentation capable of including at least a portion of the original values including the at least one original value, where the system is configured such that, based on the at least one data structure, a change to the at least one original value results in a corresponding change in a subsequent output of the presentation; and causing output of the at least one computer-readable XML-compliant data document that is eXtensible Business Reporting Language (XBRL)-compliant and is based on at least a portion of at least one data structure, the at least one computer-readable XML-compliant data document capable of including a plurality of line items at least one of which utilizes at least a portion of the original values including the at least one original value and at least some of the one or more computer-readable semantic tags, where the system is configured such that, based on the at least one data structure, a change to the at least one original value results in a corresponding change in a subsequent output of the at least one computer-readable XML-compliant data document; said apparatus configured for: receiving user input utilizing the browser, and displaying the at least one computer-readable XML-compliant data document utilizing the browser, after the user input. 10. The apparatus of claim 1 , wherein the system is configured such that the at least one computer-readable XML-compliant data document is encapsulated, in machine-readable form, with at least one reusable document including routines that are capable of being utilized for data value formatting and data value collating in connection with the at least one computer-readable XML-compliant data document as well as other computer-readable XML-compliant data documents insofar as the other computer-readable XML-compliant data documents meet requirements set forth in the at least one reusable document. | 0.91003 |
9,472,209 | 1 | 11 | 1. A method for deep tagging a recording, the method comprising the steps of: a computer filtering, from recorded audio of a communication between a plurality of participants, wherein the recorded audio comprises speech from one or more of the plurality of participants, a non-speech sound that was transmitted to the plurality of participants; the computer automatically determining that the non-speech sound corresponds to a type of sound, and in response, automatically associating a descriptive term with a time of occurrence of the non-speech sound within the recorded audio to form a searchable tag, wherein the descriptive term includes a phonetic translation of the non-speech sound; and the computer storing the searchable tag as metadata of the recorded audio. | 1. A method for deep tagging a recording, the method comprising the steps of: a computer filtering, from recorded audio of a communication between a plurality of participants, wherein the recorded audio comprises speech from one or more of the plurality of participants, a non-speech sound that was transmitted to the plurality of participants; the computer automatically determining that the non-speech sound corresponds to a type of sound, and in response, automatically associating a descriptive term with a time of occurrence of the non-speech sound within the recorded audio to form a searchable tag, wherein the descriptive term includes a phonetic translation of the non-speech sound; and the computer storing the searchable tag as metadata of the recorded audio. 11. The method of claim 1 , wherein the step of determining that the non-speech sound corresponds to a type of sound, further comprises, the computer determining that the type of sound is in a list of preferences indicating that the type of sound should be tagged. | 0.640327 |
7,949,643 | 8 | 9 | 8. The apparatus of claim 7 , the processing device, in response to the executable instructions, is further operative to: normalize the document goodness factor, the author rank and the web location rank; and generate the rating factor for the UGC data field by combining the normalized document goodness factor, the normalized author rank and the normalized web location rank. | 8. The apparatus of claim 7 , the processing device, in response to the executable instructions, is further operative to: normalize the document goodness factor, the author rank and the web location rank; and generate the rating factor for the UGC data field by combining the normalized document goodness factor, the normalized author rank and the normalized web location rank. 9. The apparatus of claim 8 , wherein the generation of the rating factor includes supervised learning. | 0.5 |
8,725,511 | 15 | 17 | 15. A computer-readable storage medium having instructions stored which, when executed by a computing device, result in the computing device performing operations comprising: comparing received speech to a first grammar based on a database, to yield a comparison; and when the comparison is below a threshold: compiling a second grammar based on data added to the database after compilation of the first grammar; and comparing the received speech to the second grammar. | 15. A computer-readable storage medium having instructions stored which, when executed by a computing device, result in the computing device performing operations comprising: comparing received speech to a first grammar based on a database, to yield a comparison; and when the comparison is below a threshold: compiling a second grammar based on data added to the database after compilation of the first grammar; and comparing the received speech to the second grammar. 17. The computer-readable storage medium of claim 15 , wherein the data is obtained from one of a table, a list, and an update database. | 0.757143 |
9,195,735 | 1 | 7 | 1. An information extracting server comprising: a collecting unit configured to collect a text in which a keyword of interest indicating information of interest that a user is interested in appears, the keyword of interest, and a time of creation of the text; a keyword extracting unit configured to extract a keyword included in the text except for the keyword of interest, and the time of creation; a local hot word extracting unit configured to extract the keyword having a time score obtained on the basis of an appearance frequency of the keyword in a time interval, which is a period T1 backward from the time of creation, exceeding a first threshold value and a local score on the basis of the appearance frequency of the keyword in a local area indicating a range of a specific topic exceeding a second threshold value as a local hot word, and also extract the extracted time interval of the extracted keyword and the keyword of interest corresponding to the keyword; and a local hot word storing unit configured to store the extracted local hot word, the time interval, and the keyword of interest. | 1. An information extracting server comprising: a collecting unit configured to collect a text in which a keyword of interest indicating information of interest that a user is interested in appears, the keyword of interest, and a time of creation of the text; a keyword extracting unit configured to extract a keyword included in the text except for the keyword of interest, and the time of creation; a local hot word extracting unit configured to extract the keyword having a time score obtained on the basis of an appearance frequency of the keyword in a time interval, which is a period T1 backward from the time of creation, exceeding a first threshold value and a local score on the basis of the appearance frequency of the keyword in a local area indicating a range of a specific topic exceeding a second threshold value as a local hot word, and also extract the extracted time interval of the extracted keyword and the keyword of interest corresponding to the keyword; and a local hot word storing unit configured to store the extracted local hot word, the time interval, and the keyword of interest. 7. The information extracting server according to claim 1 , wherein the local hot word is a keyword within a local area indicating a range of a specific topic within a specific time interval. | 0.874011 |
8,626,585 | 1 | 10 | 1. A method performed by data processing apparatus, the method comprising: for each of one or more textual advertisements of a sponsor of the textual advertisements, each of the advertisements including a link to a corresponding landing page that causes a user device to request the landing page in response to the advertisement being selected when the advertisement is displayed on the user device: identifying landing page images in the landing page to which the textual advertisement links; for each landing page image identified in the landing page, determining a relevance measure that measures the relevance of the landing page image to the content of the landing page; selecting, by a data processing apparatus, one or more of the landing page images for concurrent display with the textual advertisement based on the relevance measures of the landing page images; and storing, in a data storage system, data associating the selected landing page images with the textual advertisements. | 1. A method performed by data processing apparatus, the method comprising: for each of one or more textual advertisements of a sponsor of the textual advertisements, each of the advertisements including a link to a corresponding landing page that causes a user device to request the landing page in response to the advertisement being selected when the advertisement is displayed on the user device: identifying landing page images in the landing page to which the textual advertisement links; for each landing page image identified in the landing page, determining a relevance measure that measures the relevance of the landing page image to the content of the landing page; selecting, by a data processing apparatus, one or more of the landing page images for concurrent display with the textual advertisement based on the relevance measures of the landing page images; and storing, in a data storage system, data associating the selected landing page images with the textual advertisements. 10. The method of claim 1 , wherein each of the one or more textual content items of the sponsor is an advertisement for which the sponsor has not specified an image to be displayed with the advertisement. | 0.826565 |
8,832,117 | 9 | 10 | 9. The processor-implemented method of claim 1 , wherein user-specific linkage strengths are used to indicate a strength of association between pairs of linked subject items in the knowledge base and the linkage strengths are used in the determination of candidacy and in the computation of the priority values. | 9. The processor-implemented method of claim 1 , wherein user-specific linkage strengths are used to indicate a strength of association between pairs of linked subject items in the knowledge base and the linkage strengths are used in the determination of candidacy and in the computation of the priority values. 10. The processor-implemented method of claim 9 , wherein the priority values are computed based on the understanding values of at least one of a plurality of subject items, if the weighted average of the understanding values corresponding to the at least one of a plurality of basic subject items is above an understanding value threshold, wherein the weights associated with the understanding values are a function of the user-specific linkage strengths between the at least one of the plurality of basic subject items and the candidate subject item. | 0.503597 |
8,073,718 | 5 | 6 | 5. The method of claim 3 comprising: determining the temporary translation table comprises one row; and translating the data into the one or more vehicle identifiers based on the one row. | 5. The method of claim 3 comprising: determining the temporary translation table comprises one row; and translating the data into the one or more vehicle identifiers based on the one row. 6. The method of claim 5 comprising: determining the temporary translation table comprises two or more rows with one or more matches in the model subset field; calculating a goodness value for each row, wherein the goodness value is based on match information for each row, a number of row matches, or any combination thereof; and translating the data into the one or more vehicle identifiers based a row with a highest goodness value. | 0.5 |
8,615,419 | 31 | 35 | 31. An apparatus for calculating an interaction churn score in an organization with which the customer has an interaction, the apparatus comprising: a voice recording device for capturing the interaction; a category definition component for defining a plurality of categories, each category characterized by an at least one parameter of a voiced expression; an extraction engine for extracting information from the interaction; a category score determination component for determining at least one category-interaction indication associating the interaction with at least one churning category out of a total number of categories; an interaction churn score determination component for determining an interaction churn score related to the interaction, wherein the interaction churn score comprises a term directly related to the number of churning categories the interaction is associated with and inversely related to the total number of churning categories based on a formula as:
A *(maximal score for a churning category)+ B *((the number of churning categories into which the interaction is categorized)/(the number of churning categories)*100), wherein A and B are coefficients that satisfy a condition of A+B=1; a transactional churn score determination component for determining a transaction churn score for the customer, based on additional data related to the customer or to the organization; a combined churn score determination component for combining the interaction churn score and the transaction churn score into a combined churn score; a retention offer engine for making a retention offer to the customer; and a capturing or logging component for capturing the interaction; and wherein the cited components comprise processing apparatus configured to perform the corresponding tasks cited above and wherein the cited engines comprise processing apparatus configured to perform the corresponding tasks cited above. | 31. An apparatus for calculating an interaction churn score in an organization with which the customer has an interaction, the apparatus comprising: a voice recording device for capturing the interaction; a category definition component for defining a plurality of categories, each category characterized by an at least one parameter of a voiced expression; an extraction engine for extracting information from the interaction; a category score determination component for determining at least one category-interaction indication associating the interaction with at least one churning category out of a total number of categories; an interaction churn score determination component for determining an interaction churn score related to the interaction, wherein the interaction churn score comprises a term directly related to the number of churning categories the interaction is associated with and inversely related to the total number of churning categories based on a formula as:
A *(maximal score for a churning category)+ B *((the number of churning categories into which the interaction is categorized)/(the number of churning categories)*100), wherein A and B are coefficients that satisfy a condition of A+B=1; a transactional churn score determination component for determining a transaction churn score for the customer, based on additional data related to the customer or to the organization; a combined churn score determination component for combining the interaction churn score and the transaction churn score into a combined churn score; a retention offer engine for making a retention offer to the customer; and a capturing or logging component for capturing the interaction; and wherein the cited components comprise processing apparatus configured to perform the corresponding tasks cited above and wherein the cited engines comprise processing apparatus configured to perform the corresponding tasks cited above. 35. The apparatus according to claim 31 , wherein the categories are provided by a user. | 0.84058 |
8,423,350 | 9 | 11 | 9. A computer program product, encoded on a tangible program carrier, operable to cause a data processing apparatus to perform operations comprising: receiving text; segmenting the text into one or more unigrams; filtering the one or more unigrams to identify one or more core unigrams; and generating a searchable data structure, wherein the generating includes, for each specific unigram of the one or more core unigrams: identifying a stem of the specific unigram, indexing the stem, obtaining (i) grammar information for the specific unigram, (ii) language information for the specific unigram, and (iii) description information for the specific unigram, and associating one or more n-grams with the indexed stem, wherein each of the one or more n-grams is derived from the text, the grammar information for the specific unigram, the language information for the specific unigram, and the description information for the specific unigram, and wherein each of the one or more n-grams includes a core unigram that is related to the indexed stem. | 9. A computer program product, encoded on a tangible program carrier, operable to cause a data processing apparatus to perform operations comprising: receiving text; segmenting the text into one or more unigrams; filtering the one or more unigrams to identify one or more core unigrams; and generating a searchable data structure, wherein the generating includes, for each specific unigram of the one or more core unigrams: identifying a stem of the specific unigram, indexing the stem, obtaining (i) grammar information for the specific unigram, (ii) language information for the specific unigram, and (iii) description information for the specific unigram, and associating one or more n-grams with the indexed stem, wherein each of the one or more n-grams is derived from the text, the grammar information for the specific unigram, the language information for the specific unigram, and the description information for the specific unigram, and wherein each of the one or more n-grams includes a core unigram that is related to the indexed stem. 11. The computer program product of claim 9 , wherein the grammar information includes information for distinguishing between different lexical categories that the specific unigram belongs to, wherein the language information includes information indicative of a language of the specific unigram, and wherein the description information includes at least one of (i) user-generated information describing the specific unigram and (ii) information generated by the data processing apparatus that describes the specific unigram. | 0.537852 |
7,937,663 | 1 | 4 | 1. A computer-implement method for providing collaborative authoring features in a document editor program, the method comprising: providing a document editor program that includes a line of business integration mode; activating the line of business integration mode; displaying a document editing pane in the document editor program, wherein the document editing pane includes a document having at least one section; displaying a document assembly pane in the document editing program, wherein the document assembly pane includes a document details pane and a section details pane; obtaining document details metadata, wherein the document details metadata includes metadata associated with collaboratively authoring the document; obtaining section details metadata, wherein the section details metadata includes data associated with an author assigned to the at least one section of the document; displaying the document details metadata in the document details pane; and displaying the section details metadata in the section details pane. | 1. A computer-implement method for providing collaborative authoring features in a document editor program, the method comprising: providing a document editor program that includes a line of business integration mode; activating the line of business integration mode; displaying a document editing pane in the document editor program, wherein the document editing pane includes a document having at least one section; displaying a document assembly pane in the document editing program, wherein the document assembly pane includes a document details pane and a section details pane; obtaining document details metadata, wherein the document details metadata includes metadata associated with collaboratively authoring the document; obtaining section details metadata, wherein the section details metadata includes data associated with an author assigned to the at least one section of the document; displaying the document details metadata in the document details pane; and displaying the section details metadata in the section details pane. 4. The computer-implemented method of claim 1 , wherein the section details pane includes a list of sections and assignments, wherein an expanded section details pane is populated with assignment metadata associated with a selected section. | 0.6 |
8,135,692 | 1 | 2 | 1. A computer-executable information retrieval apparatus for a web page retrieval using a retrieval keyword comprising: at least one processor; a computer storage medium embedded with computer instructions executed by the at least one processor, the executed computer instructions comprising: a word extract portion that extracts a first word from a web page on a display based on a display position of said web page on said display, wherein the displayed position is specified by a user, said word extract portion further extracts a second word placed around said extracted first word, said extracted second word is different from said extracted first word and is determined by an importance; wherein the importance of said extracted second word is calculated by a word importance calculation portion, the word importance calculation portion calculates the importance of said extracted second word based on an importance of said extracted second word itself and related to said extracted first word, wherein the word importance calculation portion further calculating said importance of said extracted second word related to said extracted first word based on a relationship between a ratio of the number of cooccurrences of said extracted second word with said extracted first word within a range of a certain character number in said web page to the total number of occurrences of said extracted second word in said web page, and a distance from said first word to said second word on said display; a retrieval portion that retrieves at least one web page using said extracted first word and second word. | 1. A computer-executable information retrieval apparatus for a web page retrieval using a retrieval keyword comprising: at least one processor; a computer storage medium embedded with computer instructions executed by the at least one processor, the executed computer instructions comprising: a word extract portion that extracts a first word from a web page on a display based on a display position of said web page on said display, wherein the displayed position is specified by a user, said word extract portion further extracts a second word placed around said extracted first word, said extracted second word is different from said extracted first word and is determined by an importance; wherein the importance of said extracted second word is calculated by a word importance calculation portion, the word importance calculation portion calculates the importance of said extracted second word based on an importance of said extracted second word itself and related to said extracted first word, wherein the word importance calculation portion further calculating said importance of said extracted second word related to said extracted first word based on a relationship between a ratio of the number of cooccurrences of said extracted second word with said extracted first word within a range of a certain character number in said web page to the total number of occurrences of said extracted second word in said web page, and a distance from said first word to said second word on said display; a retrieval portion that retrieves at least one web page using said extracted first word and second word. 2. The computer-executable information retrieval apparatus as recited in claim 1 , wherein said word importance calculation portion validates said importance of said extracted second word itself when said extracted second word belongs to a proper noun. | 0.602524 |
8,122,014 | 1 | 7 | 1. A computer-implemented method for augmenting web pages with related resources through layered augmentation, the method comprising: analyzing a web page to identify a keyword in the web page; locating a piece of reference data from a reference database matching the identified keyword; generating an association of the located piece of reference data and the keyword; embedding the association in an augmented web page corresponding to the web page; receiving a request from a client computer corresponding to a pointer being positioned over the keyword in the augmented web page; and responsive to receiving the signal: determining a plurality of resources relevant to the keyword by searching for the plurality of resources using the located piece of reference data in a resource database, and transmitting the plurality of resources to the client computer for display in a multi-layered dialog box, such that a viewer can access the plurality of resources by interacting with the multi-layered dialog box without leaving the augmented web page. | 1. A computer-implemented method for augmenting web pages with related resources through layered augmentation, the method comprising: analyzing a web page to identify a keyword in the web page; locating a piece of reference data from a reference database matching the identified keyword; generating an association of the located piece of reference data and the keyword; embedding the association in an augmented web page corresponding to the web page; receiving a request from a client computer corresponding to a pointer being positioned over the keyword in the augmented web page; and responsive to receiving the signal: determining a plurality of resources relevant to the keyword by searching for the plurality of resources using the located piece of reference data in a resource database, and transmitting the plurality of resources to the client computer for display in a multi-layered dialog box, such that a viewer can access the plurality of resources by interacting with the multi-layered dialog box without leaving the augmented web page. 7. The method of claim 1 , further comprising: determining a context of the keyword in the web page, wherein determining the plurality of resources relevant to the keyword further comprises searching for the plurality of resources using the context of the keyword in the resource database. | 0.783033 |
7,904,451 | 1 | 13 | 1. A method of content management comprising: retrieving a data record associated with a product object instance from a database in response to a first selection of the product object instance; retrieving an audience profile from the database in response to a second selection of the audience profile, the selected audience profile including a plurality of audience factors; converting at least a portion of the data record into a structured format file supporting a plurality of rhetorical elements, wherein the portion of the data record converted into a structured format file is based on the selected audience profile; and rendering an electronically displayable document using the structured format file, the rendering of the electronically displayable document based on assembly rules selected from a plurality of assembly rules, wherein the assembly rules are selected based on the plurality of audience factors of the selected audience profile. | 1. A method of content management comprising: retrieving a data record associated with a product object instance from a database in response to a first selection of the product object instance; retrieving an audience profile from the database in response to a second selection of the audience profile, the selected audience profile including a plurality of audience factors; converting at least a portion of the data record into a structured format file supporting a plurality of rhetorical elements, wherein the portion of the data record converted into a structured format file is based on the selected audience profile; and rendering an electronically displayable document using the structured format file, the rendering of the electronically displayable document based on assembly rules selected from a plurality of assembly rules, wherein the assembly rules are selected based on the plurality of audience factors of the selected audience profile. 13. The method of claim 1 , further comprising linking the audience profile to a concept instance having a property value. | 0.870213 |
8,892,562 | 1 | 2 | 1. A computer implemented categorization method comprising: receiving a sequence of pages to be categorized; for each of a plurality of pages in the sequence as a current page: computing a page category score for each of a set of categories for the current page; computing a first bipage category score for each of the set of categories for a first bipage comprising a preceding page and the current page; computing a second bipage category score for each of the set of categories for a second bipage comprising a subsequent page and the current page; computing a first boundary probability that there is a document boundary between the preceding page and the current page; and computing a second boundary probability that there is a document boundary between the subsequent page and the current page; with a computer processor, for at least one iteration, for each of the plurality of pages, computing a refined page category score for each of the set of categories for the current page as a function of: the first bipage category scores weighted by a first weighting factor, the first weighting factor being based on the first boundary probability; the second bipage category scores weighted by a second weighting factor, the second weighting factor being based on the second boundary probability; and the page category scores of the current page; and outputting information based on the refined page category scores for each of the plurality of pages. | 1. A computer implemented categorization method comprising: receiving a sequence of pages to be categorized; for each of a plurality of pages in the sequence as a current page: computing a page category score for each of a set of categories for the current page; computing a first bipage category score for each of the set of categories for a first bipage comprising a preceding page and the current page; computing a second bipage category score for each of the set of categories for a second bipage comprising a subsequent page and the current page; computing a first boundary probability that there is a document boundary between the preceding page and the current page; and computing a second boundary probability that there is a document boundary between the subsequent page and the current page; with a computer processor, for at least one iteration, for each of the plurality of pages, computing a refined page category score for each of the set of categories for the current page as a function of: the first bipage category scores weighted by a first weighting factor, the first weighting factor being based on the first boundary probability; the second bipage category scores weighted by a second weighting factor, the second weighting factor being based on the second boundary probability; and the page category scores of the current page; and outputting information based on the refined page category scores for each of the plurality of pages. 2. The method of claim 1 , wherein, for at least a second iteration, the computing of the refined page category scores for each of the set of categories for the current page comprises computing further refined page category scores based on the previously-computed refined page category scores for each of the set of categories and the first and second boundary probabilities. | 0.5 |
5,543,818 | 9 | 10 | 9. A system for entering text into a computer system, including: a processor; a display device connected to the processor; and an input device connected to the processor, said input device including keys, wherein the processor is programmed with software for displaying on the display device a character selection menu including simultaneously displayed groups of character representations, each of said groups including representations of B characters, the characters within each group arranged in a pattern, highlighting a selected one of the groups in response to actuation of a first set of the keys, and selecting a character representation within the selected one of the groups in response to actuation of a one of a second set of the keys, where said second set of the keys consists of B of the keys, where B is a positive integer not less than two, and where said second set of the keys is separate from the display device and is arranged in a pattern corresponding to the pattern of the characters within each group. | 9. A system for entering text into a computer system, including: a processor; a display device connected to the processor; and an input device connected to the processor, said input device including keys, wherein the processor is programmed with software for displaying on the display device a character selection menu including simultaneously displayed groups of character representations, each of said groups including representations of B characters, the characters within each group arranged in a pattern, highlighting a selected one of the groups in response to actuation of a first set of the keys, and selecting a character representation within the selected one of the groups in response to actuation of a one of a second set of the keys, where said second set of the keys consists of B of the keys, where B is a positive integer not less than two, and where said second set of the keys is separate from the display device and is arranged in a pattern corresponding to the pattern of the characters within each group. 10. The system of claim 9, wherein the first set of the keys consists of at least one cursor movement key and the second set of the keys consists of B selection keys, and wherein the processor is programmed with software for highlighting the selected one of the groups in response to actuation of the at least one cursor movement key, and selecting said character representation within said selected one of the groups in response to actuation of one of the selection keys. | 0.5 |
8,406,385 | 1 | 3 | 1. A method comprising: receiving, from a user, a voice message intended for delivery to a recipient the voice message being in a first language; determining a second language understood by the recipient; and when the first language differs from the second language, prompting the user to determine whether to translate the voice message into the second language; when the user, in response to the prompting indicates translation should occur, translating, via a processor, the voice message into the second language, to yield a translated voice message; and delivering the translated voice message to the recipient. | 1. A method comprising: receiving, from a user, a voice message intended for delivery to a recipient the voice message being in a first language; determining a second language understood by the recipient; and when the first language differs from the second language, prompting the user to determine whether to translate the voice message into the second language; when the user, in response to the prompting indicates translation should occur, translating, via a processor, the voice message into the second language, to yield a translated voice message; and delivering the translated voice message to the recipient. 3. The method of claim 1 , further comprising: delivering the voice message in addition to the translated voice message to the recipient. | 0.752708 |
8,812,321 | 1 | 12 | 1. A method comprising: recognizing, via a processor, received speech with a plurality of domain-specific speech recognizers without knowledge of a domain of the received speech, the plurality of domain-specific speech recognizers comprising two domain-specific speech recognizers from different domains and two domain-specific speech recognizers from a specific domain, wherein each domain-specific speech recognizer of the plurality of domain-specific speech recognizers recognizes the received speech, to yield respective speech recognition outputs; determining a speech recognition confidence score for each of the respective speech recognition outputs; selecting speech recognition candidates from segments of the respective speech recognition outputs based on the speech recognition confidence score for the respective speech recognition outputs; combining, via a machine-learning algorithm, the speech recognition candidates, to yield a combination of the speech recognition candidates; and generating text based on the combination. | 1. A method comprising: recognizing, via a processor, received speech with a plurality of domain-specific speech recognizers without knowledge of a domain of the received speech, the plurality of domain-specific speech recognizers comprising two domain-specific speech recognizers from different domains and two domain-specific speech recognizers from a specific domain, wherein each domain-specific speech recognizer of the plurality of domain-specific speech recognizers recognizes the received speech, to yield respective speech recognition outputs; determining a speech recognition confidence score for each of the respective speech recognition outputs; selecting speech recognition candidates from segments of the respective speech recognition outputs based on the speech recognition confidence score for the respective speech recognition outputs; combining, via a machine-learning algorithm, the speech recognition candidates, to yield a combination of the speech recognition candidates; and generating text based on the combination. 12. The method of claim 1 , wherein a speech recognition candidate comprises one of a lattice, confidence scores, and speech recognition metadata. | 0.802703 |
8,983,924 | 17 | 18 | 17. A method of sharing search information, comprising: generating a user interface display that is displayed to a first user and includes a query receiving area for receiving a query from the first user and a public stream area, displayed along with the query receiving area, indicative of queries input by other users, other than the first user, the public stream area including posts, wherein each post represents one of the queries as a selectable component that is selectable by the first user to obtain information for the query represented by the post, the post having a user identifier portion that identities another user, other than the first user, that input the query represented by the post, and the post displaying one or more query terms that were input by the other user; identifying a particular one of the selectable components that is actuated by a given user; and generating an updated user interface display in which the public stream area displays an indication that the given user has actuated the particular selectable component. | 17. A method of sharing search information, comprising: generating a user interface display that is displayed to a first user and includes a query receiving area for receiving a query from the first user and a public stream area, displayed along with the query receiving area, indicative of queries input by other users, other than the first user, the public stream area including posts, wherein each post represents one of the queries as a selectable component that is selectable by the first user to obtain information for the query represented by the post, the post having a user identifier portion that identities another user, other than the first user, that input the query represented by the post, and the post displaying one or more query terms that were input by the other user; identifying a particular one of the selectable components that is actuated by a given user; and generating an updated user interface display in which the public stream area displays an indication that the given user has actuated the particular selectable component. 18. The method of claim 17 wherein the given user is a user other than the first user, and generating a user interface display includes displaying the user identifier portion as a selectable component. | 0.509756 |
9,263,027 | 1 | 8 | 1. A broadcast signal receiver comprising: a text data receiver configured to receive broadcast text data and to transmit the broadcast text data to a user interface, wherein the broadcast text data includes at least one word; a text-to-speech (TTS) converter configured to convert received text data into an audio speech sound, wherein the TTS converter is configured to: detect whether the at least one word is also included in a stored list of words, and when the at least one word is also included in the stored list of words, convert the at least one word according to a conversion defined by the stored list, and when the at least one word is not included in the stored list of words, convert the at least one word according to a set of predetermined conversion rules; a conversion memory configured to store the list of words as initial data; an update receiver configured to receive, from a conversion repository, and via a network connection, update data, wherein the update data includes updated words, associated conversions, and updated conversion rules, and configured to store, in the conversion memory, the update data; and a commander circuitry configured to control an operation of the broadcast signal receiver, wherein the commander circuitry is configured to receive a user control input, wherein the user control input indicates an incorrect conversion carried out by the TTS converter; and wherein the broadcast signal receiver is configured to, in response to the user control input, send a message to a data provider, and thereby request update data, wherein the message indicates a conversion problem and indicates text which was converted, by the TTS converter, into speech. | 1. A broadcast signal receiver comprising: a text data receiver configured to receive broadcast text data and to transmit the broadcast text data to a user interface, wherein the broadcast text data includes at least one word; a text-to-speech (TTS) converter configured to convert received text data into an audio speech sound, wherein the TTS converter is configured to: detect whether the at least one word is also included in a stored list of words, and when the at least one word is also included in the stored list of words, convert the at least one word according to a conversion defined by the stored list, and when the at least one word is not included in the stored list of words, convert the at least one word according to a set of predetermined conversion rules; a conversion memory configured to store the list of words as initial data; an update receiver configured to receive, from a conversion repository, and via a network connection, update data, wherein the update data includes updated words, associated conversions, and updated conversion rules, and configured to store, in the conversion memory, the update data; and a commander circuitry configured to control an operation of the broadcast signal receiver, wherein the commander circuitry is configured to receive a user control input, wherein the user control input indicates an incorrect conversion carried out by the TTS converter; and wherein the broadcast signal receiver is configured to, in response to the user control input, send a message to a data provider, and thereby request update data, wherein the message indicates a conversion problem and indicates text which was converted, by the TTS converter, into speech. 8. The receiver according to claim 1 , wherein a conversion made using the update data overrides a conversion made using initial data. | 0.850446 |
8,990,224 | 12 | 21 | 12. A computer system comprising: one or more processors to: determine a plurality of portions of text extracted from a corresponding plurality of documents; process a particular portion of text, of the plurality of portions of text, by applying a first filter, of a plurality of filters, to generate a first score, the particular portion of text corresponding to a particular document of the plurality of documents; determine a total count of script changes or font changes in the particular portion of text by applying a second filter of the plurality of filters; generate a second score based on the total count of the script changes or the font changes in the particular portion of text; determine a readability score based on the first score and the second score; determine that the readability score satisfies a threshold score; generate or select a new portion of text, for the particular document, based on determining that the readability score satisfies the threshold score; and assign the new portion of text to the particular document. | 12. A computer system comprising: one or more processors to: determine a plurality of portions of text extracted from a corresponding plurality of documents; process a particular portion of text, of the plurality of portions of text, by applying a first filter, of a plurality of filters, to generate a first score, the particular portion of text corresponding to a particular document of the plurality of documents; determine a total count of script changes or font changes in the particular portion of text by applying a second filter of the plurality of filters; generate a second score based on the total count of the script changes or the font changes in the particular portion of text; determine a readability score based on the first score and the second score; determine that the readability score satisfies a threshold score; generate or select a new portion of text, for the particular document, based on determining that the readability score satisfies the threshold score; and assign the new portion of text to the particular document. 21. The computer system of claim 12 , where the one or more processors, when determining the readability score based on the first score and the second score, are to: determine that the first score is less than the second score, and select the first score as the readability score based on the first score being less than the second score. | 0.681132 |
8,275,662 | 1 | 22 | 1. A method for providing geo-targeted messages with a search result, the method comprising: providing a toolbar plug-in for an electronic document for allowing a user to enter a search query term for querying the search query term on at least one Internet search platform; customizing the toolbar plug-in with at least one geographical setting; providing exclusive leasing rights to use a leased term associated with a message, wherein the leased term exclusively corresponds to at least one selected geo-targeted area; saving the leased term; receiving a search query term, via the toolbar plug-in, for performing a search request for the search query term on said search platform(s); displaying the search result for the search query term in a second electronic document; and displaying at least one geo-targeted message corresponding to the leased term in response to the search request in a first electronic document, upon determining that the search query term matches the leased term, wherein the method simultaneously provides for displaying the geo-targeted messages in the first electronic document, and displaying said search result in the second electronic document, wherein the first electronic document and the second electronic document are independent, and wherein providing exclusive leasing rights to use the leased term comprises removing the search query term from the terms available for lease in the at least one selected geo-targeted area. | 1. A method for providing geo-targeted messages with a search result, the method comprising: providing a toolbar plug-in for an electronic document for allowing a user to enter a search query term for querying the search query term on at least one Internet search platform; customizing the toolbar plug-in with at least one geographical setting; providing exclusive leasing rights to use a leased term associated with a message, wherein the leased term exclusively corresponds to at least one selected geo-targeted area; saving the leased term; receiving a search query term, via the toolbar plug-in, for performing a search request for the search query term on said search platform(s); displaying the search result for the search query term in a second electronic document; and displaying at least one geo-targeted message corresponding to the leased term in response to the search request in a first electronic document, upon determining that the search query term matches the leased term, wherein the method simultaneously provides for displaying the geo-targeted messages in the first electronic document, and displaying said search result in the second electronic document, wherein the first electronic document and the second electronic document are independent, and wherein providing exclusive leasing rights to use the leased term comprises removing the search query term from the terms available for lease in the at least one selected geo-targeted area. 22. The method of claim 1 , wherein the first electronic document presents a first Internet result, and the second electronic document presents a second Internet result. | 0.930681 |
7,610,279 | 1 | 2 | 1. A computer implemented method of filtering context-sensitive search results, the method comprising: determining a user context based on a tunable parameter; determining a first aspect of the user context and a second aspect of the user context, wherein the first aspect of the user context includes data indicative of text being accessed by a user and the second aspect of the user context includes data indicative of at least one user task from a plurality of user tasks, wherein the at least one user task is determined based upon the user context of the user's interaction with one or more software applications; formulating a first query and a second query based on the first aspect of the user context, the first query and the second query being different than the user context; submitting the first query to a first search engine; receiving a first plurality of search results from the first search engine, the first plurality of search results being based on the first query; submitting the second query to a second different search engine; receiving a second plurality of search results from the second different search engine, the second plurality of search results being based on the second query; determining a first plurality of scores associated with the first plurality of search results at least in part by comparing data indicative of the first plurality of search results to data indicative of the first aspect of the user context; determining a second plurality of scores associated with the second plurality of search results at least in part by comparing data indicative of the second plurality of search results to the data indicative of the first aspect of the user context; and displaying a subset of the plurality of search results on a client device, wherein at least one of the first plurality of search results is filtered from being displayed to the user based on at least a portion of the first plurality of scores, and wherein at least one of the second plurality of search results is filtered from being displayed to the user based on at least a portion of the second plurality of scores. | 1. A computer implemented method of filtering context-sensitive search results, the method comprising: determining a user context based on a tunable parameter; determining a first aspect of the user context and a second aspect of the user context, wherein the first aspect of the user context includes data indicative of text being accessed by a user and the second aspect of the user context includes data indicative of at least one user task from a plurality of user tasks, wherein the at least one user task is determined based upon the user context of the user's interaction with one or more software applications; formulating a first query and a second query based on the first aspect of the user context, the first query and the second query being different than the user context; submitting the first query to a first search engine; receiving a first plurality of search results from the first search engine, the first plurality of search results being based on the first query; submitting the second query to a second different search engine; receiving a second plurality of search results from the second different search engine, the second plurality of search results being based on the second query; determining a first plurality of scores associated with the first plurality of search results at least in part by comparing data indicative of the first plurality of search results to data indicative of the first aspect of the user context; determining a second plurality of scores associated with the second plurality of search results at least in part by comparing data indicative of the second plurality of search results to the data indicative of the first aspect of the user context; and displaying a subset of the plurality of search results on a client device, wherein at least one of the first plurality of search results is filtered from being displayed to the user based on at least a portion of the first plurality of scores, and wherein at least one of the second plurality of search results is filtered from being displayed to the user based on at least a portion of the second plurality of scores. 2. The method of claim 1 , wherein the first query includes the second query. | 0.971712 |
8,949,221 | 2 | 3 | 2. The method of claim 1 , wherein the evaluation of the subquery is affected by an extension to XQuery. | 2. The method of claim 1 , wherein the evaluation of the subquery is affected by an extension to XQuery. 3. The method of claim 2 , wherein the extension comprises a function enabling distributed execution, the extension further comprising a subexpression. | 0.5 |
8,332,415 | 10 | 11 | 10. A non-transitory computer-readable medium storing computer software instructions executable by data processing apparatus to perform operations comprising: determining a first frequency of occurrence of a phrase in plurality of first text items describing business entities, wherein the first text items are received from a trusted source; determining a first ratio of the first frequency of occurrence to a count of the plurality of first text items by dividing the first frequency by the count of the plurality of first items; determining a second frequency of occurrence of the phrase in a plurality of second text items describing business entities, wherein the second text items are received from an untrusted source; determining a second ratio of the second frequency of occurrence to a count of the plurality of second text items by dividing the second frequency by the count of the plurality of second items; determining a likelihood that text items received from the untrusted source include spam; determining a likelihood that the phrase is spam based at least partially on the first ratio, the second ratio, and the likelihood that text items received from the untrusted source include spam; and determining a likelihood that a different text item received from the untrusted source and that includes the phrase is spam based at least in part on the likelihood that the phrase is spam. | 10. A non-transitory computer-readable medium storing computer software instructions executable by data processing apparatus to perform operations comprising: determining a first frequency of occurrence of a phrase in plurality of first text items describing business entities, wherein the first text items are received from a trusted source; determining a first ratio of the first frequency of occurrence to a count of the plurality of first text items by dividing the first frequency by the count of the plurality of first items; determining a second frequency of occurrence of the phrase in a plurality of second text items describing business entities, wherein the second text items are received from an untrusted source; determining a second ratio of the second frequency of occurrence to a count of the plurality of second text items by dividing the second frequency by the count of the plurality of second items; determining a likelihood that text items received from the untrusted source include spam; determining a likelihood that the phrase is spam based at least partially on the first ratio, the second ratio, and the likelihood that text items received from the untrusted source include spam; and determining a likelihood that a different text item received from the untrusted source and that includes the phrase is spam based at least in part on the likelihood that the phrase is spam. 11. The medium of claim 10 , wherein determining the likelihood that text items received from the untrusted source includes spam comprises: identifying a subset of the plurality of second text items received from the untrusted source that contain a signal that indicates that each second text item in the subset is spam; and determining the likelihood that the text items received from the untrusted source includes spam as a ratio of a count of the second text items in the subset to a count of the plurality of second text items. | 0.518149 |
8,724,441 | 10 | 11 | 10. The recording device according to claim 9 , wherein the recording unit records NRZ data obtained by performing inverting to a symbol “1” and non-inverting to a symbol “0” with respect to an encoded string of code words encoded by the encoding unit in the optical recording medium. | 10. The recording device according to claim 9 , wherein the recording unit records NRZ data obtained by performing inverting to a symbol “1” and non-inverting to a symbol “0” with respect to an encoded string of code words encoded by the encoding unit in the optical recording medium. 11. The recording device according to claim 10 , wherein the optical recording medium is a bulk type optical recording medium having a bulk layer for selectively performing mark recording at a plurality of positions in a depth direction, and the recording unit is configured to record marks by a blank in the bulk layer. | 0.5 |
9,319,816 | 9 | 20 | 9. A method of characterizing an environment in which a device resides, the device comprising at least one speaker and at least one microphone, and the method comprising: producing a pilot tone by the at least one speaker; subsequent to producing the pilot tone, generating, by the at least one microphone, a first audio signal based on sound from the environment, wherein at least a portion of the sound comprises the pilot tone as reflected by one or more surfaces within the environment and the first audio signal includes one or more characteristics; analyzing the first audio signal to determine if the one or more characteristics of the first audio signal have been altered with respect to one or more characteristics of the pilot tone; generating a second audio signal by the at least one microphone; based at least in part upon the analyzing of the first audio signal, at least one of (i) selecting a signal processing model for performing speech recognition on the second audio signal, or (ii) altering a signal processing model for performing speech recognition on the second audio signal; and performing speech recognition on the second audio signal using the at least one of the selected or altered signal processing model. | 9. A method of characterizing an environment in which a device resides, the device comprising at least one speaker and at least one microphone, and the method comprising: producing a pilot tone by the at least one speaker; subsequent to producing the pilot tone, generating, by the at least one microphone, a first audio signal based on sound from the environment, wherein at least a portion of the sound comprises the pilot tone as reflected by one or more surfaces within the environment and the first audio signal includes one or more characteristics; analyzing the first audio signal to determine if the one or more characteristics of the first audio signal have been altered with respect to one or more characteristics of the pilot tone; generating a second audio signal by the at least one microphone; based at least in part upon the analyzing of the first audio signal, at least one of (i) selecting a signal processing model for performing speech recognition on the second audio signal, or (ii) altering a signal processing model for performing speech recognition on the second audio signal; and performing speech recognition on the second audio signal using the at least one of the selected or altered signal processing model. 20. The method of claim 9 , further comprising, based at least in part upon the analyzing, altering a characteristic of a future pilot tone. | 0.802817 |
8,832,804 | 8 | 12 | 8. A computer implemented system for password pre-verification comprising one or more processors and memory comprising code that when executed cause the one or more processors to: (a) translate user input, in the form of a character string that can represent a password, to obtain a symbolic representation of the user input; (b) compare an existing symbolic representation with the symbolic representation generated from the user input; and (c) based on the result of the comparison, provide output to the user, in the form of visual, audio or haptic cues, wherein the visual, audio or haptic cues alert a user as to whether the input character string is correctly or incorrectly entered based upon a variance or similarity of the cue as compared to a previous cue provided to the user during a previous attempt to enter the input character, without providing an objective indicator, that allows an unauthorized user to discover the password, as to whether or not the password has been entered correctly if the user is unfamiliar with the variance, and wherein the output does not change until after a predetermined number of characters has been input and thereafter changes in a distinguishable way with the entry of each successive character that is input. | 8. A computer implemented system for password pre-verification comprising one or more processors and memory comprising code that when executed cause the one or more processors to: (a) translate user input, in the form of a character string that can represent a password, to obtain a symbolic representation of the user input; (b) compare an existing symbolic representation with the symbolic representation generated from the user input; and (c) based on the result of the comparison, provide output to the user, in the form of visual, audio or haptic cues, wherein the visual, audio or haptic cues alert a user as to whether the input character string is correctly or incorrectly entered based upon a variance or similarity of the cue as compared to a previous cue provided to the user during a previous attempt to enter the input character, without providing an objective indicator, that allows an unauthorized user to discover the password, as to whether or not the password has been entered correctly if the user is unfamiliar with the variance, and wherein the output does not change until after a predetermined number of characters has been input and thereafter changes in a distinguishable way with the entry of each successive character that is input. 12. The system of claim 8 , wherein the code that when executed causes the one or more processors to provide output to the user in form of a sequence of colors determined by the user input character string. | 0.621324 |
8,346,765 | 9 | 16 | 9. A system for generating ranked search results, comprising: one or more processors configured to: receive a plurality of matching information items that match a search request; rank at least some of the plurality of matching information items using a linear ranking model that linearly combines a first plurality of feature values to obtain a first set of ranked results, wherein the linear ranking model combines the first plurality of feature values in a linear fashion using weight coefficients corresponding to the first plurality of feature values; rank at least some of the first set of ranked results using a nonlinear ranking model that nonlinearly combines a second plurality of feature values to obtain a second set of ranked results, wherein the nonlinear ranking model combines the second plurality of feature values in a nonlinear fashion using weight coefficients corresponding to the second plurality of feature values; and provide a search response based at least in part on the second set of ranked results; one or more memories coupled to the one or more processors, configured to provide the processors with instructions. | 9. A system for generating ranked search results, comprising: one or more processors configured to: receive a plurality of matching information items that match a search request; rank at least some of the plurality of matching information items using a linear ranking model that linearly combines a first plurality of feature values to obtain a first set of ranked results, wherein the linear ranking model combines the first plurality of feature values in a linear fashion using weight coefficients corresponding to the first plurality of feature values; rank at least some of the first set of ranked results using a nonlinear ranking model that nonlinearly combines a second plurality of feature values to obtain a second set of ranked results, wherein the nonlinear ranking model combines the second plurality of feature values in a nonlinear fashion using weight coefficients corresponding to the second plurality of feature values; and provide a search response based at least in part on the second set of ranked results; one or more memories coupled to the one or more processors, configured to provide the processors with instructions. 16. The system of claim 9 , wherein the nonlinear ranking model is determined by training. | 0.901532 |
8,868,569 | 9 | 13 | 9. One or more non-transitory computer-readable media storing instructions, which, when executed by one or more processors, cause one or more computing devices to perform: identifying a subset of content items of a search index based at least upon content items returned in a result set generated by a search engine for a particular query that was previously submitted to the search engine; for each content item in the subset, determining a similarity value with respect to all other content items in the subset; upon determining that a similarity value of a first content item and a second content item of the subset of content items satisfy a particular threshold value, determining which of the first content item and second content item are less relevant to the particular query; and marking, in the search index, the less relevant to the particular query of the first content item and second content item as a duplicate content item for the particular query; in response to determining that the more relevant of the first content item and the second content item to the particular query is no longer available: determining which of the content items are marked as a duplicate and satisfy the particular threshold value is the most relevant content item to the particular query; and updating the search index by removing the mark as duplicate for the most relevant content item to the particular query. | 9. One or more non-transitory computer-readable media storing instructions, which, when executed by one or more processors, cause one or more computing devices to perform: identifying a subset of content items of a search index based at least upon content items returned in a result set generated by a search engine for a particular query that was previously submitted to the search engine; for each content item in the subset, determining a similarity value with respect to all other content items in the subset; upon determining that a similarity value of a first content item and a second content item of the subset of content items satisfy a particular threshold value, determining which of the first content item and second content item are less relevant to the particular query; and marking, in the search index, the less relevant to the particular query of the first content item and second content item as a duplicate content item for the particular query; in response to determining that the more relevant of the first content item and the second content item to the particular query is no longer available: determining which of the content items are marked as a duplicate and satisfy the particular threshold value is the most relevant content item to the particular query; and updating the search index by removing the mark as duplicate for the most relevant content item to the particular query. 13. The one or more non-transitory computer-readable media of claim 9 , wherein instructions for determining a similarity value further comprises instructions for performing: generating a digital signature for each content item; and calculating the difference in bits between the digital signature for one content item to the digital signature of another content item. | 0.5 |
8,559,695 | 4 | 5 | 4. The method of claim 3 , further comprising automatically stopping the transporting of the U.S. currency bills such that a first one of the plurality of detected find bills is the last U.S. currency bill transported to the one or more output receptacles. | 4. The method of claim 3 , further comprising automatically stopping the transporting of the U.S. currency bills such that a first one of the plurality of detected find bills is the last U.S. currency bill transported to the one or more output receptacles. 5. The method of claim 4 , wherein the one or more output receptacles is exactly one output receptacle. | 0.5 |
9,305,543 | 1 | 2 | 1. A method for converting text to speech, the method comprising: at an electronic device with a processor and memory storing one or more programs for execution by the processor: parsing a document to identify a plurality of text elements in the document to be converted to speech, wherein in the document, a first text element of the plurality of text elements is positioned before a second text element of the plurality of text elements; determining, by the processor, an order in which the plurality of text elements are to be spoken, wherein the determined order comprises speaking the second text element before the first text element; and converting the plurality of text elements to speech, wherein the speech is spoken in the determined order. | 1. A method for converting text to speech, the method comprising: at an electronic device with a processor and memory storing one or more programs for execution by the processor: parsing a document to identify a plurality of text elements in the document to be converted to speech, wherein in the document, a first text element of the plurality of text elements is positioned before a second text element of the plurality of text elements; determining, by the processor, an order in which the plurality of text elements are to be spoken, wherein the determined order comprises speaking the second text element before the first text element; and converting the plurality of text elements to speech, wherein the speech is spoken in the determined order. 2. The method of claim 1 , wherein the second text element includes at least a portion of a footnote of the document. | 0.865207 |
6,016,395 | 4 | 6 | 4. The method of claim 1, wherein: the computer program further includes declaration of a selection mask; and the first vector operation is subjected to the selection mask to determine which elements of the vector operand are operated upon. | 4. The method of claim 1, wherein: the computer program further includes declaration of a selection mask; and the first vector operation is subjected to the selection mask to determine which elements of the vector operand are operated upon. 6. The method of claim 4 wherein: the first operation is a vector ALU operation; and each bit in the selection mask indicates if a corresponding element of the vector operand is affected by the first operation. | 0.507042 |
8,695,037 | 17 | 19 | 17. A single, interactive graphical user interface window to be presented on a display, the graphical user interface window comprising: a representation of a set of channels; and a representation of individual content items associated with each of the channels, wherein the individual content items include television programming and interactive data; wherein the single graphical user interface enables a user to select an individual content item associated with a displayed channel; wherein if the interactive data is selected, then the representation of the set of channels and the interactive data are both displayed within the single graphical user interface window; wherein the single graphical user interface window displays the representation of the individual content items associated with a channel upon selection of the channel by the user, wherein the single graphical user interface window does not involve overlaying; wherein the single graphical user interface window simultaneously displays categories, channels, and content, and permits navigation in the single graphical user interface therethrough, such that a plurality of sets of channels that each correspond to a plurality of categories respectively; and wherein upon selection of a single category of the plurality of categories by the user, the corresponding set of channels of the plurality of sets of channels is displayed. | 17. A single, interactive graphical user interface window to be presented on a display, the graphical user interface window comprising: a representation of a set of channels; and a representation of individual content items associated with each of the channels, wherein the individual content items include television programming and interactive data; wherein the single graphical user interface enables a user to select an individual content item associated with a displayed channel; wherein if the interactive data is selected, then the representation of the set of channels and the interactive data are both displayed within the single graphical user interface window; wherein the single graphical user interface window displays the representation of the individual content items associated with a channel upon selection of the channel by the user, wherein the single graphical user interface window does not involve overlaying; wherein the single graphical user interface window simultaneously displays categories, channels, and content, and permits navigation in the single graphical user interface therethrough, such that a plurality of sets of channels that each correspond to a plurality of categories respectively; and wherein upon selection of a single category of the plurality of categories by the user, the corresponding set of channels of the plurality of sets of channels is displayed. 19. The graphical user interface window of claim 17 , wherein a connection to a source of the individual content is established through a communications interface. | 0.685328 |
8,775,403 | 1 | 9 | 1. A method of scheduling document indexing, comprising: at a computing system having one or more processors and memory storing programs for execution by the one or more processors: retrieving a number of document identifiers, each document identifier identifying a corresponding document on a network; and for each retrieved document identifier and its corresponding document, determining a query-independent score indicative of a rank of the corresponding document relative to other documents in a set of documents; determining a first score for the document identifier that is a function of the determined query-independent score, a determined content change frequency of the corresponding document, and an age of the corresponding document; comparing the first score against a threshold value thereby obtaining a result, wherein the threshold value is a function of a speed of the engine crawler system; and conditionally scheduling the corresponding document for indexing based on the result. | 1. A method of scheduling document indexing, comprising: at a computing system having one or more processors and memory storing programs for execution by the one or more processors: retrieving a number of document identifiers, each document identifier identifying a corresponding document on a network; and for each retrieved document identifier and its corresponding document, determining a query-independent score indicative of a rank of the corresponding document relative to other documents in a set of documents; determining a first score for the document identifier that is a function of the determined query-independent score, a determined content change frequency of the corresponding document, and an age of the corresponding document; comparing the first score against a threshold value thereby obtaining a result, wherein the threshold value is a function of a speed of the engine crawler system; and conditionally scheduling the corresponding document for indexing based on the result. 9. The method of claim 1 , wherein the function is a product of two factors selected from the group consisting of the determined query-independent score, the determined content change frequency of the corresponding document, and the age of the corresponding document. | 0.5 |
5,481,703 | 9 | 14 | 9. A relational database restructuring system, having at least one relation, each said relation having a plurality of tuples, a set of attributes, a set of candidate keys and a set of non-key attributes, wherein each said tuple is managed as a two-dimensional relation for each said attribute and wherein each said relation has a candidate key serving as a set of attributes which can uniquely identify one of said tuples, comprising: first determination means for checking, with reference to values of tuples which are present in said relations, whether a first set of attributes is functionally dependent on a second set of attributes; division means for dividing a first relation into a second and a third relation by a projecting operation for a designated attribute set; second determination means for determining, from attribute sets A and B which are included in a relation and are mutually primary, whether said attribute sets A and B satisfy at least one of a first condition and a second condition, said first condition being that said attribute set A is a proper subset of said set of candidate keys and said attribute set B is a subset of a non-key attribute set serving as a subset of said set of candidate keys said second condition being that both the attribute sets A and B are proper subsets of said non-key attribute set; and means for checking whether said attribute set B is functionally dependent on said attribute set A once said second determination means has determined that said attribute sets A and B satisfy at least one of said first condition and said second condition, and dividing said relation including said attribute sets A and B, when said attribute set A is functionally dependent on attribute set B, into a relation formed by a projection to a subset of the attribute set B and, a relation formed by a projection to a union between said attribute sets A and B. | 9. A relational database restructuring system, having at least one relation, each said relation having a plurality of tuples, a set of attributes, a set of candidate keys and a set of non-key attributes, wherein each said tuple is managed as a two-dimensional relation for each said attribute and wherein each said relation has a candidate key serving as a set of attributes which can uniquely identify one of said tuples, comprising: first determination means for checking, with reference to values of tuples which are present in said relations, whether a first set of attributes is functionally dependent on a second set of attributes; division means for dividing a first relation into a second and a third relation by a projecting operation for a designated attribute set; second determination means for determining, from attribute sets A and B which are included in a relation and are mutually primary, whether said attribute sets A and B satisfy at least one of a first condition and a second condition, said first condition being that said attribute set A is a proper subset of said set of candidate keys and said attribute set B is a subset of a non-key attribute set serving as a subset of said set of candidate keys said second condition being that both the attribute sets A and B are proper subsets of said non-key attribute set; and means for checking whether said attribute set B is functionally dependent on said attribute set A once said second determination means has determined that said attribute sets A and B satisfy at least one of said first condition and said second condition, and dividing said relation including said attribute sets A and B, when said attribute set A is functionally dependent on attribute set B, into a relation formed by a projection to a subset of the attribute set B and, a relation formed by a projection to a union between said attribute sets A and B. 14. A system according to claim 9, wherein said system further comprises means for converting each of at least one third normal form relations divided by said division means into a relation having a normal form at a level higher than that of said third normal form. | 0.77466 |
8,125,669 | 1 | 10 | 1. A method comprising: A processor examining graphic user interface (GUI) logic; identifying flaws in the logic that expose security damage; mapping a visual invariant to a program invariant; discovering inputs to the GUI logic that include a user action and an execution context to cause the program invariant to be violated; and uncovering browser address bar spoofing by examining for logic correctness as to navigation functionality that includes loading a new page, travelling back in the history log, and opening a new window. | 1. A method comprising: A processor examining graphic user interface (GUI) logic; identifying flaws in the logic that expose security damage; mapping a visual invariant to a program invariant; discovering inputs to the GUI logic that include a user action and an execution context to cause the program invariant to be violated; and uncovering browser address bar spoofing by examining for logic correctness as to navigation functionality that includes loading a new page, travelling back in the history log, and opening a new window. 10. The method of claim 1 , wherein browser address bar spoofing is uncovered by examining execution context of a spoofing attack that includes a set of Boolean flags that affect the execution of navigation functions. | 0.511261 |
7,975,220 | 1 | 4 | 1. A structured document management apparatus comprising: a document data accepting unit that accepts input of structured document data having a hierarchical logic structure; a structure guide data storage unit that stores structure guide data which is a summary of hierarchical structure information of the structured document, wherein the structure guide data contains a guide node where unique identification information is allocated; a structure stream converting unit that executes a syntax analysis of the structured document data, and converts the structured document data into structure stream data as one-dimensional sequence data by arranging the unique identification information of guide nodes corresponding to nodes that pass when depth-prioritized tracing is performed from a route node of the structured document data using the structured guide data; a structure stream data storage unit that stores the structure stream data; a query data accepting unit that accepts input of query data; a path pattern compile unit that creates a path pattern processing table which specifies a processing procedure specialized for the query data by executing a syntax analysis of the accepted query data and creating a primary structure graph in which a relationship between tags is expressed by a tree format, and collating the primary structure graph and the structured guide data, converting the primary structure graph and the structured guide data into the unique identification information, and creating a secondary structure graph where unnecessary nodes are removed, the path pattern processing table including: an Entry Table which has a sequence element corresponding to the unique identification information and executes a process corresponding to the unique identification information; a Place which is a storage area for holding a queue of Tokens as intermediate data, the Place representing a position of the unique identification information; and a Trans which connects one Place and another Place and flows a Token held at a high-order Place to a low-order Place, the path pattern processing table being created by pasting the process corresponding to the unique identification information of the Entry Table and linking the Place and the Trans recursively from the route node to a terminal node of the secondary structure graph; and a structure stream scanning unit that acquires the structure stream data from the structure stream data storage unit, and gives the structure stream to the path pattern processing table so as to execute the processing procedure. | 1. A structured document management apparatus comprising: a document data accepting unit that accepts input of structured document data having a hierarchical logic structure; a structure guide data storage unit that stores structure guide data which is a summary of hierarchical structure information of the structured document, wherein the structure guide data contains a guide node where unique identification information is allocated; a structure stream converting unit that executes a syntax analysis of the structured document data, and converts the structured document data into structure stream data as one-dimensional sequence data by arranging the unique identification information of guide nodes corresponding to nodes that pass when depth-prioritized tracing is performed from a route node of the structured document data using the structured guide data; a structure stream data storage unit that stores the structure stream data; a query data accepting unit that accepts input of query data; a path pattern compile unit that creates a path pattern processing table which specifies a processing procedure specialized for the query data by executing a syntax analysis of the accepted query data and creating a primary structure graph in which a relationship between tags is expressed by a tree format, and collating the primary structure graph and the structured guide data, converting the primary structure graph and the structured guide data into the unique identification information, and creating a secondary structure graph where unnecessary nodes are removed, the path pattern processing table including: an Entry Table which has a sequence element corresponding to the unique identification information and executes a process corresponding to the unique identification information; a Place which is a storage area for holding a queue of Tokens as intermediate data, the Place representing a position of the unique identification information; and a Trans which connects one Place and another Place and flows a Token held at a high-order Place to a low-order Place, the path pattern processing table being created by pasting the process corresponding to the unique identification information of the Entry Table and linking the Place and the Trans recursively from the route node to a terminal node of the secondary structure graph; and a structure stream scanning unit that acquires the structure stream data from the structure stream data storage unit, and gives the structure stream to the path pattern processing table so as to execute the processing procedure. 4. The apparatus according to claim 1 , wherein the path pattern compile unit incorporates a procedure for skipping a portion of the structure stream data in the path pattern processing table when the structure information appears due to statistics information of the structured document data. | 0.608289 |
9,182,952 | 34 | 36 | 34. A non-transitory computer-readable medium storing instructions that are executable by a processor to cause the processor to perform operations comprising: capturing an image of a scene that includes a portion of a diagram representing functional blocks, wherein the functional blocks include at least a first functional block associated with a first computer operation; applying functional block recognition rules to image data of the image to recognize the functional blocks; determining whether the functional blocks comply with functional block syntax rules, wherein the functional block syntax rules indicate a hierarchy of operations associated with the functional blocks; and computer-generating a functional graph corresponding to the diagram based on the functional blocks complying with the functional block syntax rules, wherein the functional graph includes a graphical representation of the functional blocks. | 34. A non-transitory computer-readable medium storing instructions that are executable by a processor to cause the processor to perform operations comprising: capturing an image of a scene that includes a portion of a diagram representing functional blocks, wherein the functional blocks include at least a first functional block associated with a first computer operation; applying functional block recognition rules to image data of the image to recognize the functional blocks; determining whether the functional blocks comply with functional block syntax rules, wherein the functional block syntax rules indicate a hierarchy of operations associated with the functional blocks; and computer-generating a functional graph corresponding to the diagram based on the functional blocks complying with the functional block syntax rules, wherein the functional graph includes a graphical representation of the functional blocks. 36. The computer-readable medium of claim 34 , wherein applying the functional block recognition rules to the image data includes applying graph topology rules to the image data, and wherein the graph topology rules include rules for recognizing a functional block of the functional graph, a decision block of the functional graph, or a combination thereof. | 0.5 |
8,458,195 | 1 | 7 | 1. A computer-implemented method for determining similar users, comprising: receiving information for a source user, at a computer system, the information including at least one topic and a user value for each topic, where: the user value includes a user authority value representing a user expertise related to that topic and a user interest value representing a degree of user association with that topic, and the user value represents how strongly the user is associated with that topic; generating similarity scores based on a user value for each topic for the source user and a user value for the same topic for each user in a set of users, where each user in the set of users is associated with a user value for each topic; selecting one or more similar users based on the generated similarity scores; outputting one or more of the selected users; and outputting the identity of one or more overlapping topics and a value indicating a degree of overlap for each overlapping topic. | 1. A computer-implemented method for determining similar users, comprising: receiving information for a source user, at a computer system, the information including at least one topic and a user value for each topic, where: the user value includes a user authority value representing a user expertise related to that topic and a user interest value representing a degree of user association with that topic, and the user value represents how strongly the user is associated with that topic; generating similarity scores based on a user value for each topic for the source user and a user value for the same topic for each user in a set of users, where each user in the set of users is associated with a user value for each topic; selecting one or more similar users based on the generated similarity scores; outputting one or more of the selected users; and outputting the identity of one or more overlapping topics and a value indicating a degree of overlap for each overlapping topic. 7. The method of claim 1 , wherein the one or more similar users are selected based on an automatically determined threshold similarity score. | 0.643216 |
8,568,451 | 1 | 3 | 1. An anchor assembly comprising: an anchor body comprising an anchor formed in one piece with a yoke; said yoke has first and second arms and forms a U shape; a shaft spanning the yoke of the anchor body between the first and second arms of the yoke; a saddle having a first bore, wherein the shaft is received through said first bore; said saddle adapted to receive a member; a compression unit that is positioned in a second bore of the saddle adjacent the shaft, and said compression unit adapted to be adjacent the member received in said saddle; a set that is received in said saddle and adapted to selectively apply force against the member received in said saddle and thereby apply force through said compression unit to said shaft; and wherein said compression unit includes a first recess that is adapted to receive the member and a second recess that can receive the shaft. | 1. An anchor assembly comprising: an anchor body comprising an anchor formed in one piece with a yoke; said yoke has first and second arms and forms a U shape; a shaft spanning the yoke of the anchor body between the first and second arms of the yoke; a saddle having a first bore, wherein the shaft is received through said first bore; said saddle adapted to receive a member; a compression unit that is positioned in a second bore of the saddle adjacent the shaft, and said compression unit adapted to be adjacent the member received in said saddle; a set that is received in said saddle and adapted to selectively apply force against the member received in said saddle and thereby apply force through said compression unit to said shaft; and wherein said compression unit includes a first recess that is adapted to receive the member and a second recess that can receive the shaft. 3. The anchor assembly of claim 1 wherein said first recess is not aligned with said second recess. | 0.762019 |
9,633,082 | 5 | 7 | 5. The search result ranking method as described in claim 1 , wherein the objects subjected to user actions are objects that were selected from among the search results. | 5. The search result ranking method as described in claim 1 , wherein the objects subjected to user actions are objects that were selected from among the search results. 7. The search result ranking method as described in claim 5 , further comprising: classifying objects selected from among the search results with the selected set, wherein the adjusting of the rank of objects that are to be displayed or to be ranked and whose attribute characteristics comply with the reference norms comprises: calculating a commonality level of each attribute characteristic in the selected set based on the user action information on the objects in the selected set; ranking various attribute characteristics in the selected set and unselected set in order of highest to lowest commonality level; selecting a pre-established quantity of top-ranked attribute characteristics to serve as reference norms; and raising the rank of objects that are to be displayed or to be ranked and whose attribute characteristics comply with the reference norms. | 0.5 |
9,754,040 | 1 | 11 | 1. A computer-implemented method comprising: receiving, from a first client device, an identification of user group configuration settings for a user group comprising a plurality of users, the user group configuration settings identifying (i) a first plurality of content items available to be retrieved from a first plurality of remote content provider servers and to be provided in web pages of the user group for use by users in the user group, and (ii) the plurality of users in the user group; receiving, from a second client device that is different than the first client device, data identifying personal configuration settings that personalize a web page of the user group for a first user, the personal configuration settings for the first user specifying a second plurality of content items selected by the first user to be retrieved from a second plurality of remote content provider servers and to be included in the web page of the user group personalized for the first user; receiving, from the second client device, a request that identifies the web page of the user group, wherein the request includes a universal resource locator (URL) identifying the user group; in response to receiving the request that identifies the web page of the user group, determining, at least partly based on parsing the URL, that (i) the web page requested is for the user group, (ii) a user of the second client device is in the user group that includes the web page identified by the request, and (iii) the data identifying personal configuration settings that personalize the web page of the user group to the first user was previously received; in response to determining that (i) the web page requested is for the user group, (ii) the user of the second client device is in the user group that includes the web page identified by the request, and (iii) the data identifying personal configuration settings that personalize the web page of the user group to the first user was previously received, generating a first personal web page in accordance with both the user group configuration settings for the user group that identify (i) the first plurality of content items available to be retrieved from the first plurality of remote content provider servers and to be provided in web pages of the user group for use by users in the user group, and (ii) the plurality of users in the user group, and the personal configuration settings that personalize the web page of the user group to the first user, the first personal web page including: one or more visualizations of one or more of a first plurality of content modules that provide the first plurality of content items from the first plurality of remote content provider servers; and one or more visualizations of a second plurality of content modules that provide the second plurality of content items from the second plurality of remote content provider servers; and sending the first personal web page over a network to the second client device. | 1. A computer-implemented method comprising: receiving, from a first client device, an identification of user group configuration settings for a user group comprising a plurality of users, the user group configuration settings identifying (i) a first plurality of content items available to be retrieved from a first plurality of remote content provider servers and to be provided in web pages of the user group for use by users in the user group, and (ii) the plurality of users in the user group; receiving, from a second client device that is different than the first client device, data identifying personal configuration settings that personalize a web page of the user group for a first user, the personal configuration settings for the first user specifying a second plurality of content items selected by the first user to be retrieved from a second plurality of remote content provider servers and to be included in the web page of the user group personalized for the first user; receiving, from the second client device, a request that identifies the web page of the user group, wherein the request includes a universal resource locator (URL) identifying the user group; in response to receiving the request that identifies the web page of the user group, determining, at least partly based on parsing the URL, that (i) the web page requested is for the user group, (ii) a user of the second client device is in the user group that includes the web page identified by the request, and (iii) the data identifying personal configuration settings that personalize the web page of the user group to the first user was previously received; in response to determining that (i) the web page requested is for the user group, (ii) the user of the second client device is in the user group that includes the web page identified by the request, and (iii) the data identifying personal configuration settings that personalize the web page of the user group to the first user was previously received, generating a first personal web page in accordance with both the user group configuration settings for the user group that identify (i) the first plurality of content items available to be retrieved from the first plurality of remote content provider servers and to be provided in web pages of the user group for use by users in the user group, and (ii) the plurality of users in the user group, and the personal configuration settings that personalize the web page of the user group to the first user, the first personal web page including: one or more visualizations of one or more of a first plurality of content modules that provide the first plurality of content items from the first plurality of remote content provider servers; and one or more visualizations of a second plurality of content modules that provide the second plurality of content items from the second plurality of remote content provider servers; and sending the first personal web page over a network to the second client device. 11. The method of claim 1 , further comprising storing at least a portion of the user group configuration settings using a scalable storage system platform. | 0.890449 |
9,093,062 | 10 | 13 | 10. A computer system for delivering an announcement in two or more languages, the system comprising: a plurality of microphones deployed in an environment; and one or more processors, one or more computer-readable memories, one or more computer-readable tangible storage devices, and program instructions stored on at least one of the one or more storage devices for execution by at least one of the one or more processors via at least one of the one or more memories, the program instructions comprising: program instructions to receive, from the plurality of microphones deployed in the environment, input representative of audio of a group of human speakers speaking in the environment in two or more natural languages during a duration of time, wherein each microphone of the plurality of microphones transmits respective audio signals on separate channels; program instructions to process the input to identify the two or more natural languages being spoken in the environment by the group of human speakers during the duration of time; program instructions to process the audio signals on each channel to identify a first utterance match for one of the identified two or more natural languages; program instructions to, for each of the identified two or more natural languages, calculate a number of channels on which a first utterance match for that natural language was identified; program instructions to process the input to determine a relative proportion of each of the identified two or more natural languages being spoken in the environment by the group of human speakers during the duration of time, wherein the relative proportion of a natural language is based, at least in part, on the calculated number of channels on which a first utterance match for that natural language was identified; program instructions to determine two or more natural languages in which to deliver the announcement based, at least in part, on the relative proportion of each of the identified two or more natural languages being spoken in the environment by the group of human speakers during the duration of time; program instructions to determine a descending sequential order in which to deliver the announcement in the determined two or more natural languages based, at least in part, on the relative proportion of each of the identified two or more natural languages; and program instructions to cause to be delivered the announcement in the determined two or more natural languages in the determined descending sequential order by transmitting the announcement to an announcement system. | 10. A computer system for delivering an announcement in two or more languages, the system comprising: a plurality of microphones deployed in an environment; and one or more processors, one or more computer-readable memories, one or more computer-readable tangible storage devices, and program instructions stored on at least one of the one or more storage devices for execution by at least one of the one or more processors via at least one of the one or more memories, the program instructions comprising: program instructions to receive, from the plurality of microphones deployed in the environment, input representative of audio of a group of human speakers speaking in the environment in two or more natural languages during a duration of time, wherein each microphone of the plurality of microphones transmits respective audio signals on separate channels; program instructions to process the input to identify the two or more natural languages being spoken in the environment by the group of human speakers during the duration of time; program instructions to process the audio signals on each channel to identify a first utterance match for one of the identified two or more natural languages; program instructions to, for each of the identified two or more natural languages, calculate a number of channels on which a first utterance match for that natural language was identified; program instructions to process the input to determine a relative proportion of each of the identified two or more natural languages being spoken in the environment by the group of human speakers during the duration of time, wherein the relative proportion of a natural language is based, at least in part, on the calculated number of channels on which a first utterance match for that natural language was identified; program instructions to determine two or more natural languages in which to deliver the announcement based, at least in part, on the relative proportion of each of the identified two or more natural languages being spoken in the environment by the group of human speakers during the duration of time; program instructions to determine a descending sequential order in which to deliver the announcement in the determined two or more natural languages based, at least in part, on the relative proportion of each of the identified two or more natural languages; and program instructions to cause to be delivered the announcement in the determined two or more natural languages in the determined descending sequential order by transmitting the announcement to an announcement system. 13. The system of claim 10 , wherein the program instructions further comprise program instructions to cause the announcement to be delivered visually. | 0.731317 |
8,595,004 | 8 | 9 | 8. A pronunciation variation rule extraction method comprising: storing base form pronunciation data representing base form pronunciation of speech data; generating a sub word language model from said base form pronunciation data; recognizing said speech data by using said sub word language model; extracting a difference between a recognition result of said recognizing and said base form pronunciation data by comparing said recognition result and said base form pronunciation data; and controlling one weight value for said sub word language model, wherein said controlling includes outputting a plurality of said weight values, wherein said recognizing includes recognizing said speech data for each of said plurality of weight values, and wherein said controlling further includes determining whether or not said weight value should be updated, based on said difference when said difference is extracted. | 8. A pronunciation variation rule extraction method comprising: storing base form pronunciation data representing base form pronunciation of speech data; generating a sub word language model from said base form pronunciation data; recognizing said speech data by using said sub word language model; extracting a difference between a recognition result of said recognizing and said base form pronunciation data by comparing said recognition result and said base form pronunciation data; and controlling one weight value for said sub word language model, wherein said controlling includes outputting a plurality of said weight values, wherein said recognizing includes recognizing said speech data for each of said plurality of weight values, and wherein said controlling further includes determining whether or not said weight value should be updated, based on said difference when said difference is extracted. 9. The pronunciation variation rule extraction method according to claim 8 , wherein said controlling further includes updating said weight value, when said difference is smaller than a predetermined threshold, such that said weight value is decreased. | 0.763602 |
9,965,774 | 4 | 5 | 4. The method of claim 3 , wherein the topic is determined based on one or more characteristics of the digital magazine server user. | 4. The method of claim 3 , wherein the topic is determined based on one or more characteristics of the digital magazine server user. 5. The method of claim 4 , wherein one or more characteristics of the digital magazine server user includes a location within a threshold distance of a location specified by the request. | 0.5 |
8,561,013 | 10 | 11 | 10. A method for processing Component Business Model (CBM) related data, the process comprising the following steps: providing CBM related data comprising a heat map; at a first converting step, automatically converting the CBM related data to a Unified Modeling Language (UML) representation; and subsequent to the first converting step, at a second converting step, converting the UML representation of the CBM related data to an Services Oriented Architucture (SOA) service model; wherein the first converting step comprises the following sub-steps: parsing the CBM related data; retrieving a plurality of CBM elements; processing the plurality of CBM elements; identifying a plurality of UML elements that respectively correspond to the plurality of CBM elements; and forming the plurality of UML elements into the UML representation of the CBM related data. | 10. A method for processing Component Business Model (CBM) related data, the process comprising the following steps: providing CBM related data comprising a heat map; at a first converting step, automatically converting the CBM related data to a Unified Modeling Language (UML) representation; and subsequent to the first converting step, at a second converting step, converting the UML representation of the CBM related data to an Services Oriented Architucture (SOA) service model; wherein the first converting step comprises the following sub-steps: parsing the CBM related data; retrieving a plurality of CBM elements; processing the plurality of CBM elements; identifying a plurality of UML elements that respectively correspond to the plurality of CBM elements; and forming the plurality of UML elements into the UML representation of the CBM related data. 11. The method of claim 10 wherein the SOA service model is a domain based SOA service model. | 0.5 |
9,760,629 | 1 | 2 | 1. A computer-implemented method comprising: receiving, by one or more processors, a search query from a user device via a network; determining, by the one or more processors and based on the search query, clusters of documents that are associated with the search query, the clusters of documents being related to different topics; providing on a graphical user interface of a user device, by the one or more processors and for presentations in a first section of a document, information regarding a plurality of the clusters of documents, the information identifying one or more respective documents associated with each cluster of the plurality of clusters of documents, and the one or more respective documents being aggregated from different genres and being related to a common topic; providing on the graphical user interface of the user device, by the one or more processors and for presentation in a second section of the document, user comments from a first user related to at least one cluster of the plurality of clusters of documents, wherein the first section of the document is different from the second section of the document; receiving, by the one or more processor, a rating from a second user for the user comments, where the rating is based on a relevance, depth, or usefulness of at least one user comment; providing, by the one or more processor, a discussion forum for the user comments, the discussion forum allowing a second user to comment on the user comments; ranking, by the one or more processors and for presentation in the second section of the document, the user comments based on the rating from the second user, wherein the ranking the user comments further comprises: ranking comments of the user comments, posted by users who are named in a document of at least one cluster of the plurality of clusters of documents, higher than comments of the user comments that are posted by users who are not named in a document of the at least one cluster; and receiving the user comments related to the clusters of documents; and storing, in a memory of a computer, the received user comments. | 1. A computer-implemented method comprising: receiving, by one or more processors, a search query from a user device via a network; determining, by the one or more processors and based on the search query, clusters of documents that are associated with the search query, the clusters of documents being related to different topics; providing on a graphical user interface of a user device, by the one or more processors and for presentations in a first section of a document, information regarding a plurality of the clusters of documents, the information identifying one or more respective documents associated with each cluster of the plurality of clusters of documents, and the one or more respective documents being aggregated from different genres and being related to a common topic; providing on the graphical user interface of the user device, by the one or more processors and for presentation in a second section of the document, user comments from a first user related to at least one cluster of the plurality of clusters of documents, wherein the first section of the document is different from the second section of the document; receiving, by the one or more processor, a rating from a second user for the user comments, where the rating is based on a relevance, depth, or usefulness of at least one user comment; providing, by the one or more processor, a discussion forum for the user comments, the discussion forum allowing a second user to comment on the user comments; ranking, by the one or more processors and for presentation in the second section of the document, the user comments based on the rating from the second user, wherein the ranking the user comments further comprises: ranking comments of the user comments, posted by users who are named in a document of at least one cluster of the plurality of clusters of documents, higher than comments of the user comments that are posted by users who are not named in a document of the at least one cluster; and receiving the user comments related to the clusters of documents; and storing, in a memory of a computer, the received user comments. 2. The method of claim 1 , where providing the user comments comprises: ranking the user comments; and providing, for presentation, the ranked user comments. | 0.558989 |
9,082,310 | 9 | 10 | 9. The method of claim 1 , wherein (b) comprises identifying a plurality of portions of the data set based on the first region definition, wherein the first region includes the plurality of portions. | 9. The method of claim 1 , wherein (b) comprises identifying a plurality of portions of the data set based on the first region definition, wherein the first region includes the plurality of portions. 10. The method of claim 9 , wherein (d) comprises providing output to the user representing the plurality of portions of the data set. | 0.77592 |
9,727,642 | 1 | 3 | 1. A method, in a data processing system, for generating a set of questions to evaluate a link between concept entities, comprising: receiving, by the data processing system, a set of evidential data specifying a plurality of information concept entities; analyzing, by the data processing system, an ontological data structure associated with the set of evidential data to identify potential ontological relationships between information concept entities in the plurality of information concept entities; automatically generating, by the data processing system, a hypothetical link between at least two information concept entities in the plurality of information concept entities based on results of the analysis, wherein the hypothetical link represents a scenario involving the at least two information concept entities; retrieving, by the data processing system, a set of questions corresponding to the hypothetical link between the at least two information concept entities; pruning, by the data processing system, the set of questions into a subset of questions based on at least one of characteristics of the hypothetical link or characteristics of the at least two information concept entities; processing, by the data processing system, the pruned set of questions based on a corpus of evidence to thereby generate a measure of support for or against the hypothetical link being an actual link between the at least two information concept entities; and outputting, by the data processing system, an validity indication for the hypothetical link indicating whether or not the hypothetical link is an actual link between the at least two information concept entities. | 1. A method, in a data processing system, for generating a set of questions to evaluate a link between concept entities, comprising: receiving, by the data processing system, a set of evidential data specifying a plurality of information concept entities; analyzing, by the data processing system, an ontological data structure associated with the set of evidential data to identify potential ontological relationships between information concept entities in the plurality of information concept entities; automatically generating, by the data processing system, a hypothetical link between at least two information concept entities in the plurality of information concept entities based on results of the analysis, wherein the hypothetical link represents a scenario involving the at least two information concept entities; retrieving, by the data processing system, a set of questions corresponding to the hypothetical link between the at least two information concept entities; pruning, by the data processing system, the set of questions into a subset of questions based on at least one of characteristics of the hypothetical link or characteristics of the at least two information concept entities; processing, by the data processing system, the pruned set of questions based on a corpus of evidence to thereby generate a measure of support for or against the hypothetical link being an actual link between the at least two information concept entities; and outputting, by the data processing system, an validity indication for the hypothetical link indicating whether or not the hypothetical link is an actual link between the at least two information concept entities. 3. The method of claim 1 , wherein the set of questions is generated by performing a lookup in a question template database of types of the information concept entities and a type of a relationship specified by the hypothetical link to identify a set of question templates corresponding to the types of information concept entities and type of relationship. | 0.5 |
9,977,775 | 4 | 5 | 4. The computer-readable storage medium of claim 1 , the data structure further comprising a fourth table comprised of entries each representing a different part of speech, each entry of the fourth table containing a word type ID identifying its word type, each entry of the second table further containing a word type ID identifying a word type to which its definition corresponds. | 4. The computer-readable storage medium of claim 1 , the data structure further comprising a fourth table comprised of entries each representing a different part of speech, each entry of the fourth table containing a word type ID identifying its word type, each entry of the second table further containing a word type ID identifying a word type to which its definition corresponds. 5. The computer-readable storage medium of claim 4 wherein a distinguished entity of the fourth table contains a word type ID indicating a word type corresponding to a particular part of speech. | 0.5 |
9,288,275 | 1 | 18 | 1. An event-centric computer-implemented social networking platform, said social networking platform accessible to users via a computer network, said social networking platform comprising: a first repository configured to store at least user related information; a second repository configured to store the information corresponding to catalog offerings; a third repository configured to store at least event-related information corresponding to said users, information corresponding to resources uploaded onto a social networking platform by said users, information corresponding to access privileges and action permissions granted to respective users; an event planning module accessible to said users, said event planning module comprising: a receiving module configured to receive a request from a user towards organizing an event based on at least one of catalog offerings related activities/catalog offerings, said request including at least event related information; a first search module configured to search said second repository for catalog offerings related to said event related information, said first search module further configured to generate a list of catalog offerings related to event specified by a user based on user related information; a first selection module configured to enable selection of at least one catalog offering, from said list of catalog offerings; an updating module cooperating with said third repository, said updating module configured to update the event-related information stored in said third repository; a second search module cooperating with said first repository and third repository, said second search module configured to search friend list for users, based on a pre-defined criteria, said second search module configured to categorize users in search result into pre-determined invitee categories; an invitation module cooperating with said event planning module and configured to generate an invitee list for an event including user names selected from at least one of said pre-determined invitee categories and non-registered invitees, said invitation module configured to selectively transmit an invitation inviting users included in said invitee list to attend said event, said invitation module further configured to receive and track the responses of invited users; and a presentation module accessible to users, said presentation module configured to display a list of event invitations including past events and the events planned for future dates, said presentation manager configured to control users' access to said list of event invitations, said presentation manager configured to provide users with selective access to contents of a listed event invitation, said presentation manager further configured to enable said users to view the listed event invitation, edit the listed event invitation, comment on the listed event invitation and add photos/social media files on to the listed event invitation; a notification module configured to generate notifications corresponding to activities performed by said users on the social networking platform, said notification module further configured to transmit notifications to other users included in the friend list associated with said users. | 1. An event-centric computer-implemented social networking platform, said social networking platform accessible to users via a computer network, said social networking platform comprising: a first repository configured to store at least user related information; a second repository configured to store the information corresponding to catalog offerings; a third repository configured to store at least event-related information corresponding to said users, information corresponding to resources uploaded onto a social networking platform by said users, information corresponding to access privileges and action permissions granted to respective users; an event planning module accessible to said users, said event planning module comprising: a receiving module configured to receive a request from a user towards organizing an event based on at least one of catalog offerings related activities/catalog offerings, said request including at least event related information; a first search module configured to search said second repository for catalog offerings related to said event related information, said first search module further configured to generate a list of catalog offerings related to event specified by a user based on user related information; a first selection module configured to enable selection of at least one catalog offering, from said list of catalog offerings; an updating module cooperating with said third repository, said updating module configured to update the event-related information stored in said third repository; a second search module cooperating with said first repository and third repository, said second search module configured to search friend list for users, based on a pre-defined criteria, said second search module configured to categorize users in search result into pre-determined invitee categories; an invitation module cooperating with said event planning module and configured to generate an invitee list for an event including user names selected from at least one of said pre-determined invitee categories and non-registered invitees, said invitation module configured to selectively transmit an invitation inviting users included in said invitee list to attend said event, said invitation module further configured to receive and track the responses of invited users; and a presentation module accessible to users, said presentation module configured to display a list of event invitations including past events and the events planned for future dates, said presentation manager configured to control users' access to said list of event invitations, said presentation manager configured to provide users with selective access to contents of a listed event invitation, said presentation manager further configured to enable said users to view the listed event invitation, edit the listed event invitation, comment on the listed event invitation and add photos/social media files on to the listed event invitation; a notification module configured to generate notifications corresponding to activities performed by said users on the social networking platform, said notification module further configured to transmit notifications to other users included in the friend list associated with said users. 18. The social networking platform as claimed in claim 1 , wherein said event planning module is configured to enable said users to announce their availability for event participation during a specific time period, their interest towards attending an event based on specific catalog offerings, one or more activity types associated with said catalog offerings, said event planning module configured to enable user to express their preference of friends from whom said users wish to receive event invitations in response to their announcement, said event planning module still further configured to notify other users present in said user's friend list of the announcement should a notified user wish to invite announcing user and other users to a planned event. | 0.586862 |
8,452,793 | 1 | 14 | 1. A machine executed method comprising: presenting, at a local client machine, a first webpage that includes a first plurality of search results based on a user-provided search criteria, wherein a copy of the first webpage is locally cached; receiving a first user selection of a search result of the first plurality of search results included on the first webpage, wherein selection of the search result causes a document corresponding to the first user selection to be displayed; modifying, at the local client machine, the locally cached copy of the first webpage to include metadata associated with the first user selection of the search result; in response to receiving a request to re-display the first-webpage: inspecting the locally cached copy of the first webpage for any metadata, added to the locally cached copy subsequent to presenting the first webpage, associated with user interaction on the first web page; detecting that the locally cached copy of the first webpage has been modified to include the metadata associated with the first user selection of the search result; in response to the detecting step, obtaining content based on the metadata; responding to the request to re-display the first webpage by displaying a modified search results webpage, wherein the modified search results webpage has been changed relative to the first web page based, at least in part, on the content that was obtained based on the metadata. | 1. A machine executed method comprising: presenting, at a local client machine, a first webpage that includes a first plurality of search results based on a user-provided search criteria, wherein a copy of the first webpage is locally cached; receiving a first user selection of a search result of the first plurality of search results included on the first webpage, wherein selection of the search result causes a document corresponding to the first user selection to be displayed; modifying, at the local client machine, the locally cached copy of the first webpage to include metadata associated with the first user selection of the search result; in response to receiving a request to re-display the first-webpage: inspecting the locally cached copy of the first webpage for any metadata, added to the locally cached copy subsequent to presenting the first webpage, associated with user interaction on the first web page; detecting that the locally cached copy of the first webpage has been modified to include the metadata associated with the first user selection of the search result; in response to the detecting step, obtaining content based on the metadata; responding to the request to re-display the first webpage by displaying a modified search results webpage, wherein the modified search results webpage has been changed relative to the first web page based, at least in part, on the content that was obtained based on the metadata. 14. The method of claim 1 , wherein the metadata is stored in the locally cached copy of the first webpage in a manner such that the metadata would not be displayed if the locally cached copy of the first webpage were to be rendered in a browser. | 0.872539 |
9,460,076 | 3 | 4 | 3. The method of claim 1 , further comprising speech tagging the text units from the plurality of text units from the corpus of text documents into phrases. | 3. The method of claim 1 , further comprising speech tagging the text units from the plurality of text units from the corpus of text documents into phrases. 4. The method of claim 3 , further comprising storing the phrases in a respective factorized matrix or a factorized tensor as a first and a last word of the phrase. | 0.5 |
9,704,177 | 15 | 18 | 15. A computer-readable storage device storing computer instructions, which when executed by a processor of a computer, causes the computer to: execute a Turing test to test the one or more avatars, wherein the Turing test evaluates positional movement of each of the one or more avatars; determine the behavior characteristics of the one of the one or more avatars, wherein the behavior characteristics comprise whether each of the one or more avatars is able to demonstrate human intelligence; retrieve from an avatar its multimedia characteristics, the VU system comprising one or more avatars that each have behavior characteristics, wherein at least one of the avatars is an automated, non-human operated spam avatar created by an advertiser operating within the VU, the VU system having memory that stores behavior characteristics of known spam avatars; compare the retrieved behavior characteristics with behavior characteristics of known spam avatars; identify similarities between the retrieved behavior characteristics with behavior characteristics of known spam avatars; and identify the avatar as an automated, non-human operated spam avatar based upon the similarities between the behavior characteristics of the avatar with the behavior characteristics of the known spam avatars. | 15. A computer-readable storage device storing computer instructions, which when executed by a processor of a computer, causes the computer to: execute a Turing test to test the one or more avatars, wherein the Turing test evaluates positional movement of each of the one or more avatars; determine the behavior characteristics of the one of the one or more avatars, wherein the behavior characteristics comprise whether each of the one or more avatars is able to demonstrate human intelligence; retrieve from an avatar its multimedia characteristics, the VU system comprising one or more avatars that each have behavior characteristics, wherein at least one of the avatars is an automated, non-human operated spam avatar created by an advertiser operating within the VU, the VU system having memory that stores behavior characteristics of known spam avatars; compare the retrieved behavior characteristics with behavior characteristics of known spam avatars; identify similarities between the retrieved behavior characteristics with behavior characteristics of known spam avatars; and identify the avatar as an automated, non-human operated spam avatar based upon the similarities between the behavior characteristics of the avatar with the behavior characteristics of the known spam avatars. 18. The computer-readable storage device as defined in claim 15 wherein the Turing test further evaluates an ability of the one or more avatars to recall and demonstrate a series of commands. | 0.5 |
9,183,515 | 1 | 10 | 1. A method comprising: receiving input from a first user, the received input associated with published content on a webpage; determining a context of the first user and based on the input the published content; retrieving content and context from a plurality of web site servers hosting a plurality of different websites, wherein the context is used to determine (1) what information is added to a sharing interface and (2) which one of the plurality of different websites will the sharing interface be pushed to, the context including information about the webpage based on the determined context; generating customized content by processing the retrieved content based on the determined context; receiving and processing a request for the sharing interface; providing the sharing interface including the customized content using the context and an endorsement; adding the retrieved content based on the context to the sharing interface, the sharing interface overlaid on a portion of the webpage and including at least one area for displaying the retrieved content and receiving the customized content, the at least one area for displaying the retrieved content and receiving customized content allowing for additional input of information into the sharing interface including input of comments and at least one user identifier associated with a second user, the second user an intended recipient of the customized content; adding an action button to the sharing interface; sending the sharing interface for display; transferring the customized content in the sharing interface based on the context in response to user selection of the action button; and sending the customized content to the second user associated with the at least one user identifier. | 1. A method comprising: receiving input from a first user, the received input associated with published content on a webpage; determining a context of the first user and based on the input the published content; retrieving content and context from a plurality of web site servers hosting a plurality of different websites, wherein the context is used to determine (1) what information is added to a sharing interface and (2) which one of the plurality of different websites will the sharing interface be pushed to, the context including information about the webpage based on the determined context; generating customized content by processing the retrieved content based on the determined context; receiving and processing a request for the sharing interface; providing the sharing interface including the customized content using the context and an endorsement; adding the retrieved content based on the context to the sharing interface, the sharing interface overlaid on a portion of the webpage and including at least one area for displaying the retrieved content and receiving the customized content, the at least one area for displaying the retrieved content and receiving customized content allowing for additional input of information into the sharing interface including input of comments and at least one user identifier associated with a second user, the second user an intended recipient of the customized content; adding an action button to the sharing interface; sending the sharing interface for display; transferring the customized content in the sharing interface based on the context in response to user selection of the action button; and sending the customized content to the second user associated with the at least one user identifier. 10. The method of claim 1 further comprising receiving additional content for the sharing interface and sharing the additional content and the content added to the sharing interface. | 0.644531 |
8,370,352 | 1 | 14 | 1. A system for searching one or more electronic records and displaying relevant data based on the search, the system comprising: a processor; and one or more non-transitory program storage devices readable by the processor, tangibly embodying a searching unit, a visual interface and a statistical analyzer executable by the processor, wherein the searching unit is configured to search for text in the one or more electronic records that are within a context of an entered query string, wherein the context is influenced by text that precedes or follows an instance of the entered query string in the one or more electronic records wherein a context type describes a structure in which the instance of the entered query string may be presented in the one or more electronic records, wherein the context type comprises at least a phrasal context, a bullet context, or a list context, wherein the statistical analyzer is configured to analyze results of the search, provide search statistics, and order the results associated with the entered query string based on the search statistics and the context of the entered query string, and wherein the visual interface is configured to display the search statistics and the results of the search presented in the structure corresponding to the context type. | 1. A system for searching one or more electronic records and displaying relevant data based on the search, the system comprising: a processor; and one or more non-transitory program storage devices readable by the processor, tangibly embodying a searching unit, a visual interface and a statistical analyzer executable by the processor, wherein the searching unit is configured to search for text in the one or more electronic records that are within a context of an entered query string, wherein the context is influenced by text that precedes or follows an instance of the entered query string in the one or more electronic records wherein a context type describes a structure in which the instance of the entered query string may be presented in the one or more electronic records, wherein the context type comprises at least a phrasal context, a bullet context, or a list context, wherein the statistical analyzer is configured to analyze results of the search, provide search statistics, and order the results associated with the entered query string based on the search statistics and the context of the entered query string, and wherein the visual interface is configured to display the search statistics and the results of the search presented in the structure corresponding to the context type. 14. The system of claim 1 , wherein the system is further configured to combine the results of the search based on co-occurrence statistics. | 0.771987 |
Subsets and Splits