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8,712,931 | 4 | 16 | 4. A computer-implemented method for intelligently predicting user input entered on a computing device, comprising: receiving, on the computing device, user text input; accessing a text repository including a plurality of text items classified according to a probabilistic model; inferring, using a processor of the computing device, one or more input predictions by applying the probabilistic model to the user text input; presenting, using a visual output element of the computing device, a suggested text based on the one or more input predictions; receiving, on the computing device, an indication of a user override of the suggested text; and updating at least one probability of the probabilistic model, the at least one probability corresponding to the user override, wherein the at least one probability is based at least in part upon an average probability of one or more other probabilities of the probabilistic model when the user override is a new probability of the probabilistic model, the one or more other probabilities corresponding to the text items that have at least some same text as the user override. | 4. A computer-implemented method for intelligently predicting user input entered on a computing device, comprising: receiving, on the computing device, user text input; accessing a text repository including a plurality of text items classified according to a probabilistic model; inferring, using a processor of the computing device, one or more input predictions by applying the probabilistic model to the user text input; presenting, using a visual output element of the computing device, a suggested text based on the one or more input predictions; receiving, on the computing device, an indication of a user override of the suggested text; and updating at least one probability of the probabilistic model, the at least one probability corresponding to the user override, wherein the at least one probability is based at least in part upon an average probability of one or more other probabilities of the probabilistic model when the user override is a new probability of the probabilistic model, the one or more other probabilities corresponding to the text items that have at least some same text as the user override. 16. The computer-implemented method of claim 4 , wherein presenting the suggested text comprises modifying the user text input to an input prediction with at least a minimum probability. | 0.655556 |
9,626,699 | 12 | 14 | 12. A method comprising: obtaining a Document Object Model of a web page; identifying Document Object Model elements, of the Document Object Model, associated with native advertisement placement candidate containers; identifying, with the Document Object Model, HTML tag sequences that include at least L tags, where L is a specified number, repeat at least R times, where R is a specified number, and all correspond to a single element of the Document Object Model: analyzing the Document Object Model by utilizing a node flattening technique in connection with the Document Object Model, the node flattening technique comprising creating, at each node, a string including a tag name of the each node concatenated with a tag name of each child of the each node; and filtering determined candidate containers based on at least one of (1) candidate container size, (2) size of a meta-container associated with multiple candidate containers, (3) number of element types included within a candidate container, (4) anticipated display location of native advertisements associated with candidate containers, and (5) topology of the Document Object Model; based at least in part on the analysis relating to the Document Object Model, and utilizing at least some of the identified elements, determining, within the Document Object Model, one or more native advertisement placement candidate containers. | 12. A method comprising: obtaining a Document Object Model of a web page; identifying Document Object Model elements, of the Document Object Model, associated with native advertisement placement candidate containers; identifying, with the Document Object Model, HTML tag sequences that include at least L tags, where L is a specified number, repeat at least R times, where R is a specified number, and all correspond to a single element of the Document Object Model: analyzing the Document Object Model by utilizing a node flattening technique in connection with the Document Object Model, the node flattening technique comprising creating, at each node, a string including a tag name of the each node concatenated with a tag name of each child of the each node; and filtering determined candidate containers based on at least one of (1) candidate container size, (2) size of a meta-container associated with multiple candidate containers, (3) number of element types included within a candidate container, (4) anticipated display location of native advertisements associated with candidate containers, and (5) topology of the Document Object Model; based at least in part on the analysis relating to the Document Object Model, and utilizing at least some of the identified elements, determining, within the Document Object Model, one or more native advertisement placement candidate containers. 14. The method of claim 12 , wherein identifying the HTML tag sequences comprises computation utilizing a Document Object Model node flattening technique. | 0.684426 |
9,305,085 | 7 | 8 | 7. The method according to claim 1 , wherein said determining of a relevance score with respect to each post in a discussion thread comprises employing a query likelihood model with smoothing. | 7. The method according to claim 1 , wherein said determining of a relevance score with respect to each post in a discussion thread comprises employing a query likelihood model with smoothing. 8. The method according to claim 7 , wherein said employing of a query likelihood model with smoothing comprises determining an average relevance of scorewise top-k posts in a thread. | 0.5 |
8,868,512 | 1 | 8 | 1. A method for a database system, comprising: establishing a column-oriented in-memory database structure including a main store and a dictionary compressed delta store, wherein the delta store comprises a value identifier vector that includes each value of a record stored in a same row of a column of the database and a delta dictionary associated with the column of the database; receiving a transaction associated with the column; recording the transaction within the delta store; adding an entry associated with the transaction to a value log of the value identifier vector, the value log comprising a transaction identifier and a row identifier indicating a row in the value identifier vector; and adding an entry associated with the transaction to a dictionary log of the delta dictionary. | 1. A method for a database system, comprising: establishing a column-oriented in-memory database structure including a main store and a dictionary compressed delta store, wherein the delta store comprises a value identifier vector that includes each value of a record stored in a same row of a column of the database and a delta dictionary associated with the column of the database; receiving a transaction associated with the column; recording the transaction within the delta store; adding an entry associated with the transaction to a value log of the value identifier vector, the value log comprising a transaction identifier and a row identifier indicating a row in the value identifier vector; and adding an entry associated with the transaction to a dictionary log of the delta dictionary. 8. The method of claim 1 , wherein multiple columns are managed as a single table, each column being associated with a value log and dictionary log. | 0.811705 |
8,799,265 | 34 | 35 | 34. A computer readable memory having recorded thereon statements and instructions for execution by a data processing system to carry out the method of claim 16 . | 34. A computer readable memory having recorded thereon statements and instructions for execution by a data processing system to carry out the method of claim 16 . 35. The computer readable memory of claim 34 wherein the statements and instructions for execution by the data processing system contained thereon are software for operation on a standalone computer. | 0.632841 |
8,700,604 | 1 | 3 | 1. A computer-implemented method for providing natural language based content recommendations, comprising: receiving an indication of text content; processing the indicated text content using natural language processing (“NLP”) parsing and linguistic analysis to derive a list of named entities present in the indicated text; presenting an ordered list of the derived named entities, the list reflective of what the text content concerns; and presenting indicators of additional content associated with the derived named entities wherein the additional content is provided upon receiving an indication that at least one of the presented indicators has been navigated to, and wherein additional content is determined as relevant based upon a natural language processing analysis of the named entities relative to the indicated text content and of the named entities relative to a large corpus of document information or a knowledge repository, and wherein the additional content includes a representation of connections and wherein the connections are presented graphically and illustrate relationships between entities based upon actions. | 1. A computer-implemented method for providing natural language based content recommendations, comprising: receiving an indication of text content; processing the indicated text content using natural language processing (“NLP”) parsing and linguistic analysis to derive a list of named entities present in the indicated text; presenting an ordered list of the derived named entities, the list reflective of what the text content concerns; and presenting indicators of additional content associated with the derived named entities wherein the additional content is provided upon receiving an indication that at least one of the presented indicators has been navigated to, and wherein additional content is determined as relevant based upon a natural language processing analysis of the named entities relative to the indicated text content and of the named entities relative to a large corpus of document information or a knowledge repository, and wherein the additional content includes a representation of connections and wherein the connections are presented graphically and illustrate relationships between entities based upon actions. 3. The method of claims 1 wherein the additional content is determined using a search of an ontology knowledge repository. | 0.603896 |
9,881,228 | 9 | 10 | 9. An apparatus for removing a mark in a document image, the apparatus comprising: an extracting device configured to extract connected components from a binary image corresponding to the document image; a clustering device configured to cluster the connected components based on grayscale features of the connected components to obtain one clustering center; a searching device configured to search, within numerical ranges of a clustering radius R from the clustering center and a grayscale threshold T, for a combination (R, T) which causes an evaluation value based on the grayscale features of the connected components to be higher than a first evaluation threshold; and a fine removing device configured to remove the mark in the document image based on the grayscale threshold in the combination; wherein the grayscale features of the connected components comprise: a minimum one of grayscale values of pixels in the document image, which correspond to all black pixels in each of connected components; wherein the fine removing device is further configured to remove the connected components, the grayscale features of which are greater than the grayscale threshold, as the mark in the document image. | 9. An apparatus for removing a mark in a document image, the apparatus comprising: an extracting device configured to extract connected components from a binary image corresponding to the document image; a clustering device configured to cluster the connected components based on grayscale features of the connected components to obtain one clustering center; a searching device configured to search, within numerical ranges of a clustering radius R from the clustering center and a grayscale threshold T, for a combination (R, T) which causes an evaluation value based on the grayscale features of the connected components to be higher than a first evaluation threshold; and a fine removing device configured to remove the mark in the document image based on the grayscale threshold in the combination; wherein the grayscale features of the connected components comprise: a minimum one of grayscale values of pixels in the document image, which correspond to all black pixels in each of connected components; wherein the fine removing device is further configured to remove the connected components, the grayscale features of which are greater than the grayscale threshold, as the mark in the document image. 10. The apparatus according to claim 9 , wherein the clustering device is further configured to cluster the connected components based on the grayscale features and intrinsic features of the connected components to obtain the one clustering center; wherein the intrinsic features of the connected components comprise at least one of: a number of black pixels in each of the connected components, a ratio of the number of the black pixels in the connected component to a number of pixels in a bounding box of the connected component, and an aspect ratio of the bounding box of the connected component, in the binary image. | 0.5 |
7,953,720 | 7 | 8 | 7. The method of claim 6 , further comprising: identifying a fourth answer of the possible answers as an answer that is contradictory to the third answer; and determining a supported score for the fourth answer. | 7. The method of claim 6 , further comprising: identifying a fourth answer of the possible answers as an answer that is contradictory to the third answer; and determining a supported score for the fourth answer. 8. The method of claim 7 , wherein the first condition further includes the best supported score exceeding the supported score of the fourth answer by at least a predefined margin. | 0.745042 |
8,935,272 | 5 | 6 | 5. The method of the curated answers system of claim 4 further comprising: generating a user group of the another user and the user based on a relevancy between the similar query and the initial query; and permitting users of the database to associate at least one of an electronic mailing address, a phone number, a biography, a personal photograph, a social media handle, and an educational background with their profile in the set of profiles. | 5. The method of the curated answers system of claim 4 further comprising: generating a user group of the another user and the user based on a relevancy between the similar query and the initial query; and permitting users of the database to associate at least one of an electronic mailing address, a phone number, a biography, a personal photograph, a social media handle, and an educational background with their profile in the set of profiles. 6. The method of the curated answers system of claim 5 further comprising: automatically populating the another profile markup page of the another user with information describing the similar query of the database that the another user has generated, wherein the automatically populating the profile markup page of the user with information describing the initial query of the database that the user has generated and the automatically populating the another profile markup page of the another user with information describing the similar query of the database, are both performed through automatic observation and monitoring of activity of the user and the another user in interacting with the database. | 0.5 |
9,361,398 | 1 | 2 | 1. A method for representing informational content of a stream of tag-language messages, the method comprising: from each of a plurality of tag-language messages of a stream of tag-language messages, processing a plurality of open tags, wherein each open tag corresponds to an element in the corresponding tag-language message; and wherein the stream of tag-language messages comprises a first message and a second message with the first message having a first hierarchical format and the second message having a second hierarchical format that is different than the first hierarchical format; in response to processing the first message, automatically creating a relational table based on the processed first message and storing the relational table in a relational database; determining that the second hierarchal format comprises a hierarchical format (a) not previously processed, (b) not previously associated with the relational table stored in the relational database, and (c) not previously associated with a previously-created data column of the relational table; and in response to determining that the second hierarchal format comprises a hierarchical format (a) not previously processed, (b) not previously associated with the relational table stored in the relational database, and (c) not previously associated with the previously-created data column of the relational table, automatically creating at least one new data column in the relational table, wherein the at least one new data column is configured to correspond to at least one tag from the second tag-language message, and wherein the automatically creating at least one new data column is independent of user interactions and independent of receiving a document that includes instructions to create at least one new data column in the relational table. | 1. A method for representing informational content of a stream of tag-language messages, the method comprising: from each of a plurality of tag-language messages of a stream of tag-language messages, processing a plurality of open tags, wherein each open tag corresponds to an element in the corresponding tag-language message; and wherein the stream of tag-language messages comprises a first message and a second message with the first message having a first hierarchical format and the second message having a second hierarchical format that is different than the first hierarchical format; in response to processing the first message, automatically creating a relational table based on the processed first message and storing the relational table in a relational database; determining that the second hierarchal format comprises a hierarchical format (a) not previously processed, (b) not previously associated with the relational table stored in the relational database, and (c) not previously associated with a previously-created data column of the relational table; and in response to determining that the second hierarchal format comprises a hierarchical format (a) not previously processed, (b) not previously associated with the relational table stored in the relational database, and (c) not previously associated with the previously-created data column of the relational table, automatically creating at least one new data column in the relational table, wherein the at least one new data column is configured to correspond to at least one tag from the second tag-language message, and wherein the automatically creating at least one new data column is independent of user interactions and independent of receiving a document that includes instructions to create at least one new data column in the relational table. 2. The method of claim 1 , wherein automatically creating the at least one new column in the relational table comprises: for each read open tag, automatically determining a path from a root node corresponding to a first read open tag from the corresponding tag-language message to the currently read open tag; for each determined path: automatically designating the relational table in the relational database corresponding to the path, and storing a combination of at least one of (i) a first identifier for the currently read open tag corresponding to the path, the first identifier being stored in connection with information identifying a primary key column of the designated relational table corresponding to a primary key for the designated relational table, and (ii) a second identifier of a parent of the currently read open tag, the parent comprising the open tag immediately preceding the currently read open tag in the determined path, the second identifier being stored in connection with information identifying a foreign key column of the relational table corresponding to a foreign key of the relational table; for each read open tag having at least one of a value or an attribute value: designating at least one new data column different from the primary and foreign key columns of the relational table corresponding to the determined path for the read open tag, the at least one new data column corresponding to the at least one of the value or the attribute value, and storing information identifying the at least one new data column of the relational table in connection with the stored combination of the first identifier and the second identifier for the read open tag. | 0.5 |
8,527,523 | 2 | 3 | 2. The method according to claim 1 wherein said cut-off point is selected from all ranks of documents in said control subset so as to maximize a quality criterion. | 2. The method according to claim 1 wherein said cut-off point is selected from all ranks of documents in said control subset so as to maximize a quality criterion. 3. The method according to claim 2 wherein said quality criterion comprises an F-measure. | 0.839928 |
8,108,883 | 5 | 8 | 5. The method of claim 4 further comprising: selecting a third digital file having a third digital data content, using said information management software application, before performing said step of communicating with said third-party document generation application via said application program interface (API); and dragging and dropping said selected third digital file into a displayed third data holder location of said displayed document layout representation within said data drop window, using said information management software application, such that said third data holder location of said displayed document layout representation is populated with said third digital data content before performing said step of communicating with said third-party document generation application via said at least one application program interface (API). | 5. The method of claim 4 further comprising: selecting a third digital file having a third digital data content, using said information management software application, before performing said step of communicating with said third-party document generation application via said application program interface (API); and dragging and dropping said selected third digital file into a displayed third data holder location of said displayed document layout representation within said data drop window, using said information management software application, such that said third data holder location of said displayed document layout representation is populated with said third digital data content before performing said step of communicating with said third-party document generation application via said at least one application program interface (API). 8. The method of claim 5 wherein said third digital file comprises a graphic file and said third digital data content comprises a graphic. | 0.5 |
4,214,125 | 8 | 12 | 8. A method of analyzing speech comprising the steps of generating electrical signals representative of the spoken vocabulary words and portions of spoken vocabulary words of a predetermined finite vocabulary with the vocabulary words being included into units containing a plurality of phonemes or phoneme groups, time quantizing the amplitude of the electrical signals into digital form, selectively compressing the time quantized signals by discarding selected portions of them while substantially simultaneously generating instruction signals as to which portions have been discarded, and storing selected portions of the digital signals representative of phonemes and phoneme groups in a first, addressable memory, storing the instruction signals in a second, addressable memory including instruction signals as to the sequence of addresses of the stored phonemes and phoneme groups necessary to reproduce words and sentences of the vocabulary, wherein the signal compressing and storing steps include the following steps: (a) selecting signals representative of certain phonemes and phoneme groups from the time quantized signals and replacing portions of these selected signals corresponding to parts of the pitch periods of the certain phonemes and phoneme groups by a constant amplitude signal while generating instruction signals as to which phonemes and phoneme groups have been so selected, and (b) Fourier transforming the time quantized signals to generate a set of discrete amplitudes and phase angles, adjusting the phase angles so that the inverse Fourier transformation of the amplitudes and new phases is symmetric, inverse Fourier transforming the phase adjusted amplitudes and phases, storing one-half of a selected waveform as representative of each discrete set of phase adjusted amplitudes and phases and discarding the other half of the selected waveform. | 8. A method of analyzing speech comprising the steps of generating electrical signals representative of the spoken vocabulary words and portions of spoken vocabulary words of a predetermined finite vocabulary with the vocabulary words being included into units containing a plurality of phonemes or phoneme groups, time quantizing the amplitude of the electrical signals into digital form, selectively compressing the time quantized signals by discarding selected portions of them while substantially simultaneously generating instruction signals as to which portions have been discarded, and storing selected portions of the digital signals representative of phonemes and phoneme groups in a first, addressable memory, storing the instruction signals in a second, addressable memory including instruction signals as to the sequence of addresses of the stored phonemes and phoneme groups necessary to reproduce words and sentences of the vocabulary, wherein the signal compressing and storing steps include the following steps: (a) selecting signals representative of certain phonemes and phoneme groups from the time quantized signals and replacing portions of these selected signals corresponding to parts of the pitch periods of the certain phonemes and phoneme groups by a constant amplitude signal while generating instruction signals as to which phonemes and phoneme groups have been so selected, and (b) Fourier transforming the time quantized signals to generate a set of discrete amplitudes and phase angles, adjusting the phase angles so that the inverse Fourier transformation of the amplitudes and new phases is symmetric, inverse Fourier transforming the phase adjusted amplitudes and phases, storing one-half of a selected waveform as representative of each discrete set of phase adjusted amplitudes and phases and discarding the other half of the selected waveform. 12. A method of analyzing speech as recited in claim 8, further comprising the steps of selectively reproducing certain words of the vocabulary by retrieving selected instruction signals from the second memory and using the instruction signals to sequentially extract selected portions of the stored digital signals from the first memory, and electromechanically reproducing the selected portions of the digital signals extracted from the first memory as selected audible, spoken words of the vocabulary. | 0.5 |
8,781,837 | 13 | 18 | 13. A speech recognition method comprising: in a computer processor, generating recognition result hypotheses for a speech supplied from one speech input unit, the recognition result hypotheses not being biased to either a first application or a second application; and the computer processor receiving the recognition result hypotheses and simultaneously generating a first recognition result specialized for the first application and a second recognition result, different from the first recognition result, specialized for the second application, and outputting the recognition results to the respective applications. | 13. A speech recognition method comprising: in a computer processor, generating recognition result hypotheses for a speech supplied from one speech input unit, the recognition result hypotheses not being biased to either a first application or a second application; and the computer processor receiving the recognition result hypotheses and simultaneously generating a first recognition result specialized for the first application and a second recognition result, different from the first recognition result, specialized for the second application, and outputting the recognition results to the respective applications. 18. The method according to claim 13 , wherein the applications include an application that converts a call to characters without alteration and an application that detects an inappropriate speech from the call. | 0.919404 |
9,542,436 | 12 | 14 | 12. A method comprising using a computer to manage a lifecycle of a platform, including: populating associative memory with plurality of matrices pertaining to lifecycle information about the platform, each matrix including related entity values and attribute values; causing the associative memory to create correlations between each matrix relative to the other matrices; searching the correlations for lifecycle entity and attribute values to investigate a component of the platform; and displaying any highly correlated entity and attribute values that do not include the component under investigation but are highly correlated to the component under investigation; wherein the highly correlated entity is the entity with the highest value that corresponds to a number of times the entity is returned within a repetitive search executed by an entity analytic engine; and updating a plurality of information tools with reports based on other similar components that are either further ahead or behind in the lifecycle of the specified component. | 12. A method comprising using a computer to manage a lifecycle of a platform, including: populating associative memory with plurality of matrices pertaining to lifecycle information about the platform, each matrix including related entity values and attribute values; causing the associative memory to create correlations between each matrix relative to the other matrices; searching the correlations for lifecycle entity and attribute values to investigate a component of the platform; and displaying any highly correlated entity and attribute values that do not include the component under investigation but are highly correlated to the component under investigation; wherein the highly correlated entity is the entity with the highest value that corresponds to a number of times the entity is returned within a repetitive search executed by an entity analytic engine; and updating a plurality of information tools with reports based on other similar components that are either further ahead or behind in the lifecycle of the specified component. 14. The method of claim 12 , wherein the searching is performed before the component under investigation wears out. | 0.746696 |
8,537,401 | 1 | 3 | 1. A system for controlling the automated printing of electronic documents, comprising: a computing processor; computing memory communicatively coupled with the computing processor, the computing memory having computer executable instructions stored thereon that when executed by the computer system cause the computer system to perform operations comprising: receiving in the system an electronic file comprising a plurality of electronic documents; displaying the electronic file on a display; receiving in the system input identifying a first text item located in a first area of a page in the electronic file; receiving in the system input identifying a printing option to be performed in response to locating the first text item in the electronic file; storing in the system information identifying the printing option to be performed in response to locating the first text item in the electronic file; and creating machine readable instructions for printing the plurality of electronic documents, said machine readable executable instructions comprising instructions for implementing the identified printing option to be performed in response to locating the first text item in the electronic file. | 1. A system for controlling the automated printing of electronic documents, comprising: a computing processor; computing memory communicatively coupled with the computing processor, the computing memory having computer executable instructions stored thereon that when executed by the computer system cause the computer system to perform operations comprising: receiving in the system an electronic file comprising a plurality of electronic documents; displaying the electronic file on a display; receiving in the system input identifying a first text item located in a first area of a page in the electronic file; receiving in the system input identifying a printing option to be performed in response to locating the first text item in the electronic file; storing in the system information identifying the printing option to be performed in response to locating the first text item in the electronic file; and creating machine readable instructions for printing the plurality of electronic documents, said machine readable executable instructions comprising instructions for implementing the identified printing option to be performed in response to locating the first text item in the electronic file. 3. The system of claim 1 , wherein receiving input identifying a printing option to be performed in response to locating the first text item in the electronic file comprises receiving input identifying to select an exception page. | 0.849869 |
9,891,791 | 1 | 4 | 1. A computer implemented method comprising: processing building information model data to identify a plurality of building entities, each building entity representing a respective feature of a building modeled by the building information model data, wherein processing comprises parsing the building information model data to further generate a set of tessellate geometry for each of the plurality of building entities respectively, wherein the set of tessellate geometry is used to render corresponding two dimensional views of each of the plurality of building entities; processing a plurality of simulated user interactions corresponding to presentations of the two dimensional views of each of the plurality of building entities, wherein the plurality of simulated user interactions is based on a set of permitted user interactions associated with each corresponding view of the building entity; determining relationships between different respective pairs of the building entities, including determining a particular relationship between a first building entity and a second building entity; obtaining data representing an interaction graph for the plurality of building entities, wherein the interaction graph has nodes and links, each node representing a building entity of the building, and wherein each link connects a corresponding pair of nodes and represents a simulated user interaction with a presentation of a building entity represented by a first node of the pair from the processed plurality of simulated user interactions, the simulated user interaction resulting in a request for a presentation of another building entity represented by a second node of the pair; identifying a first node in the interaction graph corresponding to the first building entity, a second node in the interaction graph corresponding to the second building entity, and a link between the first node and the second node, the link representing a first permitted user interaction from the set of permitted user interactions associated with a first presentation of the first building entity; generating a first presentation comprising a first predetermined view of the first building entity based on the generated set of tessellate geometry for the first building entity, wherein the first presentation comprises a selectable reference for the first permitted user interaction with the first presentation, the selectable reference representing the particular relationship between the first building entity and the second building entity; determining a second predetermined view of the second building entity according to the particular relationship represented by the selectable reference in the first presentation; generating a second presentation based on the generated set of tessellate geometry for the second building entity and comprising the second predetermined view of the second building entity; after generating the first presentation and the second presentation, receiving, over a network from a user device of a user, a user request for the first presentation of the first predetermined view of the first building entity; providing the first presentation of the first predetermined view of the first building entity for presentation to the user at the user device; receiving an indication of user interaction with the selectable reference within the first presentation; and in response to receiving the indication, providing the second presentation of the second predetermined view of the second building entity for presentation to the user at the user device. | 1. A computer implemented method comprising: processing building information model data to identify a plurality of building entities, each building entity representing a respective feature of a building modeled by the building information model data, wherein processing comprises parsing the building information model data to further generate a set of tessellate geometry for each of the plurality of building entities respectively, wherein the set of tessellate geometry is used to render corresponding two dimensional views of each of the plurality of building entities; processing a plurality of simulated user interactions corresponding to presentations of the two dimensional views of each of the plurality of building entities, wherein the plurality of simulated user interactions is based on a set of permitted user interactions associated with each corresponding view of the building entity; determining relationships between different respective pairs of the building entities, including determining a particular relationship between a first building entity and a second building entity; obtaining data representing an interaction graph for the plurality of building entities, wherein the interaction graph has nodes and links, each node representing a building entity of the building, and wherein each link connects a corresponding pair of nodes and represents a simulated user interaction with a presentation of a building entity represented by a first node of the pair from the processed plurality of simulated user interactions, the simulated user interaction resulting in a request for a presentation of another building entity represented by a second node of the pair; identifying a first node in the interaction graph corresponding to the first building entity, a second node in the interaction graph corresponding to the second building entity, and a link between the first node and the second node, the link representing a first permitted user interaction from the set of permitted user interactions associated with a first presentation of the first building entity; generating a first presentation comprising a first predetermined view of the first building entity based on the generated set of tessellate geometry for the first building entity, wherein the first presentation comprises a selectable reference for the first permitted user interaction with the first presentation, the selectable reference representing the particular relationship between the first building entity and the second building entity; determining a second predetermined view of the second building entity according to the particular relationship represented by the selectable reference in the first presentation; generating a second presentation based on the generated set of tessellate geometry for the second building entity and comprising the second predetermined view of the second building entity; after generating the first presentation and the second presentation, receiving, over a network from a user device of a user, a user request for the first presentation of the first predetermined view of the first building entity; providing the first presentation of the first predetermined view of the first building entity for presentation to the user at the user device; receiving an indication of user interaction with the selectable reference within the first presentation; and in response to receiving the indication, providing the second presentation of the second predetermined view of the second building entity for presentation to the user at the user device. 4. The method of claim 1 , further comprising: generating multiple layers for the first presentation, wherein each layer corresponds to a distinct building context of the first building entity. | 0.771868 |
9,165,038 | 15 | 17 | 15. A non-transitory computer-readable medium storing instructions, the instructions comprising: one or more instructions which, when executed by one or more processors, cause the one or more processors to receive a search query, the search query including a plurality of search terms; one or more instructions which, when executed by the one or more processors, cause the one or more processors to identify, based on a taxonomy, a hierarchical relationship between: a first search term of the plurality of search terms, and a second search term of the plurality of search terms, each of the first search term and the second search term being associated with a different level of the hierarchical relationship; one or more instructions which, when executed by the one or more processors, cause the one or more processors to generate an interpretation for a combination of the first search term and the second search term, the interpretation being generated based on the hierarchical relationship identified between the first search term and the second search term; one or more instructions which, when executed by the one or more processors, cause the one or more processors to determine a score for the interpretation of the combination of the first search term and the second search term; one or more instructions which, when executed by the one or more processors, cause the one or more processors to identify one or more search results based on the interpretation of the combination of the first search term and the second search term when the score exceeds a threshold; and one or more instructions which, when executed by the one or more processors, cause the one or more processors to provide the one or more search results for display. | 15. A non-transitory computer-readable medium storing instructions, the instructions comprising: one or more instructions which, when executed by one or more processors, cause the one or more processors to receive a search query, the search query including a plurality of search terms; one or more instructions which, when executed by the one or more processors, cause the one or more processors to identify, based on a taxonomy, a hierarchical relationship between: a first search term of the plurality of search terms, and a second search term of the plurality of search terms, each of the first search term and the second search term being associated with a different level of the hierarchical relationship; one or more instructions which, when executed by the one or more processors, cause the one or more processors to generate an interpretation for a combination of the first search term and the second search term, the interpretation being generated based on the hierarchical relationship identified between the first search term and the second search term; one or more instructions which, when executed by the one or more processors, cause the one or more processors to determine a score for the interpretation of the combination of the first search term and the second search term; one or more instructions which, when executed by the one or more processors, cause the one or more processors to identify one or more search results based on the interpretation of the combination of the first search term and the second search term when the score exceeds a threshold; and one or more instructions which, when executed by the one or more processors, cause the one or more processors to provide the one or more search results for display. 17. The non-transitory computer-readable medium of claim 15 , where the one or more instructions to generate the interpretation include: one or more instructions to generate the interpretation based on a measure of importance of one of the first search term or the second search term with respect to another one of the first search term or the second search term. | 0.5 |
9,460,151 | 2 | 3 | 2. The system of claim 1 , wherein the executable instructions cause the processor to further perform the operations comprising: generate dictionary information that corresponds to a second user, the dictionary information that corresponds to the second user includes a second list of compatible query operators and a description of compatible data types that correspond to each operator in the second list of compatible query operators, wherein the dictionary information that corresponds to the second user is different from the dictionary information that corresponds to the first user. | 2. The system of claim 1 , wherein the executable instructions cause the processor to further perform the operations comprising: generate dictionary information that corresponds to a second user, the dictionary information that corresponds to the second user includes a second list of compatible query operators and a description of compatible data types that correspond to each operator in the second list of compatible query operators, wherein the dictionary information that corresponds to the second user is different from the dictionary information that corresponds to the first user. 3. The system of claim 2 , wherein the executable instructions cause the processor to further perform the operations comprising: receive, from the second user, a search query to search for document information in the database, wherein the search query from the second user is different than the search query from the first user. | 0.5 |
5,393,062 | 1 | 3 | 1. A method of solving word transformation puzzles by transforming a first word into a second word in the shortest possible sequence, the steps comprising: a) growing a first tree having a plurality of adjacent nodes with words disposed thereon, the root node of said first tree having said first word disposed thereon; b) generating one or more words for each of said nodes occurring in the topmost level of said first tree, each of said generated words having a predetermined relationship to the word from which it was generated; c) growing a second tree having a plurality of adjacent nodes with words disposed thereon, the root node of said second tree having said second word disposed thereon; d) generating one or more words for each of said nodes occurring in the topmost level of said second tree, each of said generated words having a predetermined relationship to the word from which it was generated; e) comparing at least one word of said first tree with at least one word of said second tree in order to identify a word common to both of said trees; f) identifying a sequence of words in each of said trees connecting the respective roots thereof to said common word; and g) combining said first and second sequences of words into a single sequence connecting the respective roots of said trees to one another via said common word. | 1. A method of solving word transformation puzzles by transforming a first word into a second word in the shortest possible sequence, the steps comprising: a) growing a first tree having a plurality of adjacent nodes with words disposed thereon, the root node of said first tree having said first word disposed thereon; b) generating one or more words for each of said nodes occurring in the topmost level of said first tree, each of said generated words having a predetermined relationship to the word from which it was generated; c) growing a second tree having a plurality of adjacent nodes with words disposed thereon, the root node of said second tree having said second word disposed thereon; d) generating one or more words for each of said nodes occurring in the topmost level of said second tree, each of said generated words having a predetermined relationship to the word from which it was generated; e) comparing at least one word of said first tree with at least one word of said second tree in order to identify a word common to both of said trees; f) identifying a sequence of words in each of said trees connecting the respective roots thereof to said common word; and g) combining said first and second sequences of words into a single sequence connecting the respective roots of said trees to one another via said common word. 3. The method of solving word transformation puzzles in accordance with claim 1, wherein said comparing step (e) is performed for each word in a given level of each of said trees prior to adding additional levels thereto, so that the number of words in the solution sequence is minimized. | 0.524752 |
9,430,531 | 1 | 14 | 1. A method comprising: receiving first activity information for a sender of a first link to at least one recipient collected by a collection resource at a Web site, wherein no personally identifiable information of the sender is collected in collecting the first activity information, and the personally identifiable information of the sender comprises an e-mail address of the sender; storing the first activity information at a storage server; receiving second activity information when a recipient accesses the first link sent by the sender corresponding to the first activity information stored at the storage server, wherein no personally identifiable information of the recipient collected in collecting the second activity information; using at least one processor, attempting to identify a first node representative of the sender in a social graph; when a first node representative of the sender in a social graph is not identified and after receiving the second activity information, creating a second node to represent the sender in the social graph; and based on at least information associated with the second node in the social graph, selecting a personalized digital content for delivery to the sender. | 1. A method comprising: receiving first activity information for a sender of a first link to at least one recipient collected by a collection resource at a Web site, wherein no personally identifiable information of the sender is collected in collecting the first activity information, and the personally identifiable information of the sender comprises an e-mail address of the sender; storing the first activity information at a storage server; receiving second activity information when a recipient accesses the first link sent by the sender corresponding to the first activity information stored at the storage server, wherein no personally identifiable information of the recipient collected in collecting the second activity information; using at least one processor, attempting to identify a first node representative of the sender in a social graph; when a first node representative of the sender in a social graph is not identified and after receiving the second activity information, creating a second node to represent the sender in the social graph; and based on at least information associated with the second node in the social graph, selecting a personalized digital content for delivery to the sender. 14. The method of claim 1 comprising: sending a bid in response to a bid request from a real-time bidding exchange, wherein the bid comprises the selected personalized digital content. | 0.816 |
8,626,585 | 12 | 15 | 12. A system, comprising: a data processing apparatus; a memory storage apparatus in data communication with the data processing apparatus and storing instructions executable by the data processing apparatus and that upon such execution cause the data processing apparatus to perform operations 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 the 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. | 12. A system, comprising: a data processing apparatus; a memory storage apparatus in data communication with the data processing apparatus and storing instructions executable by the data processing apparatus and that upon such execution cause the data processing apparatus to perform operations 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 the 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. 15. The system of claim 12 , wherein the operations further comprise, for each of the one or more advertisements: determining an advertising entity for the textual advertisement; identifying one or more entity images based on the advertising entity; and storing, in the data storage system, data associating the entity images with the textual advertisement. | 0.739416 |
7,783,488 | 1 | 8 | 1. A computer-implemented method comprising the steps of: receiving audio input speech signals; extracting acoustic information comprising recognition features from said speech signals using a first automatic speech recognition system; compressing said acoustic information; transmitting said compressed acoustic information to a remote site; decompressing said compressed acoustic information to obtain decompressed recognition features; inputting, at said remote site, the decompressed recognition features into a second automatic speech recognition system to obtain a recognition result; and based at least in part on the recognition result, adjusting said first automatic speech recognition system. | 1. A computer-implemented method comprising the steps of: receiving audio input speech signals; extracting acoustic information comprising recognition features from said speech signals using a first automatic speech recognition system; compressing said acoustic information; transmitting said compressed acoustic information to a remote site; decompressing said compressed acoustic information to obtain decompressed recognition features; inputting, at said remote site, the decompressed recognition features into a second automatic speech recognition system to obtain a recognition result; and based at least in part on the recognition result, adjusting said first automatic speech recognition system. 8. The method according to claim 1 , wherein adjusting said first automatic speech recognition system comprises accessing said first automatic speech recognition system from said remote site. | 0.779446 |
9,092,688 | 7 | 8 | 7. An assisted OCR system, comprising: a non-transitory storage medium to store computer program code; and a processor to execute the computer program code, the processor, when executing the computer program code, performing the following: receiving an image file of an image of a text document, the image of the text document including a plurality of glyphs; determining a position of each of the glyphs in the image of the text document; determining a spacing of the glyphs in the image of the text document; identifying word boundaries in the image of the text document from the spacing thereby implying an existence of a first plurality of words in the image of the text document, each one of the first plurality of words having a word length measured by the number of characters in the one word; preparing a first array of word lengths based on the word length of each of the first plurality of words, the first array being ordered according to the order in which the first plurality of words appear in the image of the text document; receiving a text file including a certain text, the text file including a second plurality of words and a plurality of characters, each of the second plurality of words having a word length; preparing a second array of word lengths based on the word length of each of the second plurality of words, the second array being ordered according to the order in which the second plurality of words appear in the text file; comparing at least part of the first array of word lengths to at least part of the second array of word lengths in order to find a best alignment between the first array of word lengths and the second array of word lengths; assigning at least some of the characters of the text file of the certain text to at least some of the glyphs of the image of the text document based on the best alignment; selecting a letter of an alphabet included in the characters of the text file; selecting some of the glyphs of the image of the text document that correspond to the selected letter of the alphabet based on the best alignment; comparing the selected glyphs with each other to provide a level of confidence in the best alignment; deriving a layout of at least part of the certain text as arranged in the image of the text document at least based on the position of each of the at least some glyphs in the image of the text document and assigning at least some of the characters of the text file of the certain text to at least some of the glyphs of the image of the text document according to the best alignment; and extracting a watermark embedded in the image of the text document. | 7. An assisted OCR system, comprising: a non-transitory storage medium to store computer program code; and a processor to execute the computer program code, the processor, when executing the computer program code, performing the following: receiving an image file of an image of a text document, the image of the text document including a plurality of glyphs; determining a position of each of the glyphs in the image of the text document; determining a spacing of the glyphs in the image of the text document; identifying word boundaries in the image of the text document from the spacing thereby implying an existence of a first plurality of words in the image of the text document, each one of the first plurality of words having a word length measured by the number of characters in the one word; preparing a first array of word lengths based on the word length of each of the first plurality of words, the first array being ordered according to the order in which the first plurality of words appear in the image of the text document; receiving a text file including a certain text, the text file including a second plurality of words and a plurality of characters, each of the second plurality of words having a word length; preparing a second array of word lengths based on the word length of each of the second plurality of words, the second array being ordered according to the order in which the second plurality of words appear in the text file; comparing at least part of the first array of word lengths to at least part of the second array of word lengths in order to find a best alignment between the first array of word lengths and the second array of word lengths; assigning at least some of the characters of the text file of the certain text to at least some of the glyphs of the image of the text document based on the best alignment; selecting a letter of an alphabet included in the characters of the text file; selecting some of the glyphs of the image of the text document that correspond to the selected letter of the alphabet based on the best alignment; comparing the selected glyphs with each other to provide a level of confidence in the best alignment; deriving a layout of at least part of the certain text as arranged in the image of the text document at least based on the position of each of the at least some glyphs in the image of the text document and assigning at least some of the characters of the text file of the certain text to at least some of the glyphs of the image of the text document according to the best alignment; and extracting a watermark embedded in the image of the text document. 8. The system according to claim 7 , wherein the comparing includes applying a longest common subsequence matching algorithm with the first array and the second array as input in order to find the best alignment. | 0.835404 |
9,678,637 | 1 | 3 | 1. A system comprising: an electronic data store configured to store content association information that associates a portion of each of a plurality of audio books with a content characteristic; and a computing device, comprising a physical processor and memory, that is in communication with the electronic data store, the computing device configured to: receive context information associated with a current context of a user, wherein the context information includes at least one of a current location of the user or a current activity of the user; determine a context attribute associated with the current context of the user based at least in part on the received context information; determine a content characteristic that is identified in stored context-to-characteristic association information as being associated with the context attribute, wherein the content characteristic is not the current location of the user and the content characteristic is not the current activity of the user; determine a recommended portion of an audio book, selected from among the plurality of audio books, to be consumed in the current context, wherein the recommended portion of the audio book is determined based at least in part on a determination that the content association information indicates that the content characteristic that is identified in the stored context-to-characteristic association information as being associated with the context attribute is also associated with the recommended portion of the audio book; and cause presentation of an option whose selection enables the recommended portion of the audio book to be audibly presented to the user. | 1. A system comprising: an electronic data store configured to store content association information that associates a portion of each of a plurality of audio books with a content characteristic; and a computing device, comprising a physical processor and memory, that is in communication with the electronic data store, the computing device configured to: receive context information associated with a current context of a user, wherein the context information includes at least one of a current location of the user or a current activity of the user; determine a context attribute associated with the current context of the user based at least in part on the received context information; determine a content characteristic that is identified in stored context-to-characteristic association information as being associated with the context attribute, wherein the content characteristic is not the current location of the user and the content characteristic is not the current activity of the user; determine a recommended portion of an audio book, selected from among the plurality of audio books, to be consumed in the current context, wherein the recommended portion of the audio book is determined based at least in part on a determination that the content association information indicates that the content characteristic that is identified in the stored context-to-characteristic association information as being associated with the context attribute is also associated with the recommended portion of the audio book; and cause presentation of an option whose selection enables the recommended portion of the audio book to be audibly presented to the user. 3. The system of claim 1 , wherein the context-to-characteristic association information comprises stored information that maps each of a plurality of context attributes with at least one content characteristic. | 0.642373 |
9,727,618 | 1 | 14 | 1. A computer-implemented method of identifying information of interest within an organization, wherein the organization includes a structured body of users with associated roles within the organization and who have access to information items within the organization, the method comprising: determining use data that characterizes relationships among the information items and relationships between the information items and users within the organization, wherein each information item is a document, a presentation, a video, an image, or a webpage, wherein a relationship between a first user and a first information item corresponds to activities performed by the first user on the first information item; wherein the activities include at least five of: querying, browsing, opening, editing, bookmarking, collecting, or curating the first information item; and, wherein the use data is determined in part by tracking which information items or portions of information items users interact with; generating interest data indicating affinity among the information items based on the determined use data, wherein generating the interest data includes identifying at least one set of two or more information items that are frequently viewed together, where each set of information items includes a first information item from the set of information items and a second, different information item from the set of information items; using the interest data to create a feed of information items ordered by relevance to a particular user; and providing the feed of information items to the particular user. | 1. A computer-implemented method of identifying information of interest within an organization, wherein the organization includes a structured body of users with associated roles within the organization and who have access to information items within the organization, the method comprising: determining use data that characterizes relationships among the information items and relationships between the information items and users within the organization, wherein each information item is a document, a presentation, a video, an image, or a webpage, wherein a relationship between a first user and a first information item corresponds to activities performed by the first user on the first information item; wherein the activities include at least five of: querying, browsing, opening, editing, bookmarking, collecting, or curating the first information item; and, wherein the use data is determined in part by tracking which information items or portions of information items users interact with; generating interest data indicating affinity among the information items based on the determined use data, wherein generating the interest data includes identifying at least one set of two or more information items that are frequently viewed together, where each set of information items includes a first information item from the set of information items and a second, different information item from the set of information items; using the interest data to create a feed of information items ordered by relevance to a particular user; and providing the feed of information items to the particular user. 14. The computer-implemented method of claim 1 , further comprising: determining an affinity between a first user and a first information item based on: an affinity between the first user and a second user and a relationship between the second user and the first information item, or an affinity between the first user and a collection to which the first information item belongs. | 0.510309 |
9,262,784 | 11 | 14 | 11. A computer-implemented system comprising a processor with a memory configured to: extract product descriptors from a product page; receive a result of a search for prices of the product based on the extracted product descriptors; generate, using the result of the search for prices of the product, a price comparison result for the product displayed in the product page; identify, using the price comparison result, a product with selected attributes; generate a buyer button, the buyer button including a direct link to the identified product with selected attributes; generate a browser toolbar and the product page contemporaneously in a client browser, wherein the browser toolbar includes a seller button, the buyer button, and the price comparison result for the product displayed in the product page; and generate, in response to operation of the seller button, a product listing on a marketplace, wherein generating the product listing includes determining a product category and a product description from the product descriptors extracted from the product page. | 11. A computer-implemented system comprising a processor with a memory configured to: extract product descriptors from a product page; receive a result of a search for prices of the product based on the extracted product descriptors; generate, using the result of the search for prices of the product, a price comparison result for the product displayed in the product page; identify, using the price comparison result, a product with selected attributes; generate a buyer button, the buyer button including a direct link to the identified product with selected attributes; generate a browser toolbar and the product page contemporaneously in a client browser, wherein the browser toolbar includes a seller button, the buyer button, and the price comparison result for the product displayed in the product page; and generate, in response to operation of the seller button, a product listing on a marketplace, wherein generating the product listing includes determining a product category and a product description from the product descriptors extracted from the product page. 14. The computer-implemented system of claim 11 , wherein the processor displaying the comparison of prices for the product displayed in the product page includes displaying a suggested price for the product. | 0.712707 |
8,359,275 | 1 | 2 | 1. An electronic-network based system for knowledge creation, said electronic-network based system comprising: at least one computer processor account subsystem, Said at least one computer processor account subsystem having a plurality of user accounts; at least one computer processor exchange subsystem; at least one computer processor governance subsystem for governing activities of said at least one computer processor exchange subsystem; said at least one computer processor governance subsystem being a system self-governed through said plurality of said user accounts; wherein said exchange subsystem is internetworked with said computer account system and said computer governance subsystem; and wherein said computer exchange subsystem is configured by said computer governance system to operate in accordance with said self-governing system to: receive through each of said plurality of user accounts, an election of at least one person responsible for said computer exchange subsystem; elect at least one person responsible for said computer exchange subsystem according to said received elections; receive first user's knowledge deposited through a first user account of said plurality of user accounts of said computer account subsystem; receive a second user's offer for purchasing a view of said knowledge deposit, said offer being sent through a second user account of said plurality of user accounts of said computer account subsystem; accept said second user's offer; and distribute said knowledge deposit view to said second user account of said plurality of user accounts of said computer account subsystem in exchange for receiving, from said second user's account, money revenue for purchases; further comprising a Dispute Resolution subsystem, internetworked with said computer exchange subsystem; and wherein said exchange subsystem is further configured to: log particulars of said second user's offer to purchase said view, said acceptance of said second user's offer; and said distribution of said purchased view to said second user account; log a receipt of said particulars in at least one of said first user account and said second user account; and wherein said dispute resolution subsystem is configured to: resolve a dispute between user accounts based on said logged particulars and logged receipt in response to receiving input from at least one of said first user account and said second user account whereby the ability to pay legal fees is equalized such that a user with greater financial resources cannot unjustly prevail over users with fewer financial resource. | 1. An electronic-network based system for knowledge creation, said electronic-network based system comprising: at least one computer processor account subsystem, Said at least one computer processor account subsystem having a plurality of user accounts; at least one computer processor exchange subsystem; at least one computer processor governance subsystem for governing activities of said at least one computer processor exchange subsystem; said at least one computer processor governance subsystem being a system self-governed through said plurality of said user accounts; wherein said exchange subsystem is internetworked with said computer account system and said computer governance subsystem; and wherein said computer exchange subsystem is configured by said computer governance system to operate in accordance with said self-governing system to: receive through each of said plurality of user accounts, an election of at least one person responsible for said computer exchange subsystem; elect at least one person responsible for said computer exchange subsystem according to said received elections; receive first user's knowledge deposited through a first user account of said plurality of user accounts of said computer account subsystem; receive a second user's offer for purchasing a view of said knowledge deposit, said offer being sent through a second user account of said plurality of user accounts of said computer account subsystem; accept said second user's offer; and distribute said knowledge deposit view to said second user account of said plurality of user accounts of said computer account subsystem in exchange for receiving, from said second user's account, money revenue for purchases; further comprising a Dispute Resolution subsystem, internetworked with said computer exchange subsystem; and wherein said exchange subsystem is further configured to: log particulars of said second user's offer to purchase said view, said acceptance of said second user's offer; and said distribution of said purchased view to said second user account; log a receipt of said particulars in at least one of said first user account and said second user account; and wherein said dispute resolution subsystem is configured to: resolve a dispute between user accounts based on said logged particulars and logged receipt in response to receiving input from at least one of said first user account and said second user account whereby the ability to pay legal fees is equalized such that a user with greater financial resources cannot unjustly prevail over users with fewer financial resource. 2. The system of claim 1 , wherein said exchange subsystem is further configured to control distribution of said purchased knowledge deposit view received in said second user's account on a distribution system according to a first user decision input received from said first user account. | 0.849007 |
8,005,806 | 1 | 7 | 1. A method executable by at least one computing system of retrieving information using context information comprising: storing, by at least one processor in at least one data store, context identified from a previous experience with an information item, the stored context comprising information and events associated with the information item, event relationships among the events and an event type of each event, the stored context relates the information item and at least one of the events that occurred during the previous experience with the information item; receiving, by the at least one processor, a request to search the stored context to identify the information item, the request comprising at least a portion of the stored context including the at least one event that occurred during the previous experience with the information item, the event type of the at least one event, and at least one of the event relationships; searching, by at least one processor, the stored context using the at least a portion of the stored context included in the search request to identify the information item. | 1. A method executable by at least one computing system of retrieving information using context information comprising: storing, by at least one processor in at least one data store, context identified from a previous experience with an information item, the stored context comprising information and events associated with the information item, event relationships among the events and an event type of each event, the stored context relates the information item and at least one of the events that occurred during the previous experience with the information item; receiving, by the at least one processor, a request to search the stored context to identify the information item, the request comprising at least a portion of the stored context including the at least one event that occurred during the previous experience with the information item, the event type of the at least one event, and at least one of the event relationships; searching, by at least one processor, the stored context using the at least a portion of the stored context included in the search request to identify the information item. 7. The method of claim 1 , wherein the information item is an electronic mail message. | 0.73125 |
8,645,991 | 9 | 10 | 9. The method of claim 6 , further comprising: logging a response of the second user to the information provided as a second signal. | 9. The method of claim 6 , further comprising: logging a response of the second user to the information provided as a second signal. 10. The method of claim 9 , further comprising: providing the second signal to at least one of: the first user or a provider of the at least one item of supplemental content. | 0.5 |
9,588,964 | 29 | 34 | 29. A method implemented at least partially in hardware of one or more computing devices, the method comprising: identifying, by the one or more computing devices, a word parsed from a natural language input that is not included in a vocabulary associated with an image editing operation domain; and disambiguating, by the one or more computing devices, the parsed word using the vocabulary to identify non-matching words to accomplish image editing operations, the disambiguating based on: semantic distance between the parsed word and a plurality of words included in the vocabulary, the semantic distance based at least in part on a distance matrix computed between the parsed word and one or more of the plurality of words included in the vocabulary, the distance matrix comprising semantic distances between terms for respective parts of speech; and similarity of lexical functional groups of the parsed word and the plurality of words. | 29. A method implemented at least partially in hardware of one or more computing devices, the method comprising: identifying, by the one or more computing devices, a word parsed from a natural language input that is not included in a vocabulary associated with an image editing operation domain; and disambiguating, by the one or more computing devices, the parsed word using the vocabulary to identify non-matching words to accomplish image editing operations, the disambiguating based on: semantic distance between the parsed word and a plurality of words included in the vocabulary, the semantic distance based at least in part on a distance matrix computed between the parsed word and one or more of the plurality of words included in the vocabulary, the distance matrix comprising semantic distances between terms for respective parts of speech; and similarity of lexical functional groups of the parsed word and the plurality of words. 34. A method as described in claim 29 , wherein the disambiguating includes filtering pairs of the parsed word and particular ones of the plurality of words in which a path that is usable to compute a semantic distance includes an ontology root. | 0.629909 |
8,639,937 | 1 | 2 | 1. A method for generating a password for a user during an enrollment phase, comprising: presenting said user with a plurality of topics; receiving a user selection of at least one topic; receiving one or more personal details from said user associated with said at least one selected topic as a proposed password; performing an Internet search using a query containing one or more keywords derived from said personal details of said proposed password, wherein said Internet search searches contents of the Internet across a plurality of web sites using a search engine tool; evaluating results of said search relative to one or more predefined thresholds applicable to said at least one selected topic; rejecting said proposed password when said user is correlated with said proposed password if one or more of said predefined thresholds are exceeded by said results; and recording said one or more personal details as a password for said user if said proposed password is not rejected. | 1. A method for generating a password for a user during an enrollment phase, comprising: presenting said user with a plurality of topics; receiving a user selection of at least one topic; receiving one or more personal details from said user associated with said at least one selected topic as a proposed password; performing an Internet search using a query containing one or more keywords derived from said personal details of said proposed password, wherein said Internet search searches contents of the Internet across a plurality of web sites using a search engine tool; evaluating results of said search relative to one or more predefined thresholds applicable to said at least one selected topic; rejecting said proposed password when said user is correlated with said proposed password if one or more of said predefined thresholds are exceeded by said results; and recording said one or more personal details as a password for said user if said proposed password is not rejected. 2. The method of claim 1 , further comprising the step of receiving a reminder associated with each of said one or more personal details. | 0.669082 |
8,954,837 | 9 | 15 | 9. A system for inserting delimiters into a formula, comprising: a processor configured to: successively receive a plurality of selections of cells while in a formula editing mode in a host cell into which a formula is being entered; automatically determine a current context of the formula with respect to which the selections are received; and automatically insert a first delimiter type between references to the cells inserted into the formula in response to receiving the plurality of selections when the current context comprises a first context and automatically insert a second delimiter type between references inserted into the formula in response to receiving the plurality of selections when the current context comprises a second context, wherein each first and second delimiter type spatially separates the references to the cells from each other within the formula by being inserted between the references to the cells; and a memory coupled to the processor and configured to provide instructions to the processor. | 9. A system for inserting delimiters into a formula, comprising: a processor configured to: successively receive a plurality of selections of cells while in a formula editing mode in a host cell into which a formula is being entered; automatically determine a current context of the formula with respect to which the selections are received; and automatically insert a first delimiter type between references to the cells inserted into the formula in response to receiving the plurality of selections when the current context comprises a first context and automatically insert a second delimiter type between references inserted into the formula in response to receiving the plurality of selections when the current context comprises a second context, wherein each first and second delimiter type spatially separates the references to the cells from each other within the formula by being inserted between the references to the cells; and a memory coupled to the processor and configured to provide instructions to the processor. 15. A system as recited in claim 9 , wherein the processor is further configured to provide options to specify one or more of the first delimiter type, the second delimiter type, the first context, and the second context. | 0.5 |
4,400,788 | 8 | 9 | 8. Apparatus for recognizing a speech pattern as a string of predetermined reference words according to claim 1 further characterized in that said time registering means comprises: means operative in each reference word time registration of the current level responsive to the reference word feature signal and the speech pattern segment feature signals for selecting a range of reference word frames for each speech pattern segment frame, and means operative at each speech pattern segment frame responsive to the reference word registration lower limit frame being equal to or exceeding the reference word ending frame for terminating the time registration of said reference word. | 8. Apparatus for recognizing a speech pattern as a string of predetermined reference words according to claim 1 further characterized in that said time registering means comprises: means operative in each reference word time registration of the current level responsive to the reference word feature signal and the speech pattern segment feature signals for selecting a range of reference word frames for each speech pattern segment frame, and means operative at each speech pattern segment frame responsive to the reference word registration lower limit frame being equal to or exceeding the reference word ending frame for terminating the time registration of said reference word. 9. Apparatus for recognizing a speech pattern as a string of predetermined reference words according to claim 8 further characterized in that said time registering means comprises: means operative in each level reference word time registration responsive to the reference word feature signals and the level speech pattern segment feature signals for generating a time registration correspondence signal for each level speech pattern segment frame, means responsive to the level speech pattern segment frame for generating a maximum allowable correspondence signal for said speech pattern segment frame and means responsive to said time registration correspondence signal of a speech pattern segment frame exceeding the maximum allowable correspondence signal for said speech pattern segment frame for terminating the time registration of said level reference word. | 0.5 |
8,666,727 | 30 | 31 | 30. The method of claim 24 , where estimating the natural language includes utilizing a confidence based approach including determining a confidence value for each estimated language, the confidence value being a measure of assuredness that the estimated language of the data entry is the correct language. | 30. The method of claim 24 , where estimating the natural language includes utilizing a confidence based approach including determining a confidence value for each estimated language, the confidence value being a measure of assuredness that the estimated language of the data entry is the correct language. 31. The method of claim 30 , where the natural language of the data entry is estimated based on the determined confidence value. | 0.5 |
7,684,975 | 2 | 6 | 2. The method of claim 1 , wherein a master dictionary is referenced when decomposing the text string into tokens. | 2. The method of claim 1 , wherein a master dictionary is referenced when decomposing the text string into tokens. 6. The method of claim 2 , wherein whether a token is decomposable is determined by determining whether a decomposable flag for the token in the master dictionary is set. | 0.5 |
9,081,774 | 1 | 2 | 1. A method of identifying web pages of a world wide web having relevance to a first file, comprising: identifying a plurality of web pages within the world wide web, wherein the plurality of web pages each have a relationship with the first file, wherein the world wide web provides a platform for sharing web pages, and wherein each web page includes a document or information resource that is suitable for the world wide web and is accessible through a web browser; generating, by a system server, a list of inquiries based on the plurality of web pages; providing, by the system server, the list of inquiries to at least one author of the first file; receiving from the at least one author at least one response to the list of inquiries; selecting a subset of the plurality of web pages based on the at least one response; storing information related to the selected subset of the plurality of web pages for access if the first file is selected; providing, by the system server, the selected subset of the plurality of web pages to a user who has performed a search on a search term that yields a plurality of results containing the first file; and identifying the at least one author to the user. | 1. A method of identifying web pages of a world wide web having relevance to a first file, comprising: identifying a plurality of web pages within the world wide web, wherein the plurality of web pages each have a relationship with the first file, wherein the world wide web provides a platform for sharing web pages, and wherein each web page includes a document or information resource that is suitable for the world wide web and is accessible through a web browser; generating, by a system server, a list of inquiries based on the plurality of web pages; providing, by the system server, the list of inquiries to at least one author of the first file; receiving from the at least one author at least one response to the list of inquiries; selecting a subset of the plurality of web pages based on the at least one response; storing information related to the selected subset of the plurality of web pages for access if the first file is selected; providing, by the system server, the selected subset of the plurality of web pages to a user who has performed a search on a search term that yields a plurality of results containing the first file; and identifying the at least one author to the user. 2. The method of claim 1 , further comprising: generating, by the system server, a second list of inquiries based on the plurality of web pages; providing, by the system server, the second list of inquiries to at least one second author of the plurality of web pages; receiving from the at least one second author of the plurality of web pages at least one second response to the second list of inquiries; re-selecting the subset of the plurality of web pages based on the at least one response and the at least one second response; and storing information related to the re-selected subset of the plurality of web pages for access if the first file is selected. | 0.5 |
7,533,034 | 1 | 4 | 1. A computer implemented method for providing through a computer network to business management a plan for implementing a user's suggestion for business improvement, the method comprising: in a first computer process, causing presentation to a user seeking to submit a suggestion for business improvement, a series of two or more templates for entering a structured response on a terminal device, wherein one of the templates presented to the user allows the user to characterize the type of suggestion as falling into at least one of a plurality of categories selected from a group of cost saving, revenue generation, quality improvement, safety improvement, customer service improvement, development of a new product, policy change and advertising or corporate slogan; receiving over a computer network the structured response, entered into the two or more templates from the user, wherein the structured response includes a characterization of the type of suggestion entered into one or more templates by the user and a server logically selects at least one of the templates presented to the user according to the type of suggestion characterized by the user; and in a second computer process, determining the network routing of data from the structured response to business management based upon entries of the response in one or more templates. | 1. A computer implemented method for providing through a computer network to business management a plan for implementing a user's suggestion for business improvement, the method comprising: in a first computer process, causing presentation to a user seeking to submit a suggestion for business improvement, a series of two or more templates for entering a structured response on a terminal device, wherein one of the templates presented to the user allows the user to characterize the type of suggestion as falling into at least one of a plurality of categories selected from a group of cost saving, revenue generation, quality improvement, safety improvement, customer service improvement, development of a new product, policy change and advertising or corporate slogan; receiving over a computer network the structured response, entered into the two or more templates from the user, wherein the structured response includes a characterization of the type of suggestion entered into one or more templates by the user and a server logically selects at least one of the templates presented to the user according to the type of suggestion characterized by the user; and in a second computer process, determining the network routing of data from the structured response to business management based upon entries of the response in one or more templates. 4. The method according to claim 1 , wherein at least one template provides for access to a database containing cost information. | 0.763736 |
9,232,059 | 9 | 10 | 9. The apparatus of claim 8 , comprising a call processing unit configured to call the user. | 9. The apparatus of claim 8 , comprising a call processing unit configured to call the user. 10. The apparatus of claim 9 , wherein the call processing device is configured to call at least one of the user's devices including a user landline phone, mobile phone and smartphone. | 0.5 |
8,417,948 | 7 | 9 | 7. The scripting engine of claim 1 wherein the carrier script is scripted in a first scripting language and the hidden script is scripted in a second scripting language that is different from the first scripting language. | 7. The scripting engine of claim 1 wherein the carrier script is scripted in a first scripting language and the hidden script is scripted in a second scripting language that is different from the first scripting language. 9. The scripting engine of claim 7 wherein the second scripting language is obfuscated. | 0.814103 |
7,698,080 | 1 | 22 | 1. A method, comprising: measuring spectral information for a sample with a measurement system and determining, based on the measured spectral information, probabilities that the sample corresponds to each of a plurality of candidates in a library of reference information; determining, based on the probabilities, whether sample identity information can be obtained by comparing the measured spectral information to the reference information; when the sample identity information cannot be obtained, adjusting a characteristic of the measurement system to increase a magnitude of one of the probabilities relative to the other probabilities, and repeating the steps of measuring spectral information, determining the probabilities, and determining whether the sample identity information can be obtained, until the sample identity information can be obtained; and using an electronic processor to compare the measured spectral information to the reference information to determine the sample identity information. | 1. A method, comprising: measuring spectral information for a sample with a measurement system and determining, based on the measured spectral information, probabilities that the sample corresponds to each of a plurality of candidates in a library of reference information; determining, based on the probabilities, whether sample identity information can be obtained by comparing the measured spectral information to the reference information; when the sample identity information cannot be obtained, adjusting a characteristic of the measurement system to increase a magnitude of one of the probabilities relative to the other probabilities, and repeating the steps of measuring spectral information, determining the probabilities, and determining whether the sample identity information can be obtained, until the sample identity information can be obtained; and using an electronic processor to compare the measured spectral information to the reference information to determine the sample identity information. 22. The method of claim 1 , wherein adjusting the characteristic of the measurement system comprises adjusting the measurement system to increase an intensity of Raman scattered light emitted by the sample. | 0.815412 |
6,161,093 | 3 | 4 | 3. An information access system according to claim 1 wherein said terminal further includes recording means for recording the phonetic signal information on a recording medium. | 3. An information access system according to claim 1 wherein said terminal further includes recording means for recording the phonetic signal information on a recording medium. 4. An information access system according to claim 3 wherein said terminal further includes playback means for playing back the phonetic signal information recorded on the recording medium. | 0.522727 |
8,560,938 | 16 | 17 | 16. A system for customizing a software application, the system comprising: a repository configured to store a base metadata document and a plurality of customization documents, wherein the base metadata document defines one or more characteristics of at least a portion of the software application, wherein the plurality of customization documents define modifications to the base metadata document, and wherein the plurality of customization documents are stored separately from the base metadata document; and a processor configured to: receive the base metadata document; identify the plurality of customization documents by: determining a plurality of customization levels associated with the base metadata document, each of the plurality of customization levels representing a scope for which the base metadata document can be customized, the plurality of customization levels being determined by accessing a configuration file comprising mappings between customization levels and base metadata documents, wherein the plurality of customization levels are sorted in a precedence order; and identifying a customization document for each customization level in the plurality of customization levels, wherein the customization document is identified based on one or more runtime attributes corresponding to the customization level; and generate a customized metadata document by applying the plurality of customization documents to the base metadata document in the precedence order. | 16. A system for customizing a software application, the system comprising: a repository configured to store a base metadata document and a plurality of customization documents, wherein the base metadata document defines one or more characteristics of at least a portion of the software application, wherein the plurality of customization documents define modifications to the base metadata document, and wherein the plurality of customization documents are stored separately from the base metadata document; and a processor configured to: receive the base metadata document; identify the plurality of customization documents by: determining a plurality of customization levels associated with the base metadata document, each of the plurality of customization levels representing a scope for which the base metadata document can be customized, the plurality of customization levels being determined by accessing a configuration file comprising mappings between customization levels and base metadata documents, wherein the plurality of customization levels are sorted in a precedence order; and identifying a customization document for each customization level in the plurality of customization levels, wherein the customization document is identified based on one or more runtime attributes corresponding to the customization level; and generate a customized metadata document by applying the plurality of customization documents to the base metadata document in the precedence order. 17. The system of claim 16 , wherein the processor is configured to perform the steps of receiving, identifying, and generating at runtime of the software application. | 0.5 |
8,515,750 | 14 | 19 | 14. A system comprising: one or more computers and one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising: receiving a transcription of a first portion of a speech session, wherein the transcription of the first portion of the speech session is generated using a speaker adaptation profile; receiving a stability measure for a segment of the transcription; determining that the stability measure for the segment satisfies a threshold; in response to determining that the stability measure for the segment satisfies the threshold, triggering a real-time update of the speaker adaptation profile using the segment, or using a portion of speech data that corresponds to the segment; receiving a transcription of a second portion of the speech session, wherein the transcription of the second portion of the speech session is generated using the updated speaker adaptation profile; and outputting a set of transcriptions comprising the transcription of the first portion of the speech session and the transcription of the second portion of the speech session. | 14. A system comprising: one or more computers and one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising: receiving a transcription of a first portion of a speech session, wherein the transcription of the first portion of the speech session is generated using a speaker adaptation profile; receiving a stability measure for a segment of the transcription; determining that the stability measure for the segment satisfies a threshold; in response to determining that the stability measure for the segment satisfies the threshold, triggering a real-time update of the speaker adaptation profile using the segment, or using a portion of speech data that corresponds to the segment; receiving a transcription of a second portion of the speech session, wherein the transcription of the second portion of the speech session is generated using the updated speaker adaptation profile; and outputting a set of transcriptions comprising the transcription of the first portion of the speech session and the transcription of the second portion of the speech session. 19. The system of claim 14 , wherein the speech session is one utterance. | 0.742958 |
7,869,578 | 1 | 2 | 1. A printer circuit comprising: a speech recognizer comprising: a first input that receives a remotely generated voice message; a second input that receives speech patterns and vocabulary words from a speech bank; logic for comparing the remotely generated voice message to the speech patterns and vocabulary words from the speech bank and translating the remotely generated voice message into text data, wherein the speech recognizer is operable to have its operation corrected based on corrective input from a user; and printing logic that causes the text data to be printed. | 1. A printer circuit comprising: a speech recognizer comprising: a first input that receives a remotely generated voice message; a second input that receives speech patterns and vocabulary words from a speech bank; logic for comparing the remotely generated voice message to the speech patterns and vocabulary words from the speech bank and translating the remotely generated voice message into text data, wherein the speech recognizer is operable to have its operation corrected based on corrective input from a user; and printing logic that causes the text data to be printed. 2. The printer circuit as in claim 1 , wherein the remotely generated voice message comprises digital data. | 0.692529 |
9,191,476 | 1 | 9 | 1. A method, comprising: sending, via an interface, from an agent to a caller, a request for authentication information for the caller; receiving, in response to the request for authentication information, a plurality of utterances from the caller, the plurality of utterances including a plurality of spoken words; performing, by at least one processor, speech recognition on the plurality of spoken words to generate text representing the utterances; identifying, by the at least one processor, a context of the utterances, using the text, wherein the context including a particular pattern of the utterances and a particular grammar used in the utterances; determining, by the at least one processor, a problem and location information associated with the caller using the identified context; in response to determining that the caller has not provided expected authentication information in the identified context, determining, by at least one processor, whether a solution to the problem is available based on the location information; when it is determined that the solution to the problem is available, providing, by the at least one processor, the solution to the caller, via the interface, without authenticating the caller; when it is determined that the solution to the problem is not available, requesting, via the interface, additional authentication information from the caller; and verifying, by the at least processor, text entered by the agent matches the recognized spoken words; and in response to detecting a mismatch, alerting the agent, via agent interface, that the mismatch has been detected. | 1. A method, comprising: sending, via an interface, from an agent to a caller, a request for authentication information for the caller; receiving, in response to the request for authentication information, a plurality of utterances from the caller, the plurality of utterances including a plurality of spoken words; performing, by at least one processor, speech recognition on the plurality of spoken words to generate text representing the utterances; identifying, by the at least one processor, a context of the utterances, using the text, wherein the context including a particular pattern of the utterances and a particular grammar used in the utterances; determining, by the at least one processor, a problem and location information associated with the caller using the identified context; in response to determining that the caller has not provided expected authentication information in the identified context, determining, by at least one processor, whether a solution to the problem is available based on the location information; when it is determined that the solution to the problem is available, providing, by the at least one processor, the solution to the caller, via the interface, without authenticating the caller; when it is determined that the solution to the problem is not available, requesting, via the interface, additional authentication information from the caller; and verifying, by the at least processor, text entered by the agent matches the recognized spoken words; and in response to detecting a mismatch, alerting the agent, via agent interface, that the mismatch has been detected. 9. The method of claim 1 , and further comprising identifying the caller, based on the speech recognition. | 0.807273 |
8,280,823 | 114 | 121 | 114. The system of claim 110 , wherein the search criteria comprises a job description that includes at least one job requirement, each said at least one job requirement including a required skill or experience-related phrase and a required term of experience. | 114. The system of claim 110 , wherein the search criteria comprises a job description that includes at least one job requirement, each said at least one job requirement including a required skill or experience-related phrase and a required term of experience. 121. The system of claim 114 , wherein to satisfy the search criteria, the parsed resume associated with each said at least one matching resume includes, for each said at least one job requirement, either the required skill or experience-related phrase, or an alternative required skill or experience-related phrase, and wherein the term of experience for either the required skill or experience-related phrase, or the alternative required skill or experience-related phrase, is greater than or equal to the required term of experience. | 0.534722 |
7,689,540 | 12 | 13 | 12. The system of claim 11 wherein the operations further comprise: accessing at least one second query reformulation path; comparing the query reformulation path with the at least one second query reformulation path; recognizing a pattern common to the query reformulation path and the at least one second query reformulation path; and generating a query reformulation pattern based on the recognized pattern. | 12. The system of claim 11 wherein the operations further comprise: accessing at least one second query reformulation path; comparing the query reformulation path with the at least one second query reformulation path; recognizing a pattern common to the query reformulation path and the at least one second query reformulation path; and generating a query reformulation pattern based on the recognized pattern. 13. The system of claim 12 wherein generating a query reformulation pattern includes generating a query reformulation pattern in which at least a portion of the query reformulation pattern is related to higher level semantics. | 0.5 |
8,285,714 | 1 | 2 | 1. An apparatus for providing related words for a query, comprising: a communication module connected to an external client through a network to receive an input query from the client; a relational database storing data including at least one first word, at least one second word co-occurring with the at least one first word, and a co-occurrence frequency, wherein the co-occurrence frequency indicates how many times the at least one second word occurs in relation to the at least one first word; and a related word control module extracting first words included in source data by searching the source data, extracting and storing second words co-occurring by the extracted first words and the co-occurrence frequency in the relational database, wherein the related word control module is configured to search for third words co-occurring by at least one of the second words, and to determine that the at least one second word is related to at least one of the first words if the third words include the at least one of the first words, and wherein the related word control module is configured to extract the query input through the communication module and related words from the relational database, wherein at least one of the communication module, the relational database, and the related word control module comprises a processor, wherein the related word control module comprises an advanced extraction module reading the co-occurrence words by words from the relational database, extracting related words related to the word among the co-occurrence words, and storing the extracted related words in the relational database, wherein the advanced extraction module reads the co-occurrence words by specified words from the relational database, extracts N upper co-occurrence words by the specified words in the order of the co-occurrence frequency, extracts second co-occurrence words with respect to the N co-occurrence words when the co-occurrence words occur, and judges the co-occurrence word for the specified word as being a related word if the specified word among the second co-occurrence words is within the order predetermined by the co-occurrence frequency order. | 1. An apparatus for providing related words for a query, comprising: a communication module connected to an external client through a network to receive an input query from the client; a relational database storing data including at least one first word, at least one second word co-occurring with the at least one first word, and a co-occurrence frequency, wherein the co-occurrence frequency indicates how many times the at least one second word occurs in relation to the at least one first word; and a related word control module extracting first words included in source data by searching the source data, extracting and storing second words co-occurring by the extracted first words and the co-occurrence frequency in the relational database, wherein the related word control module is configured to search for third words co-occurring by at least one of the second words, and to determine that the at least one second word is related to at least one of the first words if the third words include the at least one of the first words, and wherein the related word control module is configured to extract the query input through the communication module and related words from the relational database, wherein at least one of the communication module, the relational database, and the related word control module comprises a processor, wherein the related word control module comprises an advanced extraction module reading the co-occurrence words by words from the relational database, extracting related words related to the word among the co-occurrence words, and storing the extracted related words in the relational database, wherein the advanced extraction module reads the co-occurrence words by specified words from the relational database, extracts N upper co-occurrence words by the specified words in the order of the co-occurrence frequency, extracts second co-occurrence words with respect to the N co-occurrence words when the co-occurrence words occur, and judges the co-occurrence word for the specified word as being a related word if the specified word among the second co-occurrence words is within the order predetermined by the co-occurrence frequency order. 2. The apparatus as claimed in claim 1 , wherein the related word control module comprises: an occurrence frequency examination module extracting the words included in the source data by searching the source data, extracting and storing the co-occurrence words co-occurring by the extracted words and the co-occurrence frequency in the relational database; and an extraction module extracting the related words related to the input query from the relational database. | 0.5 |
8,812,296 | 27 | 30 | 27. A system for capturing data from a document image, the system comprising: a processor; and a memory coupled to the processor and in electronic communication with the imaging component, the memory configured with instructions for causing the processor to: identify a word token in a text corpus; apply by the computer system one or more paradigm rules to the word token; generate by the computer system one or more hypotheses about a part of speech for a base form of the word token; search by the computer system for one or more word inflected forms corresponding to the base form of the word token; verify by the computer system a hypothesis of the one or more hypotheses for the base form of the word token; add by the computer system at least one grammatical value and at least one inflection paradigm to the base form of the word token based at least in part on the verified hypothesis; obtain by the computer system one or more morphological descriptions for the word token based at least in part on the verified hypothesis; and add the base form of the word token with the one or more morphological descriptions to the morphological dictionary. | 27. A system for capturing data from a document image, the system comprising: a processor; and a memory coupled to the processor and in electronic communication with the imaging component, the memory configured with instructions for causing the processor to: identify a word token in a text corpus; apply by the computer system one or more paradigm rules to the word token; generate by the computer system one or more hypotheses about a part of speech for a base form of the word token; search by the computer system for one or more word inflected forms corresponding to the base form of the word token; verify by the computer system a hypothesis of the one or more hypotheses for the base form of the word token; add by the computer system at least one grammatical value and at least one inflection paradigm to the base form of the word token based at least in part on the verified hypothesis; obtain by the computer system one or more morphological descriptions for the word token based at least in part on the verified hypothesis; and add the base form of the word token with the one or more morphological descriptions to the morphological dictionary. 30. The system of claim 27 , wherein the one or more morphological descriptions comprise one or more word formation rules. | 0.573427 |
9,129,303 | 1 | 3 | 1. A method of sharing locations of users participating in a social networking service at a geographic location and communicating app related information of users participating in the social networking service, the method executed by a computer system and comprising: receiving location information and text descriptive information from a mobile device of a first user of the social networking service, the location information representing a geographic location of the first user, the text descriptive information manually provided by the first user on an input module of the mobile device; associating the location information with the text descriptive information of the first user in a database; sending the text descriptive information and the location information of the first user to a second user for display; operating at least one social network application server for interacting with users of the social network application service, wherein at least some of the users of the social network application service are users of wireless computing devices; providing a first mobile application for interacting with the social network application service via communication with the at least one social network application server, the first mobile application providing social network application operations independent of operations of a separate browser application, wherein (i) the first mobile application is further operable to employ geolocation functions of a respective wireless device to communicate geolocation information to one or more servers of hardware and software of the social network application, (ii) the first mobile application is programmed to upload photos to a respective user account with text descriptive information manually entered by the respective user for posting on a webpage of the social network application for the respective user, and (iii) at least some entries of text descriptive information communicated from the first mobile application and received by the one or more servers of the social network application are indicative of current activities of respective users; logging activities of users of the social network application using at least information received from the first mobile application; receiving app usage information, by one or more servers of hardware and software, from a plurality of second mobile applications of different types executing on respective wireless computing devices that is generated independently of user initiated web browsing operations, wherein (i) each of the plurality of second mobile applications includes code for installation on respective wireless computing devices for application operations on respective wireless computing devices, (ii) the plurality of second mobile applications include at least mobile gaming applications that include code for conducting gaming operations without employing a separate browser application on the respective wireless computing device for gaming operations, (iii) the plurality of second mobile applications include mobile digital content applications for accessing digital content from a respective library of digital content without employing a separate browser application on the respective wireless computing device for digital content presentation operations, (iv) the plurality of second mobile application include shopping-related mobile applications for completing shopping operations without employing a separate browser application on the respective wireless computing device for shopping operations, and (v) the second plurality of mobile applications are functionally integrated with the social network application service to share social network user activities and user activities of the second plurality of applications; combining app usage information from the second plurality of mobile applications with social network application information, wherein the combining comprises correlating non-social network application activities to respective identities in the social network application service and wherein the app usage information from the plurality of second mobile applications includes app-specific postings that differ depending on a respective mobile application or mobile application type; presenting combined activity listings to viewing users in one or more respective webpages by one or more web servers; and providing centralized app specific advertising, by one or more servers of hardware and software, for the plurality of second mobile applications, wherein the centralized app specific advertising includes providing rankings of apps including an analysis of app popularity in relation to app usage across an aggregate population of users of the plurality of second mobile applications and wherein the ranking of apps includes determining app usage information within the aggregate population relative to different demographic parameters. | 1. A method of sharing locations of users participating in a social networking service at a geographic location and communicating app related information of users participating in the social networking service, the method executed by a computer system and comprising: receiving location information and text descriptive information from a mobile device of a first user of the social networking service, the location information representing a geographic location of the first user, the text descriptive information manually provided by the first user on an input module of the mobile device; associating the location information with the text descriptive information of the first user in a database; sending the text descriptive information and the location information of the first user to a second user for display; operating at least one social network application server for interacting with users of the social network application service, wherein at least some of the users of the social network application service are users of wireless computing devices; providing a first mobile application for interacting with the social network application service via communication with the at least one social network application server, the first mobile application providing social network application operations independent of operations of a separate browser application, wherein (i) the first mobile application is further operable to employ geolocation functions of a respective wireless device to communicate geolocation information to one or more servers of hardware and software of the social network application, (ii) the first mobile application is programmed to upload photos to a respective user account with text descriptive information manually entered by the respective user for posting on a webpage of the social network application for the respective user, and (iii) at least some entries of text descriptive information communicated from the first mobile application and received by the one or more servers of the social network application are indicative of current activities of respective users; logging activities of users of the social network application using at least information received from the first mobile application; receiving app usage information, by one or more servers of hardware and software, from a plurality of second mobile applications of different types executing on respective wireless computing devices that is generated independently of user initiated web browsing operations, wherein (i) each of the plurality of second mobile applications includes code for installation on respective wireless computing devices for application operations on respective wireless computing devices, (ii) the plurality of second mobile applications include at least mobile gaming applications that include code for conducting gaming operations without employing a separate browser application on the respective wireless computing device for gaming operations, (iii) the plurality of second mobile applications include mobile digital content applications for accessing digital content from a respective library of digital content without employing a separate browser application on the respective wireless computing device for digital content presentation operations, (iv) the plurality of second mobile application include shopping-related mobile applications for completing shopping operations without employing a separate browser application on the respective wireless computing device for shopping operations, and (v) the second plurality of mobile applications are functionally integrated with the social network application service to share social network user activities and user activities of the second plurality of applications; combining app usage information from the second plurality of mobile applications with social network application information, wherein the combining comprises correlating non-social network application activities to respective identities in the social network application service and wherein the app usage information from the plurality of second mobile applications includes app-specific postings that differ depending on a respective mobile application or mobile application type; presenting combined activity listings to viewing users in one or more respective webpages by one or more web servers; and providing centralized app specific advertising, by one or more servers of hardware and software, for the plurality of second mobile applications, wherein the centralized app specific advertising includes providing rankings of apps including an analysis of app popularity in relation to app usage across an aggregate population of users of the plurality of second mobile applications and wherein the ranking of apps includes determining app usage information within the aggregate population relative to different demographic parameters. 3. The method of claim 1 wherein ads from the communicating are selected on a user-location dependent manner. | 0.736715 |
8,170,881 | 5 | 6 | 5. The computer-readable storage device of claim 4 , wherein the method of call processing further comprises: receiving said parsed VXML data; and providing said parsed VXML data to said associated service processor. | 5. The computer-readable storage device of claim 4 , wherein the method of call processing further comprises: receiving said parsed VXML data; and providing said parsed VXML data to said associated service processor. 6. The computer-readable storage device of claim 5 , wherein the method of call processing further comprises: executing said parsed VXML data to implement said telephony service. | 0.5 |
9,904,673 | 1 | 4 | 1. A machine-implemented method for assisting the authoring of electronic messages, comprising: invoking machine-implemented electronic messaging logic, said electronic messaging logic including user-interface object logic operable to display a user-interface object and invoke machine-implemented conversation advisor logic in response to user activation of said user-interface logic; initiating the creation of an electronic message using said electronic messaging logic, said electronic message being stored in digital form in a computer memory; invoking said conversation advisor logic in response to activation of said user-interface logic by an author of said electronic message; said conversation advisor logic accessing said electronic message in said computer memory; said conversation advisor logic inspecting one or more fields of said electronic message to identify intended recipients of said electronic message; said conversation advisor logic gathering and analyzing historical data relating to a conversation history in one or more previous electronic messages that link said author of said electronic message to said intended recipients, said gathering and analyzing of historical data including extracting and storing message content from said one or more previous electronic messages that is indicative of historical semantic styles and guidelines have been used in the past by said author to converse with said intended recipients via one or more electronic message applications; said conversation advisor logic sorting, tagging and storing said message content in a computer database as a sorted/tagged dataset that represents said historical data, said historical data being arranged in individual database entries that are each specific to a particular one of said intended recipients or to said intended recipients as a group; said conversation advisor logic being operable to populate some or all of said sorted/tagged dataset with data entries containing said historical data in advance of said electronic message being created by periodically searching for new electronic messages created by said electronic messaging logic and extracting said message content therefrom; said conversation advisor logic being operable to supplement said sorted/tagged dataset with one or more additional database entries during creation of said electronic message to account for any of said intended recipients who are not represented by existing database entries in said sorted/tagged dataset; said conversation advisor logic performing semantic analysis on said electronic message to extract words and phrases representing recipient fitness information that is indicative of whether said electronic message is appropriate for said intended recipients by virtue of being consistent with said historical data; said conversation advisor logic generating a fitness result for said electronic message by comparing said recipient fitness information to said historical data and identifying inconsistencies between said words and phrases represented by said recipient fitness information and said historical semantic styles and guidelines represented by said historical data; and said conversation advisor logic outputting said fitness result for viewing on an electronic display device associated with said author of said electronic message. | 1. A machine-implemented method for assisting the authoring of electronic messages, comprising: invoking machine-implemented electronic messaging logic, said electronic messaging logic including user-interface object logic operable to display a user-interface object and invoke machine-implemented conversation advisor logic in response to user activation of said user-interface logic; initiating the creation of an electronic message using said electronic messaging logic, said electronic message being stored in digital form in a computer memory; invoking said conversation advisor logic in response to activation of said user-interface logic by an author of said electronic message; said conversation advisor logic accessing said electronic message in said computer memory; said conversation advisor logic inspecting one or more fields of said electronic message to identify intended recipients of said electronic message; said conversation advisor logic gathering and analyzing historical data relating to a conversation history in one or more previous electronic messages that link said author of said electronic message to said intended recipients, said gathering and analyzing of historical data including extracting and storing message content from said one or more previous electronic messages that is indicative of historical semantic styles and guidelines have been used in the past by said author to converse with said intended recipients via one or more electronic message applications; said conversation advisor logic sorting, tagging and storing said message content in a computer database as a sorted/tagged dataset that represents said historical data, said historical data being arranged in individual database entries that are each specific to a particular one of said intended recipients or to said intended recipients as a group; said conversation advisor logic being operable to populate some or all of said sorted/tagged dataset with data entries containing said historical data in advance of said electronic message being created by periodically searching for new electronic messages created by said electronic messaging logic and extracting said message content therefrom; said conversation advisor logic being operable to supplement said sorted/tagged dataset with one or more additional database entries during creation of said electronic message to account for any of said intended recipients who are not represented by existing database entries in said sorted/tagged dataset; said conversation advisor logic performing semantic analysis on said electronic message to extract words and phrases representing recipient fitness information that is indicative of whether said electronic message is appropriate for said intended recipients by virtue of being consistent with said historical data; said conversation advisor logic generating a fitness result for said electronic message by comparing said recipient fitness information to said historical data and identifying inconsistencies between said words and phrases represented by said recipient fitness information and said historical semantic styles and guidelines represented by said historical data; and said conversation advisor logic outputting said fitness result for viewing on an electronic display device associated with said author of said electronic message. 4. The method of claim 1 , wherein said recipient fitness information comprises words or phrases representing proper names, nicknames and genders associated with said intended recipients. | 0.791759 |
6,134,532 | 50 | 54 | 50. A method of selecting advertisements in a computer environment, comprising: providing a database of electronic advertisements; converting an observed behavior of a user computing device in the computer environment to a behavior vector, modifying a profile vector indicative of the user with the behavior vector; comparing the modified profile vector to a plurality of entity vectors, the entity vectors indicative of the electronic advertisements, so as to identify at least one entity vector closely associated with the observed behavior; accessing the electronic database with the identified entity vector; and selecting at least one electronic advertisement to communicate to the user computing device. | 50. A method of selecting advertisements in a computer environment, comprising: providing a database of electronic advertisements; converting an observed behavior of a user computing device in the computer environment to a behavior vector, modifying a profile vector indicative of the user with the behavior vector; comparing the modified profile vector to a plurality of entity vectors, the entity vectors indicative of the electronic advertisements, so as to identify at least one entity vector closely associated with the observed behavior; accessing the electronic database with the identified entity vector; and selecting at least one electronic advertisement to communicate to the user computing device. 54. The method as defined in claim 50, wherein the electronic advertisement is communicated to the user computing device via a network, the network selected from the group consisting of an intranet, a local area network, and the Internet. | 0.814353 |
8,396,709 | 1 | 18 | 1. A computer-implemented method, comprising: accessing audio data that includes encoded speech; accessing information that indicates a docking context of a client device, the docking context being associated with the audio data; identifying a plurality of language models; identifying multiple sets of weighting values for the plurality of language models, the multiple sets of weighting values comprising at least a first set of multiple weighting values that correspond to multiple language models of the plurality of language models, the first set of multiple weighting values being associated with a first key phrase, wherein the first set of multiple weighting values is used to bias selection of a language model when a user utters the first key phrase, and a second set of multiple weighting values that correspond to multiple language models of the plurality of language models, the second set of multiple weighting values being associated with a second key phrase, the second set of multiple weighting values being different from the first set of multiple weighting values, and the second key phrase being different from the first key phrase; determining that the docking context indicates docking of the client device with a docking station of a first type; based on determining that the docking context indicates docking of the client device with the docking station of the first type, selecting, from among the multiple sets of weighting values, the first set of multiple weighting values associated with the first key phrase; selecting at least a first language model of the plurality of language models using the first set of multiple weighting values associated with the first key phrase; and performing speech recognition on the audio data using the first language model to identify a transcription for a portion of the audio data. | 1. A computer-implemented method, comprising: accessing audio data that includes encoded speech; accessing information that indicates a docking context of a client device, the docking context being associated with the audio data; identifying a plurality of language models; identifying multiple sets of weighting values for the plurality of language models, the multiple sets of weighting values comprising at least a first set of multiple weighting values that correspond to multiple language models of the plurality of language models, the first set of multiple weighting values being associated with a first key phrase, wherein the first set of multiple weighting values is used to bias selection of a language model when a user utters the first key phrase, and a second set of multiple weighting values that correspond to multiple language models of the plurality of language models, the second set of multiple weighting values being associated with a second key phrase, the second set of multiple weighting values being different from the first set of multiple weighting values, and the second key phrase being different from the first key phrase; determining that the docking context indicates docking of the client device with a docking station of a first type; based on determining that the docking context indicates docking of the client device with the docking station of the first type, selecting, from among the multiple sets of weighting values, the first set of multiple weighting values associated with the first key phrase; selecting at least a first language model of the plurality of language models using the first set of multiple weighting values associated with the first key phrase; and performing speech recognition on the audio data using the first language model to identify a transcription for a portion of the audio data. 18. The computer-implemented method of claim 1 , wherein identifying multiple sets of weighting values for the plurality of language models comprises identifying sets of weighting values that each comprise a weighting value corresponding to each language model of the plurality of language models. | 0.89973 |
9,020,941 | 9 | 10 | 9. The system of claim 8 , wherein the address parser is configured to parse the address term into the region and the feature based on one or more delimiters in the address term. | 9. The system of claim 8 , wherein the address parser is configured to parse the address term into the region and the feature based on one or more delimiters in the address term. 10. The system of claim 9 , wherein each of the one or more delimiters includes one of a word, a punctuation character, or a blank space. | 0.5 |
9,390,709 | 1 | 3 | 1. A semiconductor integrated circuit device comprising: a signal processing unit extracts frequency components of an inputted voice signal, and generates a feature pattern representing a state of distribution of the frequency components of the voice signal; a voice recognition database storage unit which stores a plurality of voice recognition databases each including a standard pattern representing a state of distribution of frequency components of plural phonemes used in a predetermined language, each of the plurality of voice recognition databases having been generated based on voice signals of a different group of speakers, each different group of speakers having a different age and/or gender than other ones of the groups of speakers; a conversion list storage unit which stores a conversion list expressed by character data and including plural words or sentences to be conversion candidates, the plural words or candidates being expected responses to a question or message; a standard pattern extraction unit which extracts the standard pattern corresponding to the character data representing the first syllable of each word or sentence included in the conversion list, from the voice recognition database; and a matching detection unit which receives an input of age and/or gender of a user, and selects a corresponding one of the plurality of voice recognition databases based on the input, and which compares the feature pattern generated from the first syllable of the voice signal with the standard pattern extracted by the standard pattern extraction unit, thus detects the matching of the syllable, and outputs information specifying a word or sentence that has the matching-detected syllable as the first syllable thereof. | 1. A semiconductor integrated circuit device comprising: a signal processing unit extracts frequency components of an inputted voice signal, and generates a feature pattern representing a state of distribution of the frequency components of the voice signal; a voice recognition database storage unit which stores a plurality of voice recognition databases each including a standard pattern representing a state of distribution of frequency components of plural phonemes used in a predetermined language, each of the plurality of voice recognition databases having been generated based on voice signals of a different group of speakers, each different group of speakers having a different age and/or gender than other ones of the groups of speakers; a conversion list storage unit which stores a conversion list expressed by character data and including plural words or sentences to be conversion candidates, the plural words or candidates being expected responses to a question or message; a standard pattern extraction unit which extracts the standard pattern corresponding to the character data representing the first syllable of each word or sentence included in the conversion list, from the voice recognition database; and a matching detection unit which receives an input of age and/or gender of a user, and selects a corresponding one of the plurality of voice recognition databases based on the input, and which compares the feature pattern generated from the first syllable of the voice signal with the standard pattern extracted by the standard pattern extraction unit, thus detects the matching of the syllable, and outputs information specifying a word or sentence that has the matching-detected syllable as the first syllable thereof. 3. The semiconductor integrated circuit device according to claim 1 , wherein if the conversion list includes plural words or sentences having the matching-detected syllable as the first syllables thereof, the matching detection unit expands a range of syllables to be detected for matching. | 0.721264 |
9,280,906 | 7 | 11 | 7. A computer-implemented method comprising: under control of one or more computing devices configured with specific computer-executable instructions, identifying a first corresponding word, wherein the first corresponding word occurs in both an item of textual content and in an item of audio content; identifying a second corresponding word, wherein the second corresponding word occurs after the first corresponding word in both the item of textual content and in the item of audio content; identifying a third corresponding word, wherein the third corresponding word occurs after the second corresponding word in both the item of textual content and in the item of audio content; causing a synchronous audible and textual presentation of the first corresponding word; causing a textual presentation of the second corresponding word without synchronously audibly presenting the second corresponding word; prompting a user to speak the second corresponding word; obtaining a spoken response as audio input; determining that the spoken response includes the second corresponding word; and in response to determining that the spoken response includes the second corresponding word, causing audible presentation of the third corresponding word. | 7. A computer-implemented method comprising: under control of one or more computing devices configured with specific computer-executable instructions, identifying a first corresponding word, wherein the first corresponding word occurs in both an item of textual content and in an item of audio content; identifying a second corresponding word, wherein the second corresponding word occurs after the first corresponding word in both the item of textual content and in the item of audio content; identifying a third corresponding word, wherein the third corresponding word occurs after the second corresponding word in both the item of textual content and in the item of audio content; causing a synchronous audible and textual presentation of the first corresponding word; causing a textual presentation of the second corresponding word without synchronously audibly presenting the second corresponding word; prompting a user to speak the second corresponding word; obtaining a spoken response as audio input; determining that the spoken response includes the second corresponding word; and in response to determining that the spoken response includes the second corresponding word, causing audible presentation of the third corresponding word. 11. The computer-implemented method of claim 7 further comprising: before causing textual presentation of the second corresponding word, prompting a user to input a word; and determining that the input word is substantially identical to the second corresponding word or that the input word is a synonym for the second corresponding word; wherein the textual presentation of the second corresponding word is only caused if the input word is substantially identical to the second corresponding word or the input word is a synonym for the second corresponding word. | 0.507018 |
7,899,842 | 1 | 4 | 1. A method of identifying a complex string in a data stream, the method encoded into instructions stored in a processor-readable medium coupled to a processor, the method comprising: segmenting said complex string into a set of string segments and a suffix, each string segment comprising a prefix and a simple string, where said prefix includes indefinite characters and said suffix includes indefinite characters; ascertaining congruence of said prefix with a corresponding portion of said data stream; generating an array of bitmasks, each bitmask associated with a string segment in said set of string segments, said bitmask indicating a location index of an end character of said each string segment; associating a Boolean state variable with said complex string; locating a current simple-matchinq position in said data stream at which at least one simple string belonging to said complex string terminates; initializing a current mask as an opaque mask; performing a logical OR operation of said current mask with selected bitmasks corresponding to said at least one simple string to produce a composite current mask; determining a gap between said current simple-matching position and a previous simple-matchinq position; left-shiftinq each entry of said Boolean state variable by said gap, replacing each shifted entry by logical “0” and setting the rightmost entry to logical “1”; and updating said Boolean state variable according to a logical AND operation with said composite current mask. | 1. A method of identifying a complex string in a data stream, the method encoded into instructions stored in a processor-readable medium coupled to a processor, the method comprising: segmenting said complex string into a set of string segments and a suffix, each string segment comprising a prefix and a simple string, where said prefix includes indefinite characters and said suffix includes indefinite characters; ascertaining congruence of said prefix with a corresponding portion of said data stream; generating an array of bitmasks, each bitmask associated with a string segment in said set of string segments, said bitmask indicating a location index of an end character of said each string segment; associating a Boolean state variable with said complex string; locating a current simple-matchinq position in said data stream at which at least one simple string belonging to said complex string terminates; initializing a current mask as an opaque mask; performing a logical OR operation of said current mask with selected bitmasks corresponding to said at least one simple string to produce a composite current mask; determining a gap between said current simple-matching position and a previous simple-matchinq position; left-shiftinq each entry of said Boolean state variable by said gap, replacing each shifted entry by logical “0” and setting the rightmost entry to logical “1”; and updating said Boolean state variable according to a logical AND operation with said composite current mask. 4. The method of claim 1 , wherein the step of ascertaining congruence of said prefix with said corresponding portion of said data stream comprises a step of determining that likewise positioned characters in said prefix and said corresponding portion of said data stream belong to a same character class from among a predefined set of character classes. | 0.718601 |
8,977,540 | 3 | 4 | 3. The method as claimed in claim 1 , wherein identifying topic for each document comprises comparing each Important Words (IW) in the document with its file name and Title name, if any of the IW's matches than that is defined as a Topic. | 3. The method as claimed in claim 1 , wherein identifying topic for each document comprises comparing each Important Words (IW) in the document with its file name and Title name, if any of the IW's matches than that is defined as a Topic. 4. The method as claimed in claim 3 , wherein the IW's with highest frequency occurrences in the document is defined as the topic for the document. | 0.5 |
8,661,403 | 14 | 17 | 14. A system, comprising: a processor; and a memory storing instructions translatable by the processor to implement a collaborative filter having: a first software component configured to determine a similarity among a plurality of items based on observable features thereof; a second software component configured to aggregate online search behavior across multiple users; and a third software component configured to determine what features of the observable features are most important to an individual user, wherein the third component of the collaborative filter examines item discovery behavior of the individual user across multiple dimensions with respect to the observable features in a baseline item and at least one next item, wherein the baseline item is established by the individual user, wherein the instructions are further translatable by the processor to: for each paired observation associated with a baseline item i established by the individual user, determine what a first next item j is expected to be selected; examine all observations associated with the baseline item i to determine what a second next item t is expected to be selected; make a prediction as to which next item the individual user will select; compare the prediction with an actual next item k selected by the individual user; and assign a penalty value to the prediction if the prediction is incorrect. | 14. A system, comprising: a processor; and a memory storing instructions translatable by the processor to implement a collaborative filter having: a first software component configured to determine a similarity among a plurality of items based on observable features thereof; a second software component configured to aggregate online search behavior across multiple users; and a third software component configured to determine what features of the observable features are most important to an individual user, wherein the third component of the collaborative filter examines item discovery behavior of the individual user across multiple dimensions with respect to the observable features in a baseline item and at least one next item, wherein the baseline item is established by the individual user, wherein the instructions are further translatable by the processor to: for each paired observation associated with a baseline item i established by the individual user, determine what a first next item j is expected to be selected; examine all observations associated with the baseline item i to determine what a second next item t is expected to be selected; make a prediction as to which next item the individual user will select; compare the prediction with an actual next item k selected by the individual user; and assign a penalty value to the prediction if the prediction is incorrect. 17. A system according to claim 14 , wherein the second software component of the collaborative filter is further configured to collect item view frequencies only for all hops by the individual user in a sequence of item discovery. | 0.721687 |
7,930,167 | 17 | 20 | 17. A computer readable storage medium with computer executable instructions for a localizable video game, said instructions comprising: instructions for a video game; instructions for a plurality of language packs that include localized video game resources corresponding to a language preference for said video game; and instructions for a language interface pack library that enables the video game to use at least one language pack in the plurality of language packs. | 17. A computer readable storage medium with computer executable instructions for a localizable video game, said instructions comprising: instructions for a video game; instructions for a plurality of language packs that include localized video game resources corresponding to a language preference for said video game; and instructions for a language interface pack library that enables the video game to use at least one language pack in the plurality of language packs. 20. The computer readable storage medium of claim 17 , wherein said video game includes instructions for a language interface pack library that comprises said instructions for performing an update. | 0.5 |
8,738,608 | 41 | 42 | 41. A method of data storage and/or retrieval implemented on one or more digital data processing systems, comprising: providing storage media comprising a plurality of data tunnels, one or more of said plurality of data tunnels having a plurality of data cells, wherein the plurality of data tunnels include a plurality of entity type data tunnels for each of a plurality of entity types and a plurality of attribute data tunnels for each of a plurality of attributes wherein a number of data tunnels for each attribute is fixed for a given attribute, wherein each of the data cells contain data associated with a respective instance of an attribute for a respective and distinct instance of an entity type, wherein each of the data cells of the plurality of attribute data tunnels has data for which a respective operator evaluates to a boolean result indicating either the likely possibility or the impossibility of the attribute instance corresponding to said data cell being characterised by said operator for a given set of one or more operands, and accessing, with a storage engine that is in communications coupling with the storage media, one or more of the plurality of data tunnels based on one or more of said operators and a given set of one or more operands. | 41. A method of data storage and/or retrieval implemented on one or more digital data processing systems, comprising: providing storage media comprising a plurality of data tunnels, one or more of said plurality of data tunnels having a plurality of data cells, wherein the plurality of data tunnels include a plurality of entity type data tunnels for each of a plurality of entity types and a plurality of attribute data tunnels for each of a plurality of attributes wherein a number of data tunnels for each attribute is fixed for a given attribute, wherein each of the data cells contain data associated with a respective instance of an attribute for a respective and distinct instance of an entity type, wherein each of the data cells of the plurality of attribute data tunnels has data for which a respective operator evaluates to a boolean result indicating either the likely possibility or the impossibility of the attribute instance corresponding to said data cell being characterised by said operator for a given set of one or more operands, and accessing, with a storage engine that is in communications coupling with the storage media, one or more of the plurality of data tunnels based on one or more of said operators and a given set of one or more operands. 42. The method of claim 41 , wherein the plurality of data cells include a connective data cell that contains a digest of the attribute instance corresponding said connective data cell, the plurality of data tunnels include a plurality of connective data tunnels, which include a respective connective data tunnel that is chosen from a defined hash encoding of the attribute instance corresponding to said connective data cell and by applying a modulo of the number of the plurality of connective data tunnels to said hash encoding. | 0.889305 |
8,234,193 | 1 | 25 | 1. A computer-implemented method of enabling an organization to run a first promotion integrated with viral features associated with one or more social network-based platforms, comprising: receiving promotion information from the organization; generating one or more promotion applications responsive to the promotion information for integration with the one or more social network-based platforms, wherein the one or more promotion applications provide a way for a plurality of participants to actively interact with the first promotion and advertise the first promotion; receiving promotion entry data from the plurality of participants; storing the promotion entry data; using the viral features provided by the one or more social network-based platforms to increase awareness of at least one of a first group consisting of the promotion, the organization, a good or service associated with the promotion or organization, a third party organization, and the third party organization's good or service. | 1. A computer-implemented method of enabling an organization to run a first promotion integrated with viral features associated with one or more social network-based platforms, comprising: receiving promotion information from the organization; generating one or more promotion applications responsive to the promotion information for integration with the one or more social network-based platforms, wherein the one or more promotion applications provide a way for a plurality of participants to actively interact with the first promotion and advertise the first promotion; receiving promotion entry data from the plurality of participants; storing the promotion entry data; using the viral features provided by the one or more social network-based platforms to increase awareness of at least one of a first group consisting of the promotion, the organization, a good or service associated with the promotion or organization, a third party organization, and the third party organization's good or service. 25. The method of claim 1 , further comprising using a participant's social network-based platform friends list to provide the participant with information about the participant's social network friends' interactions with the first promotion and other promotions. | 0.707127 |
8,568,144 | 1 | 20 | 1. A reading comprehension training system, comprising: a computing device; a game logic portion that generates a reading comprehension challenge that comprises language micro-variables including one or more verb micro-variables, one or more agent micro-variables, and one or more reference micro-variables at a particular level of difficulty to test a user's comprehension of the reading comprehension challenge; a user interface portion that generates a user interface to display the reading comprehension challenge at the particular skill level on the computing device; and wherein the game logic portion comprises a game administrator portion that: receives a response from the user to the reading comprehension challenge based on controlled manipulation of the language micro-variables in the reading comprehension challenge, isolates one or more language micro-variables that are impeding the user's comprehension of the reading comprehension challenge based on the response from the user, provides direct instruction to train the user to become more proficient at the isolated one or more language micro-variables based on controlled manipulation of the isolated one or more language micro-variables, and determines, once the user becomes more proficient at the isolated one or more language micro-variables, a next reading comprehension challenge that comprises language micro-variables including one or more verb micro-variables, one or more agent micro-variables, and one or more reference micro-variables at a particular level of difficulty to test the user's comprehension of the next reading comprehension challenge. | 1. A reading comprehension training system, comprising: a computing device; a game logic portion that generates a reading comprehension challenge that comprises language micro-variables including one or more verb micro-variables, one or more agent micro-variables, and one or more reference micro-variables at a particular level of difficulty to test a user's comprehension of the reading comprehension challenge; a user interface portion that generates a user interface to display the reading comprehension challenge at the particular skill level on the computing device; and wherein the game logic portion comprises a game administrator portion that: receives a response from the user to the reading comprehension challenge based on controlled manipulation of the language micro-variables in the reading comprehension challenge, isolates one or more language micro-variables that are impeding the user's comprehension of the reading comprehension challenge based on the response from the user, provides direct instruction to train the user to become more proficient at the isolated one or more language micro-variables based on controlled manipulation of the isolated one or more language micro-variables, and determines, once the user becomes more proficient at the isolated one or more language micro-variables, a next reading comprehension challenge that comprises language micro-variables including one or more verb micro-variables, one or more agent micro-variables, and one or more reference micro-variables at a particular level of difficulty to test the user's comprehension of the next reading comprehension challenge. 20. The system of claim 1 , wherein the game logic portion further comprising a unit for selecting the words for a vocabulary training exercise, the selection unit further comprising the steps of: identifying words having a particular frequency of use in a frequency band for each grade level of a student and selecting words for the vocabulary training exercise for a particular grade level from the frequency band appropriate for the grade level and based on a pervasiveness value of the words. | 0.639535 |
9,996,441 | 1 | 2 | 1. A method of building at least a portion of a script that retrieves information from a website, the method comprising: receiving, at a computing system via a network, a request from a user to retrieve information from the website; determining, via the computing system, that no satisfactory script for retrieving the requested information from the website exists in a database; receiving, at the computing system via the network, an indication of a page type for a first web page of the website from the user; retrieving, via the network, the first web page via a network; identifying, via the computing system, a candidate script element previously defined for the page type based on a second web page; determining, via the computing system, a candidate similarity score that measures a similarity between a part of the first web page and a part of a second web page, wherein the candidate script element is configured to perform a function on the part of the second web page; determining the candidate similarity score meets a predefined threshold; and performing, via the candidate script element, the function on the part of the first web page based on the determination that the candidate similarity score meets the predefined threshold. | 1. A method of building at least a portion of a script that retrieves information from a website, the method comprising: receiving, at a computing system via a network, a request from a user to retrieve information from the website; determining, via the computing system, that no satisfactory script for retrieving the requested information from the website exists in a database; receiving, at the computing system via the network, an indication of a page type for a first web page of the website from the user; retrieving, via the network, the first web page via a network; identifying, via the computing system, a candidate script element previously defined for the page type based on a second web page; determining, via the computing system, a candidate similarity score that measures a similarity between a part of the first web page and a part of a second web page, wherein the candidate script element is configured to perform a function on the part of the second web page; determining the candidate similarity score meets a predefined threshold; and performing, via the candidate script element, the function on the part of the first web page based on the determination that the candidate similarity score meets the predefined threshold. 2. The method of claim 1 , wherein performing the function includes logging in to the website, navigating to a third page where the requested information is located, or retrieving the information from the website. | 0.869645 |
8,060,370 | 2 | 3 | 2. A method for mobile audio playback and dictation using a mobile device, comprising: in response to a user initiating a playback mode on the mobile device, an audio playback component of the mobile device entering a playback mode during which a source audio file in a source audio store is played and a voice detection component of the mobile device entering a listen mode during which the voice detection component listens for voice; upon the voice detection component detecting any voice from the user indicative of a voice interrupt condition during the playback mode, the voice detection component transmitting a pause signal to the audio playback component to pause the playback mode and the audio playback component transmitting a source data buffer index to the voice detection component; the voice detection component recording the detected voice as a comment, storing the comment as a recorded comment and the source data buffer index in a recorded comment store of the mobile device, and, upon completion of the voice interrupt condition, transmitting a resume signal to the audio playback component to resume the playback mode of the audio playback component; and in response to the user initiating an upload of the source audio file to a computer, the mobile device providing the source audio file from the source audio store and providing one or more recorded audio comments and corresponding source data buffer indexes from the recorded comment store, further comprising: the computer retrieving the source audio file from the source audio store and the one or more recorded comments and corresponding one or more source data buffer indexes associated with each voice interrupt condition from the recorded comment store; for each recorded comment of the one or more recorded comments retrieved from the recorded comment store, further comprising: the computer transcribing the source audio file back into a source document format in an updated source document until the source data buffer index for the recorded comment is encountered; the computer transcribing the recorded comment into the source document format to generate a source document format comment that is written into the updated source document at the source data buffer index; and from a last source data buffer index of a last recorded comment of the one or more recorded comments to the end of the retrieved source audio file, the computer transcribing the source audio file into the source document format in the updated source document. | 2. A method for mobile audio playback and dictation using a mobile device, comprising: in response to a user initiating a playback mode on the mobile device, an audio playback component of the mobile device entering a playback mode during which a source audio file in a source audio store is played and a voice detection component of the mobile device entering a listen mode during which the voice detection component listens for voice; upon the voice detection component detecting any voice from the user indicative of a voice interrupt condition during the playback mode, the voice detection component transmitting a pause signal to the audio playback component to pause the playback mode and the audio playback component transmitting a source data buffer index to the voice detection component; the voice detection component recording the detected voice as a comment, storing the comment as a recorded comment and the source data buffer index in a recorded comment store of the mobile device, and, upon completion of the voice interrupt condition, transmitting a resume signal to the audio playback component to resume the playback mode of the audio playback component; and in response to the user initiating an upload of the source audio file to a computer, the mobile device providing the source audio file from the source audio store and providing one or more recorded audio comments and corresponding source data buffer indexes from the recorded comment store, further comprising: the computer retrieving the source audio file from the source audio store and the one or more recorded comments and corresponding one or more source data buffer indexes associated with each voice interrupt condition from the recorded comment store; for each recorded comment of the one or more recorded comments retrieved from the recorded comment store, further comprising: the computer transcribing the source audio file back into a source document format in an updated source document until the source data buffer index for the recorded comment is encountered; the computer transcribing the recorded comment into the source document format to generate a source document format comment that is written into the updated source document at the source data buffer index; and from a last source data buffer index of a last recorded comment of the one or more recorded comments to the end of the retrieved source audio file, the computer transcribing the source audio file into the source document format in the updated source document. 3. A method as defined in claim 2 , further comprising, in response to the user initiating a download of a source document from a computer, the mobile device receiving the source audio file from the computer, the source document having been converted by the computer to the source audio file. | 0.5 |
8,627,210 | 1 | 2 | 1. A method comprising: obtaining data for a plurality of meeting participants at a computing apparatus that is in communication with a user interface and display device associated with each meeting participant; obtaining a meeting context for a meeting involving the meeting participants; identifying expert knowledge associated with the meeting context and determining the expert knowledge of each meeting participant with regard to the context; generating data representing social network relationships between the meeting participants; calculating degrees of associations between meeting participants based on the expert knowledge of the meeting participants and the social network relationships, wherein calculating the degrees of associations comprises dynamically weighting the social network relationships between the meeting participants with reference to the meeting context to produce a single degree of association quantity between two meeting participants for the meeting context; generating, for each meeting participant, data that represents single degree of association quantities between the meeting participant and the other meeting participants; and displaying to each meeting participant the data that represents the single degree of association quantities between a specific meeting participant and the other meeting participants. | 1. A method comprising: obtaining data for a plurality of meeting participants at a computing apparatus that is in communication with a user interface and display device associated with each meeting participant; obtaining a meeting context for a meeting involving the meeting participants; identifying expert knowledge associated with the meeting context and determining the expert knowledge of each meeting participant with regard to the context; generating data representing social network relationships between the meeting participants; calculating degrees of associations between meeting participants based on the expert knowledge of the meeting participants and the social network relationships, wherein calculating the degrees of associations comprises dynamically weighting the social network relationships between the meeting participants with reference to the meeting context to produce a single degree of association quantity between two meeting participants for the meeting context; generating, for each meeting participant, data that represents single degree of association quantities between the meeting participant and the other meeting participants; and displaying to each meeting participant the data that represents the single degree of association quantities between a specific meeting participant and the other meeting participants. 2. The method of claim 1 , wherein obtaining a meeting context comprises: detecting a change in the meeting context from a first meeting context to a second meeting context; and repeating said identifying, determining, calculating, generating data that represents the degrees of associations between meeting participants, and displaying based on the second meeting context. | 0.5 |
8,099,407 | 1 | 5 | 1. A computer-implemented method for processing media files using a computer, comprising: monitoring at least one application for the occurrences of events wherein at least one event is associated with a media file; capturing the at least one event upon the occurrence of the event by queuing event data associated with the event at a position in a queue; indexing and storing at least some of the events and the media file associated with the event at a time after the occurrence of the event, wherein the time is based on performance data indicating a readiness to process the event and a position in the queue; receiving a search query; locating at least one relevant media file from the indexed and stored events relevant to the search query; and outputting a result set comprising the at least one relevant media file. | 1. A computer-implemented method for processing media files using a computer, comprising: monitoring at least one application for the occurrences of events wherein at least one event is associated with a media file; capturing the at least one event upon the occurrence of the event by queuing event data associated with the event at a position in a queue; indexing and storing at least some of the events and the media file associated with the event at a time after the occurrence of the event, wherein the time is based on performance data indicating a readiness to process the event and a position in the queue; receiving a search query; locating at least one relevant media file from the indexed and stored events relevant to the search query; and outputting a result set comprising the at least one relevant media file. 5. The method of claim 1 , wherein capturing the event associated with the media file comprises determining event data external to the media file. | 0.724528 |
10,120,955 | 1 | 5 | 1. A method, comprising: receiving data representing a first user intent statement; generating a first graph comprising two or more named entities identified within the first user intent statement and one or more relationships identified between the two or more named entities; receiving data representing a second user intent statement; without modifying the first graph, performing an action based on an intent identified in the second user intent statement; and subsequent to performing the action based on the intent identified in the second user intent statement, performing an action based on an intent identified in the first user intent statement. | 1. A method, comprising: receiving data representing a first user intent statement; generating a first graph comprising two or more named entities identified within the first user intent statement and one or more relationships identified between the two or more named entities; receiving data representing a second user intent statement; without modifying the first graph, performing an action based on an intent identified in the second user intent statement; and subsequent to performing the action based on the intent identified in the second user intent statement, performing an action based on an intent identified in the first user intent statement. 5. The method of claim 1 , further comprising: applying an update rule to the first graph based on an intent identified in a third user intent statement, the update rule comprising one or more additions, deletions, or replacements of nodes in the first graph, wherein applying the update rule is further based at least in part on contents of the first graph, contents of a second graph, or a comparison of an element in the first graph to an element in the second graph. | 0.5 |
7,929,805 | 12 | 15 | 12. A Completely Automated Public test to Tell Computers and Humans Apart (CAPTCHA) system, comprising: a database for storing annotated images, each image depicting a concept or object intended for human recognition; a processor for distorting the images; a display for presenting a distorted image to a user along with a separate list of annotations to choose from; and an input allowing a user to select the annotation that best corresponds to the distorted image. | 12. A Completely Automated Public test to Tell Computers and Humans Apart (CAPTCHA) system, comprising: a database for storing annotated images, each image depicting a concept or object intended for human recognition; a processor for distorting the images; a display for presenting a distorted image to a user along with a separate list of annotations to choose from; and an input allowing a user to select the annotation that best corresponds to the distorted image. 15. The CAPTCHA system of claim 12 , wherein the processor is operative to: present a composite image including a plurality of different images separated by borders which are distorted or otherwise visually obfuscated. | 0.5 |
8,340,405 | 14 | 15 | 14. The computer readable storage medium of claim 7 , wherein the respective second digital file is associated with one or more user provided annotations, and the one or more software modules further comprise instructions for: generating a plurality of classifiers from the plurality of first features; associating one or more annotations to the respective second digital file using corresponding ones of the classifiers; receiving a third plurality of digital files; extracting a plurality of third features from at least one of the third plurality of digital files; partitioning the plurality of third features into a plurality of subsets of the third features; sorting the plurality of the subsets of the third features using corresponding ones of the classifiers and recalculating a distance between respective subsets of the third features and the second features for corresponding ones of the classifiers; determining a weight value corresponding to each one of the classifiers based on the recalculated distances; and associating with the at least one of the plurality of third digital files one or more annotations from annotations of a respective subset of the matched files based on one or more of the weight values. | 14. The computer readable storage medium of claim 7 , wherein the respective second digital file is associated with one or more user provided annotations, and the one or more software modules further comprise instructions for: generating a plurality of classifiers from the plurality of first features; associating one or more annotations to the respective second digital file using corresponding ones of the classifiers; receiving a third plurality of digital files; extracting a plurality of third features from at least one of the third plurality of digital files; partitioning the plurality of third features into a plurality of subsets of the third features; sorting the plurality of the subsets of the third features using corresponding ones of the classifiers and recalculating a distance between respective subsets of the third features and the second features for corresponding ones of the classifiers; determining a weight value corresponding to each one of the classifiers based on the recalculated distances; and associating with the at least one of the plurality of third digital files one or more annotations from annotations of a respective subset of the matched files based on one or more of the weight values. 15. The computer readable storage medium of claim 14 , wherein the one or more software modules further comprise instructions for: iteratively updating one or more of the weight values in response to subsequently receiving a digital file having one or more user provided annotations. | 0.5 |
9,098,808 | 1 | 5 | 1. A method performed by data processing apparatus, the method comprising: receiving a query from an asker; before routing the query to at least one candidate answerer: calculating for each of a plurality of users a respective first probability that the user will successfully answer a query by an asker about one or more topics, wherein the first probability is based at least partly on topics in which the user has expertise, and, for at least one user, the first probability being based at least partly on an additional topic that is not explicitly associated with the at least one user, calculating for each of the plurality of users a respective query-independent second probability that the user will provide a satisfactory answer to the asker, wherein the second probability is based at least partly on a degree of social indirection between the user and the asker, determining a score for each of the users based at least in part on their respective first and second probabilities, and defining a list of candidate answerers based on ranking users of the plurality of users based on respective scores, the list of candidate answerers comprising one or more candidate answerers; and routing the query to the one or more candidate answerers of the list of candidate answerers. | 1. A method performed by data processing apparatus, the method comprising: receiving a query from an asker; before routing the query to at least one candidate answerer: calculating for each of a plurality of users a respective first probability that the user will successfully answer a query by an asker about one or more topics, wherein the first probability is based at least partly on topics in which the user has expertise, and, for at least one user, the first probability being based at least partly on an additional topic that is not explicitly associated with the at least one user, calculating for each of the plurality of users a respective query-independent second probability that the user will provide a satisfactory answer to the asker, wherein the second probability is based at least partly on a degree of social indirection between the user and the asker, determining a score for each of the users based at least in part on their respective first and second probabilities, and defining a list of candidate answerers based on ranking users of the plurality of users based on respective scores, the list of candidate answerers comprising one or more candidate answerers; and routing the query to the one or more candidate answerers of the list of candidate answerers. 5. The method of claim 1 wherein the query is location-sensitive, and wherein the plurality of users is associated with the location. | 0.860587 |
8,620,872 | 1 | 8 | 1. A system for generating content-matching feedback on author-generated documents, the system comprising: a content matching engine comprising computer hardware configured to: provide a user interface for authors to submit documents for content matching feedback to avoid accidental plagiarism, receive a document from an author over a communications medium, the document generated by the author, compare at least a portion of the document to at least a portion of one or more first publications using one or more pattern-matching techniques, generate content-matching feedback responsive to the comparison, the content-matching feedback comprising suggestions for correcting attribution errors in the document to thereby assist the author in avoiding accidental plagiarism, generate a certificate certifying that the document was checked for plagiarism, thereby enabling the author to indicate to a reviewing entity that the document was checked for plagiarism, and output the content-matching feedback for display to the author; and a research recommender in communication with the content matching engine, the research recommender configured to: detect publication associations between a plurality of second publications based at least in part on citations in text of the plurality of second publications, generate one or more research recommendations based at least in part on cited publications in the text of the document and on the publication associations, the one or more research recommendations comprising one or more of the second publications that have publication associations with one or more of the cited publications in the text of the document, and output a subset of the one or more research recommendations for display to the author. | 1. A system for generating content-matching feedback on author-generated documents, the system comprising: a content matching engine comprising computer hardware configured to: provide a user interface for authors to submit documents for content matching feedback to avoid accidental plagiarism, receive a document from an author over a communications medium, the document generated by the author, compare at least a portion of the document to at least a portion of one or more first publications using one or more pattern-matching techniques, generate content-matching feedback responsive to the comparison, the content-matching feedback comprising suggestions for correcting attribution errors in the document to thereby assist the author in avoiding accidental plagiarism, generate a certificate certifying that the document was checked for plagiarism, thereby enabling the author to indicate to a reviewing entity that the document was checked for plagiarism, and output the content-matching feedback for display to the author; and a research recommender in communication with the content matching engine, the research recommender configured to: detect publication associations between a plurality of second publications based at least in part on citations in text of the plurality of second publications, generate one or more research recommendations based at least in part on cited publications in the text of the document and on the publication associations, the one or more research recommendations comprising one or more of the second publications that have publication associations with one or more of the cited publications in the text of the document, and output a subset of the one or more research recommendations for display to the author. 8. The system of claim 1 , wherein the content matching engine is further configured to provide configuration options to the author. | 0.810345 |
8,442,964 | 1 | 4 | 1. A method for information processing in a processing system, comprising: receiving a portion of a first complete document in a first language, said portion including some but not all information in said first complete document; searching a database for and retrieving a complete copy of said first complete document in said first language; machine translating said first complete document from said first language to a second language thereby generating a machine-translated document in said second language; and using the machine-translated document in said second language as a basis for searching for a complete original document in said second language, corresponding to said machine-translated document. | 1. A method for information processing in a processing system, comprising: receiving a portion of a first complete document in a first language, said portion including some but not all information in said first complete document; searching a database for and retrieving a complete copy of said first complete document in said first language; machine translating said first complete document from said first language to a second language thereby generating a machine-translated document in said second language; and using the machine-translated document in said second language as a basis for searching for a complete original document in said second language, corresponding to said machine-translated document. 4. The method of claim 1 , further comprising retrieving said complete original document in said second language, and using said complete original document to train said processing system and improve a search algorithm programmed therein. | 0.525896 |
8,301,808 | 4 | 6 | 4. A peripheral device control method for an information processing apparatus capable of managing a peripheral device, the method comprising: managing a peripheral device application via a peripheral device management screen to be displayed in a viewing area using peripheral device management function control information that defines information required to control each function; storing storage destination information relating to the peripheral device application in a storage unit; externally designating the storage destination information; and comparing first language information included in first storage destination information externally designated with second language information included in second storage destination information stored in the storage unit, wherein the display of the peripheral device management screen is switched using language information included in the peripheral device management function control information and the second language information, and the peripheral device application switches a view content of the viewing area using the first storage destination information when the first language information matches the second language information, and using third storage destination information, which can be generated by replacing the first language information included in the first storage destination information by the second language information, when the first language information does not match the second language information. | 4. A peripheral device control method for an information processing apparatus capable of managing a peripheral device, the method comprising: managing a peripheral device application via a peripheral device management screen to be displayed in a viewing area using peripheral device management function control information that defines information required to control each function; storing storage destination information relating to the peripheral device application in a storage unit; externally designating the storage destination information; and comparing first language information included in first storage destination information externally designated with second language information included in second storage destination information stored in the storage unit, wherein the display of the peripheral device management screen is switched using language information included in the peripheral device management function control information and the second language information, and the peripheral device application switches a view content of the viewing area using the first storage destination information when the first language information matches the second language information, and using third storage destination information, which can be generated by replacing the first language information included in the first storage destination information by the second language information, when the first language information does not match the second language information. 6. The method according to claim 4 , wherein the peripheral device application is a manual viewer application that can display manual information relating to the peripheral device. | 0.565217 |
8,731,916 | 1 | 2 | 1. A computer-implemented method of estimating noise and channel distortions and updating distorted speech parameters for an utterance, within an unscented transformation framework, during automatic speech recognition, comprising: receiving, by the computer, the utterance, wherein the utterance comprises speech generated from a transmission source for delivery to a receiver; applying, by the computer, the unscented transformation framework to speech feature vectors representative of the speech, to determine static distorted speech parameters and dynamic distorted speech parameters with initial noise and channel distortions, the initial noise distortions comprising speech parameters which are initialized by averaging a predetermined number of frames at the beginning and ending of the utterance, wherein the unscented transformation framework utilizes non-linear mapping; and estimating, by the computer, noise and channel distortions in the utterance from the static distorted speech parameters and the dynamic distorted speech parameters. | 1. A computer-implemented method of estimating noise and channel distortions and updating distorted speech parameters for an utterance, within an unscented transformation framework, during automatic speech recognition, comprising: receiving, by the computer, the utterance, wherein the utterance comprises speech generated from a transmission source for delivery to a receiver; applying, by the computer, the unscented transformation framework to speech feature vectors representative of the speech, to determine static distorted speech parameters and dynamic distorted speech parameters with initial noise and channel distortions, the initial noise distortions comprising speech parameters which are initialized by averaging a predetermined number of frames at the beginning and ending of the utterance, wherein the unscented transformation framework utilizes non-linear mapping; and estimating, by the computer, noise and channel distortions in the utterance from the static distorted speech parameters and the dynamic distorted speech parameters. 2. The method of claim 1 , further comprising: applying the unscented transformation framework to the speech feature vectors to estimate static noise parameters, static channel parameters, and dynamic noise parameters; and updating the static distorted speech parameters and the dynamic distorted speech parameters for the distorted speech in the utterance from static clean speech parameters, dynamic clean speech parameters, the static noise parameters, the static channel parameters, and the dynamic noise parameters. | 0.65287 |
7,844,645 | 1 | 7 | 1. One or more tangible computer-readable media having computer-executable instructions embodied thereon that, when executed, perform a method of an operations engine of a computing system for performing a file operation, the method comprising: receiving a request to perform a file operation, the file operation including one of copying or moving a plurality of files from a source to a destination, wherein a file includes one or more of a file and a folder; prior to initiating the file transfer operation, identifying a potential error associated with at least a first file of the plurality of files that will occur when the file operation is performed; presenting an error dialogue that includes an indication of the potential error; performing the file operation for all files of the plurality of files except for the at least first file that is associated with the potential error; receiving a correction of the potential error while performing the file operation for all files of the plurality of files except for the at least first file that is associated with the potential error; and performing the file operation for the first file. | 1. One or more tangible computer-readable media having computer-executable instructions embodied thereon that, when executed, perform a method of an operations engine of a computing system for performing a file operation, the method comprising: receiving a request to perform a file operation, the file operation including one of copying or moving a plurality of files from a source to a destination, wherein a file includes one or more of a file and a folder; prior to initiating the file transfer operation, identifying a potential error associated with at least a first file of the plurality of files that will occur when the file operation is performed; presenting an error dialogue that includes an indication of the potential error; performing the file operation for all files of the plurality of files except for the at least first file that is associated with the potential error; receiving a correction of the potential error while performing the file operation for all files of the plurality of files except for the at least first file that is associated with the potential error; and performing the file operation for the first file. 7. The computer-readable media of claim 1 , wherein performing the file operation for all files of the plurality of files except for the at least first file that is associated with the potential error further comprises: processing the plurality of files in order by processing a top level listing of the plurality of files in order and, for each of the files that includes one or more sub-files, processing each of the sub-files and any subsequent file levels therein in order prior to processing a next file in the top level listing. | 0.570048 |
8,285,662 | 6 | 8 | 6. A programmable apparatus for automatically identifying a breaking scenario during an automated software build, comprising: a computer having a memory and is connected to a rules database; and a delta framework program in the memory, the computer being directed by the delta framework software to perform the following steps: identifying a build artifact from a list of build artifacts in a repository; comparing the build artifact to a current software build; identifying a delta between the build artifact and the current software build; determining whether the delta has a link to a rule in the rules database; responsive to the artifact having a link to a rule, determining whether the rule identifies a breaking scenario; and responsive to the rule identifying the breaking scenario, taking an action specified by the rule. | 6. A programmable apparatus for automatically identifying a breaking scenario during an automated software build, comprising: a computer having a memory and is connected to a rules database; and a delta framework program in the memory, the computer being directed by the delta framework software to perform the following steps: identifying a build artifact from a list of build artifacts in a repository; comparing the build artifact to a current software build; identifying a delta between the build artifact and the current software build; determining whether the delta has a link to a rule in the rules database; responsive to the artifact having a link to a rule, determining whether the rule identifies a breaking scenario; and responsive to the rule identifying the breaking scenario, taking an action specified by the rule. 8. The programmable apparatus of claim 6 , wherein the method performs continuously during the automated software build. | 0.894921 |
8,069,033 | 9 | 11 | 9. An apparatus comprising: a processor; a storage device coupled to the processor and configurable for storing instructions, which, when executed by the processor, cause the processor to perform operations comprising: searching the document for a character sequence that is separated on its ends by blank spaces, such that one or more adjacent pairs of characters in the character sequence are separated by an amount of white space that is ambiguous because it is larger than a kerning space but smaller than a blank space; creating a solution set for the character sequence, wherein each solution in the solution set is obtained by identifying the ambiguous amount of white space between each pair of characters that is separated by an ambiguous amount of white space as either a blank space or a kerning space; searching a dictionary for each solution in the solution set; and using the results from the dictionary search to identify the ambiguous amount of white space between each pair of characters in the character sequence that is separated by an ambiguous amount of white space as either a blank space or a kerning space. | 9. An apparatus comprising: a processor; a storage device coupled to the processor and configurable for storing instructions, which, when executed by the processor, cause the processor to perform operations comprising: searching the document for a character sequence that is separated on its ends by blank spaces, such that one or more adjacent pairs of characters in the character sequence are separated by an amount of white space that is ambiguous because it is larger than a kerning space but smaller than a blank space; creating a solution set for the character sequence, wherein each solution in the solution set is obtained by identifying the ambiguous amount of white space between each pair of characters that is separated by an ambiguous amount of white space as either a blank space or a kerning space; searching a dictionary for each solution in the solution set; and using the results from the dictionary search to identify the ambiguous amount of white space between each pair of characters in the character sequence that is separated by an ambiguous amount of white space as either a blank space or a kerning space. 11. The apparatus of claim 9 , wherein the result of the dictionary search is to find none of the solutions in the solution set, the storage device further configurable for storing instructions which, when executed by the processor, cause the processor to perform operations comprising: prompting a user to manually identify the ambiguous amount of white space between each pair of characters in the character sequence that is separated by an ambiguous amount of white space as either a blank space or a kerning space. | 0.5 |
10,075,415 | 9 | 11 | 9. A device, comprising: a memory; and a processor in communication with the memory and configured to be operatively coupled to a network, the processor, during use: receiving, as input, a policy object having a first language, the policy object defining an operational constraint for an industrial machine, the industrial machine using a second language that is a control language and is different from the first language; detecting, in traffic of the network, a communication associated with the industrial machine; applying the received policy object to the detected communication to determine whether the operational constraint is satisfied; automatically translating the detected communication from the first language into the second language for use by the industrial machine; and modifying the traffic of the network to the industrial machine based on the determination whether the operational constraint is satisfied. | 9. A device, comprising: a memory; and a processor in communication with the memory and configured to be operatively coupled to a network, the processor, during use: receiving, as input, a policy object having a first language, the policy object defining an operational constraint for an industrial machine, the industrial machine using a second language that is a control language and is different from the first language; detecting, in traffic of the network, a communication associated with the industrial machine; applying the received policy object to the detected communication to determine whether the operational constraint is satisfied; automatically translating the detected communication from the first language into the second language for use by the industrial machine; and modifying the traffic of the network to the industrial machine based on the determination whether the operational constraint is satisfied. 11. The device of claim 9 , wherein the industrial machine includes an assembly robot. | 0.851724 |
9,754,192 | 10 | 11 | 10. A system for automatically identifying portions of an image of a physical scene as depicting physical objects of predefined types in the physical scene, the system comprising: a digital camera capturing two-dimensional data from the physical scene, the two-dimensional data being in the form of the image of the physical scene; a lidar device capturing three-dimensional data from the physical scene; and a computing device comprising: one or more processing units; and computer-readable media comprising computer-executable instructions, which, when executed by the one or more processing units, cause the computing device to: generate correspondences between subsets of the two-dimensional data and subsets of the three-dimensional data; identify, based on a first subset of the two-dimensional data, a first portion of the image of the physical scene as depicting a physical object of a first predefined type; select a first subset of the three-dimensional data that corresponds to the first subset of the two-dimensional data based on the generated correspondences; and determine, based on the first subset of the three-dimensional data, that the identified first portion of the image does not actually depict a physical object of the first predefined type. | 10. A system for automatically identifying portions of an image of a physical scene as depicting physical objects of predefined types in the physical scene, the system comprising: a digital camera capturing two-dimensional data from the physical scene, the two-dimensional data being in the form of the image of the physical scene; a lidar device capturing three-dimensional data from the physical scene; and a computing device comprising: one or more processing units; and computer-readable media comprising computer-executable instructions, which, when executed by the one or more processing units, cause the computing device to: generate correspondences between subsets of the two-dimensional data and subsets of the three-dimensional data; identify, based on a first subset of the two-dimensional data, a first portion of the image of the physical scene as depicting a physical object of a first predefined type; select a first subset of the three-dimensional data that corresponds to the first subset of the two-dimensional data based on the generated correspondences; and determine, based on the first subset of the three-dimensional data, that the identified first portion of the image does not actually depict a physical object of the first predefined type. 11. The system of claim 10 , wherein the computer-readable media of the computing device comprise further computer-executable instructions, which, when executed by the one or more processing units, cause the computing device to: generate a set of image features from the two-dimensional data captured by the digital camera; and generate a set of geometric features from the three-dimensional data captured by the lidar device; wherein the generating the correspondences between the subsets of the two-dimensional data and the subsets of the three-dimensional data comprises generating correspondences between image features in the generated set of image features and geometric features in the generated set of geometric features such that the first subset of the two-dimensional data corresponds to the first subset of the three-dimensional data, wherein the generating the correspondences was performed prior to the determining that the identified first portion of the image does not actually depict a physical object of the first predefined type. | 0.552137 |
6,167,395 | 1 | 5 | 1. In a multimedia call center (MMCC) supporting multiple channels and forms of communication and storing call center transactions in a data repository, a threading software application, comprising: a programming input for a user to enter association criteria; an access function that accesses at least stored data in the data repository; a search function that searches accessed data for association criteria, and notes those data entities that meet the association criteria; and a display function that displays at least indicators of data entities meeting the association criteria. | 1. In a multimedia call center (MMCC) supporting multiple channels and forms of communication and storing call center transactions in a data repository, a threading software application, comprising: a programming input for a user to enter association criteria; an access function that accesses at least stored data in the data repository; a search function that searches accessed data for association criteria, and notes those data entities that meet the association criteria; and a display function that displays at least indicators of data entities meeting the association criteria. 5. The application of claim 1 wherein the access function allows access to stored data and also an ability to monitor transactions occurring in real time. | 0.715867 |
9,253,139 | 1 | 7 | 1. A method, comprising: detecting, via a processor, a message posted on a website data source from an end user, the message posting being related to a predefined monitored entity; performing via the processor, a natural language interpretation of the message contents responsive to identifying the message posting being related to the predefined monitored entity; processing via the processor, the message to determine the user's topic of interest and to determine the user's topic of interest relates to a complaint regarding the predefined monitored entity; notifying the predefined monitored entity of the user's topic of interest and complaint; generating via a processor, a response to the message responsive to the user's topic of interest; and sending, via a transmitter, the response to the end user. | 1. A method, comprising: detecting, via a processor, a message posted on a website data source from an end user, the message posting being related to a predefined monitored entity; performing via the processor, a natural language interpretation of the message contents responsive to identifying the message posting being related to the predefined monitored entity; processing via the processor, the message to determine the user's topic of interest and to determine the user's topic of interest relates to a complaint regarding the predefined monitored entity; notifying the predefined monitored entity of the user's topic of interest and complaint; generating via a processor, a response to the message responsive to the user's topic of interest; and sending, via a transmitter, the response to the end user. 7. The method of claim 1 , wherein the message is normalized to determine words of interest prior to fulfilling the user's topic of interest. | 0.675115 |
8,860,752 | 24 | 25 | 24. A method for multimedia scripting in a computer system, comprising the steps of: presenting a script, written in a scripting language, comprising a variable representing one or more multimedia items and a manipulation to be applied to the one or more multimedia items, wherein the scripting language comprises syntax enabling system-wide application of the manipulation; evaluating the script after extraction from a container file at runtime via an interface to one or more programmable processing units communicatively coupled to each other in the computer system; invoking a plurality of processes for manipulating multimedia items in dependence upon the script, each such process associated with one or more multimedia types; processing a first multimedia type with a first process; and processing a second multimedia type with a second process, wherein the script is referenced to render one or more result multimedia items, and is referenced as one or more second original multimedia items in at least one other script for batch manipulation. | 24. A method for multimedia scripting in a computer system, comprising the steps of: presenting a script, written in a scripting language, comprising a variable representing one or more multimedia items and a manipulation to be applied to the one or more multimedia items, wherein the scripting language comprises syntax enabling system-wide application of the manipulation; evaluating the script after extraction from a container file at runtime via an interface to one or more programmable processing units communicatively coupled to each other in the computer system; invoking a plurality of processes for manipulating multimedia items in dependence upon the script, each such process associated with one or more multimedia types; processing a first multimedia type with a first process; and processing a second multimedia type with a second process, wherein the script is referenced to render one or more result multimedia items, and is referenced as one or more second original multimedia items in at least one other script for batch manipulation. 25. The method of claim 24 wherein the scripting language further comprises syntax enabling invocation of the manipulation by a plurality of application programs present in the system. | 0.820663 |
7,742,925 | 1 | 4 | 1. A speech-enabled system, comprising one or more of the following: a question control configured to provide a question function in the speech-enabled system; an announcer control configured to provide an announcer function in the speech-enabled system; a command control configured to provide an command and control function in the speech-enabled system, wherein the command control is operable to associate a grammar with a speech-enabled application; a word trainer control configured to provide a word trainer function in the speech-enabled system; wherein each of the one or more controls includes a code module which are utilized to code multiple speech-enabled applications; wherein the command control is capable of simultaneously utilizing multiple grammars associated with multiple speech-enabled applications; wherein the command control is used by the one or more speech-enabled applications to specify which of the multiple grammars an associated speech-enabled application is interested in listening to; wherein the command control is used by the one or more speech-enabled applications to alert the associated speech-enabled application when a recognition has occurred from the associated grammar; wherein in response to the command control receiving a command included in a grammar associated with an the unloaded speech-enabled application, the speech-enabled system automatically loads the unloaded speech-enabled application; and wherein one or more of the controls are computer executable and stored by a computer-storage medium. | 1. A speech-enabled system, comprising one or more of the following: a question control configured to provide a question function in the speech-enabled system; an announcer control configured to provide an announcer function in the speech-enabled system; a command control configured to provide an command and control function in the speech-enabled system, wherein the command control is operable to associate a grammar with a speech-enabled application; a word trainer control configured to provide a word trainer function in the speech-enabled system; wherein each of the one or more controls includes a code module which are utilized to code multiple speech-enabled applications; wherein the command control is capable of simultaneously utilizing multiple grammars associated with multiple speech-enabled applications; wherein the command control is used by the one or more speech-enabled applications to specify which of the multiple grammars an associated speech-enabled application is interested in listening to; wherein the command control is used by the one or more speech-enabled applications to alert the associated speech-enabled application when a recognition has occurred from the associated grammar; wherein in response to the command control receiving a command included in a grammar associated with an the unloaded speech-enabled application, the speech-enabled system automatically loads the unloaded speech-enabled application; and wherein one or more of the controls are computer executable and stored by a computer-storage medium. 4. The speech-enabled system as recited in claim 1 , wherein the question control comprises an interrupting property that, when utilized by a speech-enabled application, causes an interaction created by the question control to be processed immediately upon being submitted to the speech-enabled system. | 0.5 |
8,914,398 | 1 | 5 | 1. A computer-implemented method, comprising: receiving text input, the text input including content associated with an input source; providing the text input to a keyword suggestion tool, wherein the keyword suggestion tool generates one or more keywords based on the text input; applying a text reduction function to the text input to generate a reduced text that is a subset of the text input, wherein the text reduction function is based on a term importance score of terms in the text input; providing the reduced text to the keyword suggestion tool, wherein the keyword suggestion tool generates one or more keywords based on the reduced text, the one or more keywords generated based on the reduced text generated independently from the one or more keywords generated based on the text input; and generating a keyword set output from a combination of the one or more keywords based on the text input and the one or more keywords based on the reduced text. | 1. A computer-implemented method, comprising: receiving text input, the text input including content associated with an input source; providing the text input to a keyword suggestion tool, wherein the keyword suggestion tool generates one or more keywords based on the text input; applying a text reduction function to the text input to generate a reduced text that is a subset of the text input, wherein the text reduction function is based on a term importance score of terms in the text input; providing the reduced text to the keyword suggestion tool, wherein the keyword suggestion tool generates one or more keywords based on the reduced text, the one or more keywords generated based on the reduced text generated independently from the one or more keywords generated based on the text input; and generating a keyword set output from a combination of the one or more keywords based on the text input and the one or more keywords based on the reduced text. 5. The computer-implemented method of claim 1 , wherein the text input is received periodically or aperiodically from a source feed. | 0.840194 |
7,912,861 | 15 | 20 | 15. A non-transitory computer-readable medium comprising computer-executable instructions for testing layered data for the existence of at least one value, wherein execution of said computer-executable instructions by one or more processors causes said one or more processors to: accept a subset of data for an audience with respect to another audience into a data attribute table of said database wherein said subset of data is unique with respect to said another audience, wherein audience data for said audience not contained in said subset of data is inherited from at least one other audience including said another audience, wherein said audience and said another audience differ in one or more of language, country, region, regulatory, or cultural designations; obtain on said computer a current audience identifier wherein said current audience identifier is associated with a current layer of data corresponding to a current audience; obtain on said computer an audience order of inheritance for said current audience identifier, wherein said audience order of inheritance is implemented as a linear structure specifying two or more audience identifiers comprising a first audience identifier associated with a first layer of data for a first audience and a second audience identifier associated with a second layer of data for a second audience, wherein said second audience identifier is independently specified in said linear structure with respect to said first audience identifier; check said database for a value or link in a field in a plurality of layers of data associated with said two or more audience identifiers of said linear structure, wherein said first audience layer is checked before said second audience layer; accept on said computer an operator to determine if said value or link exists in one or more layers of data; apply said operator in relation to said checking; and, return a result set for a search based on said checking wherein said result indicates the existence of said value or link. | 15. A non-transitory computer-readable medium comprising computer-executable instructions for testing layered data for the existence of at least one value, wherein execution of said computer-executable instructions by one or more processors causes said one or more processors to: accept a subset of data for an audience with respect to another audience into a data attribute table of said database wherein said subset of data is unique with respect to said another audience, wherein audience data for said audience not contained in said subset of data is inherited from at least one other audience including said another audience, wherein said audience and said another audience differ in one or more of language, country, region, regulatory, or cultural designations; obtain on said computer a current audience identifier wherein said current audience identifier is associated with a current layer of data corresponding to a current audience; obtain on said computer an audience order of inheritance for said current audience identifier, wherein said audience order of inheritance is implemented as a linear structure specifying two or more audience identifiers comprising a first audience identifier associated with a first layer of data for a first audience and a second audience identifier associated with a second layer of data for a second audience, wherein said second audience identifier is independently specified in said linear structure with respect to said first audience identifier; check said database for a value or link in a field in a plurality of layers of data associated with said two or more audience identifiers of said linear structure, wherein said first audience layer is checked before said second audience layer; accept on said computer an operator to determine if said value or link exists in one or more layers of data; apply said operator in relation to said checking; and, return a result set for a search based on said checking wherein said result indicates the existence of said value or link. 20. The non-transitory computer readable medium of claim 15 wherein execution of said computer-executable instructions further causes said one or more processors to: accept a free form search operator; accept at least one key word; and, apply said free form search operator and said at least one key word, wherein said result is limited by said free form search operator. | 0.524359 |
7,925,652 | 13 | 15 | 13. A computer-based method for approximate matching of a candidate character string to a set of reference character strings stored within a database, said method comprising: identifying a set of dissimilar character strings in a plurality of character string records stored in the database utilizing an optimization search to generate a set of dissimilar reference character strings; generating a binary index for each character string record stored within the database based on a comparison of an n-gram representation of a selected one of the character strings in the character string record and an n-gram representation of each of the set of dissimilar reference character strings, wherein an i-th bit of the binary index represents a degree of matching of the candidate string with the i-th reference character string; generating a binary index for a respective one of a candidate character string in a candidate character string record; individually comparing the binary index of the candidate character string to the binary index for each reference character string in the set of reference character strings using a structured query language n-gram frequency similarity calculation to compare the n-gram representations by: a) determining a magnitude (A) of a vector associated with the n-gram representation of the candidate character string; b) determining a magnitude (B) of a vector associated with the n-gram representation of one of the reference character strings as magnitude B; c) computing a dot product between the two vectors; and d) computing the similarity metric for the candidate character string with respect to the reference character string according to (dot product/(magnitude A× magnitude B)); and repeating steps b), c), and d) for each reference character string wherein the number of records containing a reference character string is less than a number of the plurality of character string records. | 13. A computer-based method for approximate matching of a candidate character string to a set of reference character strings stored within a database, said method comprising: identifying a set of dissimilar character strings in a plurality of character string records stored in the database utilizing an optimization search to generate a set of dissimilar reference character strings; generating a binary index for each character string record stored within the database based on a comparison of an n-gram representation of a selected one of the character strings in the character string record and an n-gram representation of each of the set of dissimilar reference character strings, wherein an i-th bit of the binary index represents a degree of matching of the candidate string with the i-th reference character string; generating a binary index for a respective one of a candidate character string in a candidate character string record; individually comparing the binary index of the candidate character string to the binary index for each reference character string in the set of reference character strings using a structured query language n-gram frequency similarity calculation to compare the n-gram representations by: a) determining a magnitude (A) of a vector associated with the n-gram representation of the candidate character string; b) determining a magnitude (B) of a vector associated with the n-gram representation of one of the reference character strings as magnitude B; c) computing a dot product between the two vectors; and d) computing the similarity metric for the candidate character string with respect to the reference character string according to (dot product/(magnitude A× magnitude B)); and repeating steps b), c), and d) for each reference character string wherein the number of records containing a reference character string is less than a number of the plurality of character string records. 15. A computer-based method according to claim 13 further comprising: joining records that share the same binary index value; and sorting the joined records by relevance by summing the products of the frequency weights of all matching n-gram representations. | 0.529197 |
8,799,770 | 1 | 5 | 1. A computer implemented method, comprising: generating, by a first device, an executable that, when processed at a second device, reproduces one or more components and content associated with the one or more components as an in-memory data structure, wherein the one or more components and the content associated with the one or more components represent an extensible markup language (XML) document, the generating comprises providing the executable in a format used by the second device of a recipient, and the executable is in a particular program code format that comprises: a machine-specific program code format, a byte-code format, a machine-independent program code format, or a combination thereof; and configuring, by the first device, the executable with authentication logic, policy logic, and retrieval logic, and: the authentication logic provides authentication for the recipient that attempts to access the XML document via the executable at the second device, the policy logic enforces policy restrictions, the policy restrictions conditionally restrict how the one or more components and content associated with the one or more components of the XML document are subsequently populated to the in-memory data structure for the recipient at the second device, and the retrieval logic permits an embedded reference to an external document within the XML document to be appropriately retrieved by the recipient at the second device, and wherein the authentication logic, the policy logic, and the retrieval logic each include one or more instructions that are represented within the executable, such that when the executable is executed, the authentication logic, the policy logic, and the retrieval logic are processed with the executable, the authentication logic enforces identity verification when the recipient attempts to access the XML document at the second device, and the authentication logic and the policy logic together with the retrieval logic enforce conditional restrictions that determine whether the external document is to be retrieved and populated to the in-memory data structure for the recipient at the second device. | 1. A computer implemented method, comprising: generating, by a first device, an executable that, when processed at a second device, reproduces one or more components and content associated with the one or more components as an in-memory data structure, wherein the one or more components and the content associated with the one or more components represent an extensible markup language (XML) document, the generating comprises providing the executable in a format used by the second device of a recipient, and the executable is in a particular program code format that comprises: a machine-specific program code format, a byte-code format, a machine-independent program code format, or a combination thereof; and configuring, by the first device, the executable with authentication logic, policy logic, and retrieval logic, and: the authentication logic provides authentication for the recipient that attempts to access the XML document via the executable at the second device, the policy logic enforces policy restrictions, the policy restrictions conditionally restrict how the one or more components and content associated with the one or more components of the XML document are subsequently populated to the in-memory data structure for the recipient at the second device, and the retrieval logic permits an embedded reference to an external document within the XML document to be appropriately retrieved by the recipient at the second device, and wherein the authentication logic, the policy logic, and the retrieval logic each include one or more instructions that are represented within the executable, such that when the executable is executed, the authentication logic, the policy logic, and the retrieval logic are processed with the executable, the authentication logic enforces identity verification when the recipient attempts to access the XML document at the second device, and the authentication logic and the policy logic together with the retrieval logic enforce conditional restrictions that determine whether the external document is to be retrieved and populated to the in-memory data structure for the recipient at the second device. 5. The method of claim 1 , wherein said generating further includes providing logic within the executable that produces the in-memory data structure in a Document Object Model (DOM) format. | 0.675258 |
8,370,130 | 16 | 17 | 16. The speech understanding method of claim 12 , wherein said selectively producing the retrieved semantic representation produces the speech recognition result if the determined semantic representation does not exist in the example-based semantic representation pattern database. | 16. The speech understanding method of claim 12 , wherein said selectively producing the retrieved semantic representation produces the speech recognition result if the determined semantic representation does not exist in the example-based semantic representation pattern database. 17. The speech understanding method of claim 16 , wherein said selectively producing the retrieved semantic representation creates a sentence corresponding to the retrieved semantic representation, or produces the speech recognition result, the retrieved semantic representation and the additional information, if the determined semantic representation exists in the example-based semantic representation pattern database. | 0.5 |
9,208,776 | 11 | 16 | 11. A system, the system comprising: a processor; a computer-readable storage medium having instructions stored which, when executed by the processor, result in the processor performing operations comprising: retrieving information describing media available in a media content retrieval system, to yield retrieved information; constructing a graph that models how the media are interconnected based on the retrieved information, the graph interconnecting disparate categories of the media; weighting the graph based on the retrieved information, to yield a weighted graph; normalizing the weighted graph, to yield a normalized weighted graph; ranking the retrieved information describing the media based on the normailized weighted graph, to yield ranked information; and generating a speech recognition model based on the ranked information. | 11. A system, the system comprising: a processor; a computer-readable storage medium having instructions stored which, when executed by the processor, result in the processor performing operations comprising: retrieving information describing media available in a media content retrieval system, to yield retrieved information; constructing a graph that models how the media are interconnected based on the retrieved information, the graph interconnecting disparate categories of the media; weighting the graph based on the retrieved information, to yield a weighted graph; normalizing the weighted graph, to yield a normalized weighted graph; ranking the retrieved information describing the media based on the normailized weighted graph, to yield ranked information; and generating a speech recognition model based on the ranked information. 16. The system of claim 11 , wherein ranking the information describing the media is based on an algorithm which ranks pages. | 0.568966 |
8,620,872 | 12 | 14 | 12. A computer-implemented method for generating content-matching feedback on author-generated documents, the method comprising: providing functionality for authors to submit documents for content matching feedback to avoid accidental plagiarism; receiving a document from an author over a communications medium; receiving a request from the author for content-matching feedback about the document; generating content-matching feedback responsive to the request, the generating of content-matching feedback comprising performing a content matching analysis of at least a portion of the document with at least a portion of one or more second documents to thereby assist the author in avoiding accidental plagiarism; generating a certificate certifying that the document was checked for plagiarism, thereby enabling the author to indicate to a reviewing entity that the document was checked for plagiarism; detecting publication associations among a plurality of publications based at least in part on a number of times the publications citations were cited together; generating one or more research recommendations based at least in part on citations in the document and on the publication associations, the one or more research recommendations comprising a citation to at least one of the publications; and outputting the content-matching feedback and the one or more research recommendations for display to the author; wherein at least said generating content-matching feedback is performed by a computer system comprising computer hardware. | 12. A computer-implemented method for generating content-matching feedback on author-generated documents, the method comprising: providing functionality for authors to submit documents for content matching feedback to avoid accidental plagiarism; receiving a document from an author over a communications medium; receiving a request from the author for content-matching feedback about the document; generating content-matching feedback responsive to the request, the generating of content-matching feedback comprising performing a content matching analysis of at least a portion of the document with at least a portion of one or more second documents to thereby assist the author in avoiding accidental plagiarism; generating a certificate certifying that the document was checked for plagiarism, thereby enabling the author to indicate to a reviewing entity that the document was checked for plagiarism; detecting publication associations among a plurality of publications based at least in part on a number of times the publications citations were cited together; generating one or more research recommendations based at least in part on citations in the document and on the publication associations, the one or more research recommendations comprising a citation to at least one of the publications; and outputting the content-matching feedback and the one or more research recommendations for display to the author; wherein at least said generating content-matching feedback is performed by a computer system comprising computer hardware. 14. The method of claim 12 , wherein receiving the document from the author further comprises receiving application programming interface (API) calls over a communications medium. | 0.567633 |
8,909,591 | 1 | 5 | 1. A computer implemented method for identifying business listings, the method comprising: determining, using one or more processors, a first frequency value of a business listing characteristic within a first plurality of business listings received from a first source, the first plurality of business listings being associated with a particular business listing context; determining, using the one or more processors, a second frequency value of the business listing characteristic within a second plurality of business listings received from a second source, the second plurality of business listings being associated with the particular business listing context; determining, using the one or more processors, a frequency differential between the first frequency value and the second frequency value; in response to the frequency differential exceeding a threshold differential, identifying, using the one or more processors, the business listing characteristic as a differential characteristic; and identifying, using the one or more processors, a particular business listing of the plurality of business listings as a spam listing using the differential characteristic. | 1. A computer implemented method for identifying business listings, the method comprising: determining, using one or more processors, a first frequency value of a business listing characteristic within a first plurality of business listings received from a first source, the first plurality of business listings being associated with a particular business listing context; determining, using the one or more processors, a second frequency value of the business listing characteristic within a second plurality of business listings received from a second source, the second plurality of business listings being associated with the particular business listing context; determining, using the one or more processors, a frequency differential between the first frequency value and the second frequency value; in response to the frequency differential exceeding a threshold differential, identifying, using the one or more processors, the business listing characteristic as a differential characteristic; and identifying, using the one or more processors, a particular business listing of the plurality of business listings as a spam listing using the differential characteristic. 5. The method of claim 1 , wherein identifying the particular business listing further comprises: identifying, using the one or more processors, a spam score for the particular business listing using the differential characteristic; and wherein identifying the past business listing as the spam listing is done in response to the spam score being greater than a threshold. | 0.5 |
8,862,250 | 4 | 5 | 4. The method of claim 1 , further comprising using a database accessible by both the model-based expert system and the rule-based expert system, wherein the database comprises: (a) data pertaining to the configuration of the mathematical model in the model-based expert system; and (b) data pertaining to the configuration of the rules in the rule-based expert system. | 4. The method of claim 1 , further comprising using a database accessible by both the model-based expert system and the rule-based expert system, wherein the database comprises: (a) data pertaining to the configuration of the mathematical model in the model-based expert system; and (b) data pertaining to the configuration of the rules in the rule-based expert system. 5. The method of claim 4 , wherein the database further comprises: (c) data pertaining to the message suppression relationships in the integrated expert system. | 0.5 |
9,183,224 | 11 | 15 | 11. A server system, for processing a visual query, comprising: one or more central processing units for executing programs; memory storing one or more programs be executed by the one or more central processing units; the one or more programs comprising instructions for: receiving a visual query from a client system; performing optical character recognition (OCR) on the visual query to produce text recognition data representing a plurality of textual characters, including a plurality of textual characters in a contiguous region of the visual query; scoring each textual character in the plurality of textual characters based on at least high quality textual character scores and low quality textual character scores of other textual characters surrounding the textual character, wherein the scoring of each textual character is based, in part, on a transition cost associated with each textual character such that each textual character will score more similarly to the other textual characters surrounding the textual character as the transition cost increases; identifying one or more high quality text segments in the contiguous region of the visual query in accordance with a determination that a respective high quality text segment of the one or more high quality text segments comprises a plurality of high scoring textual characters; identifying, a document containing at least one high quality text segment of the one or more high quality text segments; retrieving the document containing the at least one high quality text segment; and sending at least a portion of the document to the client system. | 11. A server system, for processing a visual query, comprising: one or more central processing units for executing programs; memory storing one or more programs be executed by the one or more central processing units; the one or more programs comprising instructions for: receiving a visual query from a client system; performing optical character recognition (OCR) on the visual query to produce text recognition data representing a plurality of textual characters, including a plurality of textual characters in a contiguous region of the visual query; scoring each textual character in the plurality of textual characters based on at least high quality textual character scores and low quality textual character scores of other textual characters surrounding the textual character, wherein the scoring of each textual character is based, in part, on a transition cost associated with each textual character such that each textual character will score more similarly to the other textual characters surrounding the textual character as the transition cost increases; identifying one or more high quality text segments in the contiguous region of the visual query in accordance with a determination that a respective high quality text segment of the one or more high quality text segments comprises a plurality of high scoring textual characters; identifying, a document containing at least one high quality text segment of the one or more high quality text segments; retrieving the document containing the at least one high quality text segment; and sending at least a portion of the document to the client system. 15. The system of claim 11 , wherein the instructions for retrieving a document further includes instructions for: calculating a quality score of a respective high quality text segment of the one or more high quality text segments; retrieving an image version of the document when the quality score is below a predetermined value; and retrieving a machine readable text version of the document when the quality score is at or above a predetermined value. | 0.5 |
8,775,431 | 10 | 12 | 10. A computer-implemented method, comprising: receiving data from a plurality of remote data sources, the received data being associated with a plurality of search terms; analyzing the received data to identify a trending search term; comparing the trending search term with a database of topical terms, the database of topical terms including terms relevant to a predetermined topic associated with a particular publishing entity; determining that the trending search term is relevant to the predetermined topic; querying a content database using the trending search term to identify a caption to be associated with the trending search term, the content database including content published by the particular publishing entity; appending the caption to the trending search term; and storing the trending search term and the caption in a database, wherein the terms in the database of topical terms are derived from data in the content database. | 10. A computer-implemented method, comprising: receiving data from a plurality of remote data sources, the received data being associated with a plurality of search terms; analyzing the received data to identify a trending search term; comparing the trending search term with a database of topical terms, the database of topical terms including terms relevant to a predetermined topic associated with a particular publishing entity; determining that the trending search term is relevant to the predetermined topic; querying a content database using the trending search term to identify a caption to be associated with the trending search term, the content database including content published by the particular publishing entity; appending the caption to the trending search term; and storing the trending search term and the caption in a database, wherein the terms in the database of topical terms are derived from data in the content database. 12. The computer-implemented method of claim 10 , wherein the trending search term is a search term identified as having a higher than normal search frequency. | 0.577128 |
10,140,263 | 11 | 16 | 11. A non-transitory data processing system-readable medium bearing code which, when executed by one or more processors of a data processing system, causes the data processing system to: receive an electronic version of a document comprising a plurality of content portions; identify a plurality of prescribed elements for the document, wherein at least some of the plurality of prescribed elements are identified based on a document type for the document; correlate at least some content portions in the editing copy of the document to corresponding prescribed elements of the plurality of prescribed elements; determine a state value for each prescribed element of the plurality of prescribed elements, the state value corresponding to one of present, missing, or incomplete; generate an editing copy of the document, the generating comprising embedding code in the editing copy of the document, the code identifying at least one task corresponding to at least one content portion of the document, the code defining at least one user interface element for presentation within the editing copy when the editing copy is rendered and presented; transmit, to a user system, the editing copy of the document including the embedded code and the state value for each prescribed element of the plurality of prescribed elements for rendering and presentation by the user system; receive, from the user system, an instruction to add a new content portion not included in the plurality of content portions to the editing copy of the document; store the new content portion at the data processing system; correlate the new content portion to a further prescribed element of the plurality of prescribed elements; update the state value for the further prescribed element; and transmit, to the user system, the updated state value. | 11. A non-transitory data processing system-readable medium bearing code which, when executed by one or more processors of a data processing system, causes the data processing system to: receive an electronic version of a document comprising a plurality of content portions; identify a plurality of prescribed elements for the document, wherein at least some of the plurality of prescribed elements are identified based on a document type for the document; correlate at least some content portions in the editing copy of the document to corresponding prescribed elements of the plurality of prescribed elements; determine a state value for each prescribed element of the plurality of prescribed elements, the state value corresponding to one of present, missing, or incomplete; generate an editing copy of the document, the generating comprising embedding code in the editing copy of the document, the code identifying at least one task corresponding to at least one content portion of the document, the code defining at least one user interface element for presentation within the editing copy when the editing copy is rendered and presented; transmit, to a user system, the editing copy of the document including the embedded code and the state value for each prescribed element of the plurality of prescribed elements for rendering and presentation by the user system; receive, from the user system, an instruction to add a new content portion not included in the plurality of content portions to the editing copy of the document; store the new content portion at the data processing system; correlate the new content portion to a further prescribed element of the plurality of prescribed elements; update the state value for the further prescribed element; and transmit, to the user system, the updated state value. 16. The non-transitory data processing system-readable medium of claim 11 , wherein transmitting the state value for each prescribed element of the plurality of prescribed elements comprises transmitting additional code executable by the user system to present an identification of each of the plurality of prescribed elements and their respective state value for user selection at the user system. | 0.866174 |
7,903,566 | 1 | 2 | 1. A computer-based method for detecting anomalies in the traffic passing through an internet protocol (IP) network, said method comprising: extracting, from a database, a single instance of each unique packet header associated with a plurality of IP-to-IP packets, the IP-to-IP packets having been transmitted across the IP network over a predefined period of time; analyzing by a computer the packet headers to identify anomalous conversations based on at least one of a conversation uniqueness, a time of week uniqueness, and a data quantity uniqueness; and providing by the computer alerts corresponding to detected anomalous conversations. | 1. A computer-based method for detecting anomalies in the traffic passing through an internet protocol (IP) network, said method comprising: extracting, from a database, a single instance of each unique packet header associated with a plurality of IP-to-IP packets, the IP-to-IP packets having been transmitted across the IP network over a predefined period of time; analyzing by a computer the packet headers to identify anomalous conversations based on at least one of a conversation uniqueness, a time of week uniqueness, and a data quantity uniqueness; and providing by the computer alerts corresponding to detected anomalous conversations. 2. The method of claim 1 , wherein said analyzing the packet headers to identify anomalous conversations based on a conversation uniqueness comprises determining whether a particular conversation has been conducted on the IP network over a historical and statistically relevant period based on an IP-to-IP-on-Port conversation tuple. | 0.692237 |
6,084,985 | 1 | 7 | 1. A method for on-line handwriting recognition based on a hidden Markov model, said method comprising the steps of: real-time sensing at least an instantaneous write position of said handwriting; deriving from said handwriting a time-conforming string of samples, and from said string a series of handwriting intervals each associated by derivation to a handwriting feature vector, including calculating a center of gravity from the samples associated with each handwriting interval, and wherein the feature vectors contain one or more vector elements that are based on local observations derived from a single said handwriting interval, said handwriting interval comprising a handwriting frame, as well as being based on one or more vector elements that are based on aggregated observations derived from time-spaced said intervals defined over an associated delay, wherein the aggregated feature vector elements are representable as o'.sub.1 and o'.sub.2 as follows: ##EQU2## where o.sub.1 and o.sub.2 represent the vector elements that are based on local observations, d corresponds to a maximum value of the delay between successive frames, and m indicates a number of functions actually used; matching the time-conforming sequence of feature vectors so derived to one or more example sequence modellings from a database pertaining to the handwriting in question; selecting from said modellings a sufficiently-matching recognition string through hidden-Markov processing; and outputting essentials of a result of said selecting, or alternatively, rejecting said handwriting as failing to be recognized. | 1. A method for on-line handwriting recognition based on a hidden Markov model, said method comprising the steps of: real-time sensing at least an instantaneous write position of said handwriting; deriving from said handwriting a time-conforming string of samples, and from said string a series of handwriting intervals each associated by derivation to a handwriting feature vector, including calculating a center of gravity from the samples associated with each handwriting interval, and wherein the feature vectors contain one or more vector elements that are based on local observations derived from a single said handwriting interval, said handwriting interval comprising a handwriting frame, as well as being based on one or more vector elements that are based on aggregated observations derived from time-spaced said intervals defined over an associated delay, wherein the aggregated feature vector elements are representable as o'.sub.1 and o'.sub.2 as follows: ##EQU2## where o.sub.1 and o.sub.2 represent the vector elements that are based on local observations, d corresponds to a maximum value of the delay between successive frames, and m indicates a number of functions actually used; matching the time-conforming sequence of feature vectors so derived to one or more example sequence modellings from a database pertaining to the handwriting in question; selecting from said modellings a sufficiently-matching recognition string through hidden-Markov processing; and outputting essentials of a result of said selecting, or alternatively, rejecting said handwriting as failing to be recognized. 7. A method as claimed in claim 1, wherein at least one aggregated feature vector element is based on sensing instantaneous writing pressure. | 0.675115 |
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