Abstract: Systems, methods and products for accessing a set of electronic document templates, identifying instances of common document content such as content items which are semantically similar, and generating component templates containing the common content. Semantically similar content may be identified by analyzing content for factors such as expressed sentiment, included keyphrases, recognizable entities, expressed topics, assigning values to content based on these factors, and determining similarity based on comparisons of the assigned values. Component templates may also be generated based on types of content that include identical text or images, content that has a predefined level of similarity rather than being identical, content that has common rules, scripting logic or variables, metadata, etc. The component templates may be generated automatically, or in response to user instructions.

Abstract: A search is performed based on a voice input combined with user selection of entities displayed on a display screen as well as real-world entities. A voice input is received from the user by a media device, as well as a selection of a first entity being displayed on the media device. A gesture made by the user is also identified, and a second, real-world entity corresponding to the gesture is determined. A search query is constructed based on a search operator in the voice input, the first entity, and the second entity. The search query is transmitted to a database and, in response, the media device receives at least one identifier of a least one content item. The at least one identifier is then generated for display to the user.

Abstract: Systems and methods are provided for presenting aggregate data in response to a natural language user input. In one example, a system includes a display and a computing device coupled to the display and storing instructions executable to receive a natural language user input, process the natural language user input, in response to determining that the user input includes a request to display two different plots of record data specific to the subject, generate, with the virtual assistant, a single graph including the two different plots of record data based on the processed natural language user input, the two different plots of record data plotted from two different record data sets, one or more aspects of the single graph selected based on an overlapping parameter for each of the two different record data sets, and output, to the display, the single graph as part of a communication thread.

Abstract: Systems, devices, and methods of the present invention relate to text classification. A text classification system accesses an utterance of text. The utterance includes at least one word. The text classification system generates a parse tree for the utterance. The parse tree includes at least one terminal node with a word type. The terminal node represents a word of the utterance. The text classification system applies one or more rules to the text. The text classification system then classifies the utterance as a question or a request for an autonomous agent to perform an action.

Abstract: A computer-implemented method of transcribing an audio stream can include transcribing the audio stream using a first transcribing instance having a first predetermined transcription size that is smaller than the total length of the audio stream. The first transcribing instance can provide a plurality of consecutive first transcribed text data snippets of the audio stream and the size of the first transcribed text data snippets can respectively corresponding to the first predetermined transcription size. The audio stream can also be transcribed using at least a second transcribing instance having a second predetermined transcription size that is smaller than the length of the audio stream. The second transcribing instance can provide a plurality of consecutive second transcribed text data snippets each corresponding to the second predetermined transcription size.

Abstract: This disclosure describes a technique to determine whether a client computing device accessing an API is masquerading its device type (i.e., pretending to be a device that it is not). To this end, and according to this disclosure, the client performs certain processing requested by the server to reveal its actual processing capabilities and thereby its true device type, whereupon—once the server learns the true nature of the client device—it can take appropriate actions to mitigate or prevent further damage. To this end, during the API transaction the server returns information to the client device that causes the client device to perform certain computations or actions. The resulting activity is captured on the client computing and then transmitted back to the server, which then analyzes the data to inform its decision about the true client device type.

Abstract: A computer-implemented method for performing cross-document coreference for a corpus of input documents includes determining mentions by parsing the input documents. Each mention includes a first vector for spelling data and a second vector for context data. A hierarchical tree data structure is created by generating several leaf nodes corresponding to respective mentions. Further, for each node, a similarity score is computed based on the first and second vectors of each node. The hierarchical tree is populated iteratively until a root node is created. Each iteration includes merging two nodes that have the highest similarity scores and creating an entity node instead at a hierarchical level that is above the two nodes being merged. Further, each iteration includes computing the similarity score for the entity node. The nodes with the similarity scores above a predetermined value are entities for which coreference has been performed in input documents.

Abstract: A blank template form generation method and system may employ synthetically generated blank template forms, differing from each other in one or more respects, to train a neural network to recognize relevant differences between otherwise similar forms, including types and locations of keywords and potential locations of values corresponding to the keywords. In an embodiment, filled or partly filled forms as well as blank template forms may be used later in training. Forms are input in pairs to identify differences between the two. Depending on the differences, weights of a neural network may be adjusted. After training, when a form is input into the system, whether the form is filled or blank, a blank template may be generated for future use.

Abstract: Operating a low-latency database analysis system with phrase translation may include obtaining a locale-specific phrase localization rule and a canonical phrase localization rule for a phrase, generating a locale-specific index and a locale-specific finite state machine for the locale using the localization definition data and a canonical finite state machine, generating a resolved-request by obtaining a locale-specific token representing locale-specific input data by traversing the locale-specific index, obtaining a canonical token associated with locale-specific token, obtaining a locale-specific phrase by traversing the locale-specific finite state machine, obtaining a canonical phrase corresponding to the locale-specific phrase, the canonical phrase including the canonical token, generate a data-query based on the canonical phrase, obtaining results data responsive to the data expressing the usage intent by executing a query corresponding to the data-query by an in-memory database of the low-latency datab

Abstract: A mechanism is provided in a data processing system to implement a cognitive natural language processing (NLP) system with descriptor uniqueness identification to support named entity mention clustering. The mechanism annotates a set of documents from a corpus of documents for entity types and mentions, collects descriptor usages from all documents in the corpus of documents, analyzes the descriptor usages to classify the descriptors as base terms or modifier terms, generates compatibility scores for the descriptors, and performs entity merging of entity clusters based on the compatibility scores.

Abstract: A virtual repository system with robust item management automatically derives item data from accessed current and past transactions. The system interfaces with merchant systems to receive current and archived transaction data, scans emails for current and past transaction data, monitors browser data for online transaction data, and accepts manual input. Data obtained from all sources is collated and stored in a cache for user validation, whereupon it is added to a virtual repository. Triggers prompt the delivery of responsive results including information from shared virtual repositories.

Abstract: To enhance the accuracy of a learner in semi-supervised learning, learning means of a learning system (S) causes the learner, which is configured to classify symbol information included in each of a plurality of documents, to learn based on training data indicating an attribute value of each of a plurality of attributes. Acquisition means inputs each of the plurality of documents to the learner to acquire the symbol information classified by the learner as an attribute value candidate. Determination means determines whether a symbol or a symbol string indicated by the attribute value candidate satisfies a predetermined condition. Additional learning control means controls, based on a determination result obtained by the determination means, additional learning by the learner using the attribute value candidate.

Abstract: Embodiments of the present disclosure provide a method for generating an information assessment model, a method for determining the usefulness of comment information, apparatus, electronic device, and computer-readable medium.

Abstract: This disclosure describes a portable recording device that is configured to capture real-time multimedia data from a surrounding environment. The portable recording device may comprise one or more sensors to capture the real-time multimedia data, a category selector to selectively toggle between preset positions that designate a category classification to the real-time data, and an activation button to trigger one or more actions relating to the capture of the real-time multimedia data.

Abstract: An Artificial Intelligence (AI)-based data processing system employs a trained AI model for extracting features of products from various product classes and building a product ontology from the features. The product ontology is used to respond to user queries with product recommendations and customizations. Training data for the generation of the AI model for feature extraction is initially accessed and verified to determine of the training data meets a data density requirement. If the training data does not meet the data density requirement, data from one of a historic source or external sources is added to the training data. One of the plurality of AI models is selected for training based on the degree of overlap and the inter-class distance between the datasets of the various product classes within the training data.

Abstract: A processor may receive a plurality of text samples generated by a user and identify at least one variable text element in at least one of the plurality of text samples. The processor may tokenize the at least one variable text element, thereby producing a plurality of tokenized text samples including at least one token. The processor may build a longest common substring from the plurality of tokenized text samples and add the longest common substring and the at least one token to a set of selectable user interface options specific to the user. The processor may generate a user interface comprising the set of selectable user interface options. This can include detecting a user interface context and automatically replacing the at least one token with information specific to the user interface context within the set of selectable user interface options.

Abstract: A query processing system generates and employs a hybrid inverted index of predicates for predicate statement evaluation. The query processing system converts a collection of predicate statements to two parts, a matrix and a set of reduced predicate statements. The query processing system then generates a hybrid inverted index that maps values for variables to predicates from the matrix and the reduced predicate statements that evaluate to true for corresponding values. When querying data, the query processing system performs a lookup on the hybrid inverted index to identify predicates from the matrix and reduced predicate statements that evaluate to true for values of variables for the data. The query processing system identifies predicate statements that evaluate to true by evaluating the matrix and reduced predicate statements using treating predicates identified from the hybrid inverted index as true.

Abstract: Systems and methods for a machine learning query handling platform are described, whereby each computing node in a computer network is configured to implement a respective local prediction model that calculates an output based on input attributes passed through trained parameters of the local prediction model, whereby at least two of the computing nodes calculate different predicted outputs to the same input attributes. In an embodiment, the trained parameters of each local prediction model include a first set of parameters received from a remote server, a second set of parameters received from another interconnected computing node, and a third set of parameters based on data in a local memory. Other embodiments are also described and claimed.

Abstract: Example data processing systems and methods are described. In one implementation, a system accesses a corpus of data and analyzes the data contained in the corpus of data to identify multiple documents. The system generates vector indexes for the multiple documents such that the vector indexes allow a computing system to quickly access the plurality of documents and identify an answer to a question associated with the corpus of data.

Abstract: A system includes a memory and a node. The memory stores first and second log string correlithm objects. The node receives first and second real-world numerical values, and identifies a first sub-string correlithm object from the first log string correlithm object representing the first real-world numerical value and a second sub-string correlithm object from the second log string correlithm object representing the second real-world numerical value. The node aligns the first and second log string correlithm objects such that the first sub-string correlithm object aligns with the second sub-string correlithm object. The node identifies a sub-string correlithm object from the second log string correlithm object representing the logarithmic value of one. The node determines which sub-string correlithm object from the first log string correlithm object aligns with the identified sub-string correlithm object from the second log string correlithm object. The node outputs the determined sub-string correlithm object.

Abstract: Automatic processing of documents often generates results far different from those obtained by manual human processing. For a given document processing task, many different techniques can be tried but it is often not known which will best emulate manual, human processing. This application discloses data processing equipment and methods specially adapted for a specific application: analysis of the breadth of documents. The processing may include context-dependent pre-processing of documents and sub-portions of the documents. The sub-portions may be analyzed based on word count and commonality of words in the respective sub-portions. The equipment and methods disclosed herein improve upon other automated techniques to provide document processing by achieving a result that is quantitatively closer to manual, human processing.

Abstract: A computer-based method of reducing or limiting data transmissions from a computer to a remote network destination includes receiving an indication, at an agent on a computer, that a recent user activity has occurred at the computer. The indication typically includes data relevant to user context when the user activity occurred. The method further includes determining, with the agent, whether the data relevant to the user's context when the user activity occurred indicates that a change in user context relative to a user activity at the computer immediately prior to the recent user activity and conditioning a transmission of data relevant to the recent user activity from the computer to a remote network destination based on an outcome of the determination.

Abstract: A correlithm object processing system that includes a trainer configured to receive a real world input value and a real world output value. The trainer is further configured to send the real world input value to a sensor engine and to receive a source correlithm object in response to sending the real world value to the sensor engine. A source correlithm object is a point in an n-dimensional space represented by a binary string. The trainer is further configured to send a real world output value to an actor engine and to receive a target correlithm object in response to sending the real world output value to the actor engine. A target correlithm object is a point in the n-dimensional space represented by a binary string. The trainer is further configured to generate an entry in a node table linking the source correlithm object with the target correlithm object.

Abstract: A method comprising receiving an image of an electronic document comprising data fields and corresponding textual regions; processing said image to obtain (i) a collection of said data fields comprising an indication of a location and a field type, and (ii) an array of said textual regions comprising an indication of a location and a content; creating a mapping comprising associations of data fields in said collection with textual regions in said array based, at least in part, on analyzing a geometric relationship between each of said data fields and each of said textual regions; deriving at least one context rule for evaluating said associations, based, at least in part, on identifying a structure of said electronic document; and determining a correctness of at least one of said associations in said mapping, based, at least in part, on said at least one context rule.

Abstract: The disclosed computer-implemented method for determining topics of data artifacts may include (1) extracting at least one initial keyword from a data artifact with an unknown topic, (2) creating a set of keywords by generating a plurality of contextually relevant keywords related to the initial keyword and combining the initial keyword with the contextually relevant keywords to form the set of keywords, (3) retrieving, from a topic processor, at least one list of topics associated with each keyword within the set of keywords, and (4) generating, based on the retrieved topic lists, an ordered list of probable topics of the data artifact. Various other methods, systems, and computer-readable media are also disclosed.

Abstract: Providing query suggestions using a query log including a number of user sessions that comprise training data including a sequence of a plurality of sets of queries. Some of the sets of queries include query transitions followed by a purchase related event. The query log is cleaned and normalized. Query log stationary scores and transition scores of at least some of the plurality of sets is generated. A set of query suggestions is built and similarity scores are computed for at least some of the set of query suggestions to determine whether individual ones of the at least some of the set of query suggestions meet a predetermined assurance level. Those that meet the level are included as elements of the set of query suggestions that meet the predetermined assurance level. That set of query suggestions are mixed and ranked in accordance with a user behavior sought to be optimized.

Abstract: The present invention relates to a method for providing a virtual job market on a network comprising an application server and clients and/or electronic message systems allowing to input and output information, wherein the method comprises the following steps: providing primary dimensions information on industries, career levels and functional areas; providing secondary dimensions information on salary ranges and/or geo-data and/or educational information and/or languages and/or special expertises, entering the primary and secondary dimensions information in a three dimensional data base on the application server; collecting information chunks of open jobs and candidate profiles, and placing the information chunks in a distinct cell or number of cells in the three dimensional database.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for receiving a search query that includes a query term from a client device; obtaining first search results for the search query; identifying a candidate expansion of the query term in text associated with the first search results; revising the search query to include the candidate expansion of the query term; and obtaining second search results for the revised search query.

Abstract: Some embodiments of the present disclosure provide a graphical user interface as a means of inputting search parameters to database search engines. In some embodiments, two or three dimensional projections spatially represent relationships between search parameters, located along the periphery of the projections and search hits whose significance are represented by position relative to the center of the projection and comparative distance from each of the search parameters. As the user manipulates the overall shape of the search projection, the weighting of search parameters adjusts, reconfiguring the search. The present disclosure also provides, in some embodiments, an intuitive means of assimilating search parameter weightings based on peer or social network preferences with global search results.

Abstract: Methods, systems, and computer programs are presented for providing internet content, such as related news articles. One method includes an operation for defining a plurality of candidates based on a seed. For each candidate, scores are calculated for relevance, novelty, connection clarity, and transition smoothness. The score for connection clarity is based on a relevance score of the intersection between the words in the seed and the words in each of the candidates. Further, the score for transition smoothness measures the interest in reading each candidate when transitioning from the seed to the candidate. For each candidate, a relatedness score is calculated based on the calculated scores for relevance, novelty, connection clarity, and transition smoothness. In addition, at least one of the candidates is selected based on their relatedness scores for presentation to the user.

Abstract: Some embodiments of the present disclosure provide a graphical user interface as a means of inputting search parameters to database search engines. In some embodiments, two or three dimensional projections spatially represent relationships between search parameters, located along the periphery of the projections and search hits whose significance are represented by position relative to the center of the projection and comparative distance from each of the search parameters. As the user manipulates the overall shape of the search projection, the weighting of search parameters adjusts, reconfiguring the search. The present disclosure also provides, in some embodiments, an intuitive means of assimilating search parameter weightings based on peer or social network preferences with global search results.

Abstract: A method of location-based data organization is provided. The method includes obtaining a graph that includes nodes, each node connected to at least one other node with an arc. The nodes include a geography nodes associated with geographical locations, and activity nodes. The method also includes dynamically assigning weights to the nodes, and finding, for a first activity node, a suggested set of one or more activity nodes.

Abstract: Embodiment described herein are directed to an enhanced search engine with multiple feedback loops for providing optimal search results that are responsive a user's search query. The user's search query is parsed, and based on the underlying terms, different linguistic models and refinement techniques generate alternative candidate search queries that may yield better results. Searches are performed for the original search query and the candidate search queries, and different scores are used to select the best search results to present to the user. Results making it onto the list, as well as the underlying candidate search query, linguistic model, or refinement technique for generating that search query, will have their corresponding scores updated to reflect their success of generating a search result. Scores are stored and used by future searches to come up with better results.

Abstract: Data elements from data sources and having a data value set are linked by using hash functions to determine a dimensionally reduced instance signature for each data element based on all data values associated with that data element to yield a plurality of dimensionally reduced instance signatures of equivalent fixed size such that similarities among the data values in the data value sets across all data elements is maintained among the plurality of instance signatures. Candidate pairs of data elements to link are identified using the plurality of instance signatures in locality sensitive hash functions, and a similarity index is generated for each candidate pair using a pre-determined measure of similarity. Candidate pairs of data elements having a similarity index above a given threshold are linked.

Abstract: A query is received to search data, where the query includes a search term. A search of the data is performed in response to the query, wherein the search produces result data based on the search term and an identifier of a searcher submitting the query.

Abstract: Techniques for providing semantic search of a data store are disclosed. A similarity metric of a document comprising the data store to a concept represented in a semantic model derived at least in part from a reference source that includes content not included in the data store is determined. A relevance metric of a search query to the concept is computed. The similarity metric and the relevance metric are used to determine, at least in part, a ranking of the document with respect to the search query.

Abstract: A node a data grid receives a prepare request identifying data to lock for a first transaction. The prepare request indicates a locking order that is different from a locking order indicated by a prior prepare request of a second transaction using the same data. The node identifies keys that correspond to the data. The keys are co-located on the node. The node ranks the keys to define an order for acquiring locks for the data based on key identifiers that correspond to the keys. The defined order matches a locking order used by the second transaction. The node acquires locks for the data using the defined order.

Abstract: Processing methods and systems are provided for representing documents relative to importance of words in the document. A processor comprising a weighting model of word importance in a document in a collection relative to an importance of the word in other documents in the collection computes a deviation of distribution of the word from a probability distribution of the word in other documents in the collection, where the deviation distribution is weighted in accordance with a concavity control function. A concavity control parameter is adjustable relative to word frequency.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for selecting keywords for resources. In one aspect, a method includes identifying a particular online resource that includes non-text content. Co-visitation data are obtained for the particular resource. The co-visitation data specify one or more co-requested online resources for the particular online resource. Each of the co-requested online resources were requested by a user device within a threshold period of the request for the particular online resource by the user device. Keywords are identified for each of the co-requested online resources, and can include keywords that were selected based on text content of the co-requested online resource. One or more of the identified keywords are selected as keywords for the particular resource.

Abstract: A computer-implemented method for performing a semantically enriched search of services includes: receiving a search string that a user inputs for searching services in a repository; generating queries from the search string; searching a multi-document index using the generated queries, the multi-document index including, for each of the services, an index entry comprising documents interlinked with each other, each of the documents reflecting at least one aspect regarding the service; and presenting an outcome of the search to the user in response to receiving the search string.

Abstract: A computer-implemented method for selecting an article from an input set of articles stored on a database of a source device, comprises generating a subset of the articles relevant to a query article using a relevance metric representing a measure of dissimilarity between the query article and selected articles in the set, computing distance measures for respective ones of the articles in the subset using article attributes and article commentary objects, using the distance measures to determine measures of the diversity of respective ones of articles in the subset from one another, and using the diversity measures to select a diverse article in the subset.

Abstract: Various embodiments promote the discoverability of data that can be contained within a database. In one or more embodiments, data within a database is organized in a structure having a schema. The structure and data can be processed in a manner that renders one or more pseudo-documents each of which constitutes a sub-structure that can be indexed. Once produced and indexed, the pseudo-documents constitute a set of searchable objects each of which relationally points back to its associated structure within the database. Searches can now be performed against the pseudo-documents which, in turn, returns a set of search results. The set of search results can include multiple sub-sets of pseudo-documents, each sub-set of which is associated with a different structure.

Abstract: A social networking system provides relevant third-party content objects to users by matching user location, interests, and other social information with the content, location, and timing associated with the content objects. Content objects are provided based on relevance scores specific to a user. Relevance scores may be calculated based on the user's previous interactions with content object notifications, or based on interests that are common between the user and his or her connections in the social network. Context search is also provided for a user, wherein a list of search of results is ranked according to the relevance score of content object associated with the search results. Notifications may also be priced and distributed to users based on their relevance. In this way, the system can provide notifications that are relevant to user's interests and current circumstances, increasing the likelihood that they will find content objects of interest.

Abstract: Ranking search results using result repetition is described. In an embodiment, a set of results generated by a search engine is ranked or re-ranked based on whether any of the results were included in previous sets of results generated in response to earlier queries by the same user in one or more searching sessions. User behavior data, such as whether a user clicks on a result, skips a result or misses a result, is stored in real-time and the stored data is used in performing the ranking. In various examples, the ranking is performed using a machine-learning algorithm and various parameters, such as whether a result in a current set of results has previously been clicked, skipped or missed in the same session, are generated based on the user behavior data for the current session and input to the machine-learning algorithm.

Abstract: The subject disclosure is directed towards providing data for augmenting an entity-attribute-related task. Pre-processing is preformed on entity-attribute tables extracted from the web, e.g., to provide indexes that are accessible to find data that completes augmentation tasks. The indexes are based on both direct mappings and indirect mappings between tables. Example augmentation tasks include queries for augmented data based on an attribute name or examples, or finding synonyms for augmentation. An online query is efficiently processed by accessing the indexes to return augmented data related to the task.

Abstract: Embodiments of the invention provide methods and apparatus for recommending items from a catalog of items to users in a population of users by generating trait vectors that represent items in the catalog responsive to explicit and/or implicit preference data for a group of less than all the users and using the trait vectors to recommend items to users in the population that are not in the group.

Abstract: Methods and apparatus for bot detection using profile based filtration are disclosed. A statistical profile describing attributes of automated-origin content request activity for a network content provider is built. A plurality of content requests of unknown origin in terms of similarity to the attributes is scored. A likelihood of automated-origin content request activity based on the scoring is indicated.

Abstract: Systems, methods, and apparatuses are disclosed for presenting applications to a user, via a mobile wireless communication device (user equipment), that are selected and ranked based on context information describing a location and type of motion of the user equipment, and/or a time that the ranking request was made, compared to context information describing the applications.

Abstract: Methods, systems, and subsystems for identifying and accessing multimedia content are provided. In one embodiment, a system is disclosed for identifying and accessing video files from a network based on information about contents of the video files. The system includes instructions stored on computer readable media, and the instructions perform the following steps when executed by a processor: (a) automatically entering subject matter data from the network into an encyclopedic database; (b) automatically distilling data from the encyclopedic database to create a user library content file; (c) allowing multiple clients to search data in the user library content file to identify at least one video file on the network and to access the at least one video file on the network using at least one reference file; (d) restricting the clients from accessing the encyclopedic database; and (e) restricting search results based on profile settings for each of the clients.

Abstract: Methods, systems, and computer-storage media having computer-usable instructions embodied thereon for identifying related entities are provided. One or more entities may be identified from a search query. The one or more entities may include any identifiable term having related information associated therewith. An entity store may be referenced to identify one or more related entities related to the entity. The one or more related entities, along with their relationship(s) to the entity (and one another, perhaps) may then be ranked and displayed to a user.