Abstract: A mobile application is provided that provides intelligent recommendations based on the knowledge of where the user has been, and what venues the user would like to visit. Further, such an application may be capable of determining where people in a user's social network have been and what venue locations these related users would like to visit. Also, in another implementation, the application may be capable of determining where people with similar taste have been, and where they would like to go. Some or all of this information may be used by a mobile application that provides recommendations to a user. For instance, in one implementation, a user having a mobile device such as a cell phone wishes to locate a venue based on one or more parameters, and some or all of this information may be used to order to rank recommendations with the interface.

Abstract: In one example, a method includes receiving a query regarding a relationship among keywords, using one or more web search engines to identify highly ranked web pages related to the keywords and highly ranked ontologies related to the words, extracting semantics that are related to the keywords from the highly ranked web pages, combining the highly ranked ontologies and the extracted semantics to form an integrated ontology, identifying relationships that are related to the keywords from the integrated ontology, and ranking the relationships.

Abstract: Methods and system for providing information selected from a large set of digital content to a user. Techniques include receiving user context information associated with the user and identifying or generating a first concept in a semantic network, the first concept representing at least a portion of the user context information. The method further comprises obtaining at least one concept, including a second concept, semantically relevant to the first concept at least in part, by synthesizing the second concept based on the first concept and at least one other concept in the semantic network; and providing information to the user, wherein the information is selected by using the first concept and the at least one obtained concept semantically relevant to the first concept, wherein the first concept in a semantic network is represented by a data structure storing any data associated with a node in the semantic network.

Abstract: A mobile device for accessing information over a communication network using a keyword identifier. The mobile device comprises: i) transceiver circuitry configured to transmit information to, and receive information, from the communication network; ii) voice recognition circuitry configured to receive from a microphone of the mobile device a voice input spoken by a user of the mobile device and convert the voice input to a text string; and ii) a controller configured to determine if the text string includes a valid keyword identifier. In response to a determination that the text string includes a valid keyword identifier, the controller generates a query from the valid keyword identifier and transmits the query to a remote server. In response to a determination that the text string does not include a valid keyword identifier, the controller identifies in the text string at least one candidate keyword and at least one candidate domain name.

Abstract: A task-oriented search tool searches for one or more tasks related to a search term submitted via a computer-user interface. The task-oriented search tool displays search results that include a task related to the search term and a task-solving tool for performing the task related to the search term.

Abstract: Described is a system for supporting human intelligence analysis. The system detects changes in social relations among users within a dynamic information network and enables understanding of a current social situation in the dynamic information network through multiple integrated modules. An active network mining module identifies incomplete data that is related to at least one change in the social relations and resolves conflicting and missing data in the dynamic information network. A relevant network discovery module constructs a relevant network from hidden relations within the dynamic information network. An information-aware social network module constructs an information-aware social network using the relevant network, then classifies and prioritizes items of interest to provide an assessment of a current social situation to a user.

Abstract: An embodiment of the system and method for optimizing pattern query searches on a graph database uses a pattern query optimizer to optimize execution of the search plan for any sequence of SQL expressions by separating or breaking a pattern query into multiple subpattern queries before converting the subpattern queries into SQL expressions. An embodiment of the pattern query optimizer algorithmically, without intervention by an analyst, decomposes any pattern query into a set of subpattern queries by first identifying branches and cycles within a pattern query and then decomposing each identified branch and cycle into equivalent straight line paths, i.e., straight line nodes joined by edges. Cardinality may be used to improve the performance of pattern searches.

Abstract: A tool for targeting a message response. The tool monitors reactions of a user to message subject lines, message content, and social networks. The tool analyzes user interest data and calculates a user interest rating per keyword. Rated keywords are stored in association with the user. When a user drafts a message addressed to a recipient, the tool compares rated keywords within the recipient's log with the subject line and message content. The tool suggests an alternative subject line likely to elicit a faster and more detailed response from the recipient.

Abstract: An apparatus, system, and method are disclosed for cooperatively presenting multiple media signals via multiple presentation devices. Disclosed are apparatuses, systems and methods that integrate portions of multiple media signals and cooperatively present the portions via multiple media output devices.

Abstract: Technology is described for providing search results based on a search query. The method may include receiving the search query. A user interest based on the search query may also be identified. The user interest may be compared with currently trending interests. Interest items based on the currently trending interests that relate to the user interest may be identified.

Abstract: Embodiments are disclosed herein that relate to generating a decision tree through graphical processing unit (GPU) based machine learning. For example, one embodiment provides a method including, for each level of the decision tree: performing, at each GPU of the parallel processing pipeline, a feature test for a feature in a feature set on every example in an example set. The method further includes accumulating results of the feature tests in local memory blocks. The method further includes writing the accumulated results from each local memory block to global memory to generate a histogram of features for every node in the level, and for each node in the level, assigning a feature having a lowest entropy in accordance with the histograms to the node.

Abstract: Techniques are described herein that are capable of taking action upon users in a social networking system with respect to a purpose based on compatibility of the users to the purpose. The action may be further based on compatibility of the users and the purpose to a venue. Example actions include but are not limited to recommending users for a purpose and/or a venue; recommending a purpose for users and/or a venue; recommending a venue for users and/or a purpose; inviting users to join a group, to attend an event, or to perform an action; etc. For instance, the social networking system may include a network manager that performs a compatibility analysis with respect to attributes of users, a purpose, and/or a venue, respectively. The network manager may take an action upon the users (or a subset thereof) based on the results of the compatibility analysis.

Abstract: A system and method that improves obtaining similarity measure between concepts based on Latent Semantic Analysis by taking onto account graph structure derived from the knowledge bases by using a vector propagation algorithm, in the context domain, such as a medical domain. Concepts contained in a corpus of documents are expressed in a graph wherein each node is a concept and edges between node express relation between concepts weighted by the number of semantic relations determined from the corpus. A vector of neighbors is created and assigned to each concept, thereby providing an improved similarity measure between documents, i.e., corpus and query against corpus.

Abstract: Disclosed herein is technology for providing sentiment analysis of content items. The technology involves labeling one or more portions of a content item and having the content item analyzed for sentiment. A graphical user interface may accept inputs from a user that indicate a portion of the content item should be labeled and the use may provide an associated sentiment for the item, e.g., positive, negative, or neutral. When a user has labeled a portion of a content item and provided an associated sentiment, the label and the sentiment are stored in a data store and the content items in the data store may be re-analyzed the content item to reflect the user's labeling and the changes are displayed in near real-time in the user interface.

Abstract: A named entity input is received and a target sense for which the named entity input is to be extracted from a set of documents is identified. An extraction complexity feature is generated based on the named entity input, the target sense, and the set of documents. The extraction complexity feature indicates how difficult or complex it is deemed to be to identify the named entity input for the target sense in the set of documents.

Abstract: Techniques for analyzing and synthesizing complex knowledge representations (KRs) may utilize an atomic knowledge representation model including both an elemental data structure and knowledge processing rules stored as machine-readable data and/or programming instructions. One or more of the knowledge processing rules may be applied to analyze an input complex KR to deconstruct its complex concepts and/or concept relationships to elemental concepts and/or concept relationships to be included in the elemental data structure. One or more of the knowledge processing rules may be applied to synthesize an output complex KR from the stored elemental data structure in accordance with an input context. Multiple input complex KRs of various types may be analyzed and deconstructed to populate the elemental data structure, and input complex KRs may be transformed through the elemental data structure to output complex KRs of different types, providing semantic interoperability to KRs of different types and/or KR models.

Abstract: A method and system for automatically summarizing fine-grained opinions in digital text are disclosed. Accordingly, a digital text is analyzed for the purpose of extracting all opinion expressions found in the text. Next, the extracted opinion expressions (referred to herein as opinion frames) are analyzed to generate opinion summaries. In forming an opinion summary, those opinion frames sharing in common an opinion source and/or opinion topic may be combined, such that an overall opinion summary indicates an aggregate opinion held by the common source toward the common topic.

Abstract: A computer implemented method of constructing formal definitions in intelligent glossaries for interpreting text, comprising the steps of: providing at least one Distinction having a Boundary, an Indication, a Counter-indication and a Frame; modeling each Distinction as a diagram to provide a Distinction Model; verifying each distinction model as being an instantiation of a generic Distinction Pattern; providing at least one Arrangement made of nonintersecting Marks of Distinction containing Indications from the verified Distinction Model; writing at least one Formulation for each Indication appearing in verified Distinction model and Arrangement, providing well-founded Indications; calculating precise Formulations in Natural Language from well-founded Indications by substituting Variables symbols and/or replacing Constants symbols to transform imprecise Formulations into precise Formulations; selecting a Definition type and embedding at least one precise Formulation and Definition type as a formal Definition

Abstract: Enhancement of a first mind map to become a second enhanced mind includes: providing a content pool with information items; performing a first semantic scan based on a selected object; and generating a new object and a related connection to the selected object based on the semantic scan. Furthermore, the enhancement includes determining a strength value for each of the connections of the first mind map and determining the connection with the lowest strength value and recalculating the strength value using an external knowledge base to define the connection as obsolete if the strength value decreases.

Abstract: Computer-implemented systems and methods for synthesis of concept definitions and concept relationships from a domain of data, utilizing different semantic processing protocols such as formal concept analysis and faceted classification synthesis from existing domain concepts that have a confidence gradient built into them. A cognitive or an input agent provides an input of an active concept which is matched against existing domain concepts. The resultant pool of relevant domain concepts is then used to derive virtual concept definitions using a semantic processing protocol. The derivation is then overlaid with a concept of relative proximity of an attribute from another within an attribute set. An additional layer of coherence is given by the relative proximity measure. The end result is a pool of related virtual concept definitions in a tree structure.

Abstract: Techniques for identification of a broker-type leader in a social network based on network topology are described. According to various embodiments, an electronic sociograph is accessed, the electronic sociograph depicting a plurality of actors of an online social network service as nodes in the sociograph, and the sociograph including edges between the nodes representing relationships between the respective actors. Thereafter, a particular node in the sociograph corresponding to an information connector node between at least two distinct groups of the nodes in the sociograph is identified. A particular actor of the plurality of actors associated with the particular node is then classified as an information connector between at least two sub-networks of the actors of the online social network service.

Abstract: An adaptive probabilistic semantic computer-implemented system and method links semantic chains comprising subject, predicate, and object triples and an associated probability with behavioral-based chains comprising a system user, predicate, and object triples, and infers user preferences based on the linked chains. Recommendations are generated for delivery to system users based on the preference inferences. Explanations may be provided to recommendation recipients as to why they received recommendations, and the explanations may convey a sense of confidence in accordance with probabilistic semantic associations.

Abstract: A method of evaluating a semantic relatedness of terms. The method comprises providing a plurality of text segments, calculating, using a processor, a plurality of weights each for another of the plurality of text segments, calculating a prevalence of a co-appearance of each of a plurality of pairs of terms in the plurality of text segments, and evaluating a semantic relatedness between members of each the pair according to a combination of a respective the prevalence and a weight of each of the plurality of text segments wherein a co-appearance of the pair occurs.

Abstract: A four valued parallelized simulation with the ability to implement computer systems with the ability to combine a mixture of computer intensive techniques in DNA analysis and molecular crystallography. Disclosed systems and methods aid in the design of drugs, pharmaceutical research, genetically modified organisms and the detection of genetic sequences for gene therapy.

Abstract: Methods and systems may support conclusions of a clinician by enabling the clinician to arbitrarily define the symptoms according to the patient's record. The method may comprise: (a) determining a plurality of symptoms representing a patient and including characteristics of the patient, the symptoms being categorized as present symptoms, absent symptoms or open symptoms; (b) establishing a multi-tier relationship between said symptoms and a plurality of diseases based on a knowledge model; (c) adjusting weighting factor(s) for at least one multi-tier relationship based on said knowledge model; (d) optionally adjusting at least one weighting factor of step (c) by an expert; and (e) building a ranking of diseases from said multi-tier relationship based on said weighting factors. The method may provide an efficient ranking of disease information, thereby supporting a clinical diagnosis that may consider multiple symptoms while emphasizing particular symptoms in view of the clinician's expertise.

Abstract: Machine semantic perception is discussed. One example system can comprise an environmental knowledgebase (KB) associating features with properties, and an interface component receiving sensor data associated with observed properties. The KB and sensor observations can be encoded in bit-matrix and bit-vector representations, respectively, for efficient storage and computation. A perception component can perform semantic perception on observed properties based on the KB. The perception component can determine explanatory features associated with the observed properties through abductive reasoning, and determine discriminatory properties associated with the explanatory features through deductive reasoning. These can be executed in an iterative and interleaved Perception Cycle for efficient computation of minimum actionable explanations of observations.

Abstract: A processor-implemented method, system, and/or computer program product generate a recommendation to add a member to a receptivity cohort. A receptivity cohort is made up of members who share a conduct attribute, which is a facial expression, body language, and/or social interaction of a person. The conduct attribute has been predetermined to be an indicator of a level of receptiveness to a proposed future change in a set of circumstances. Biometric sensor data, which describe the facial expression, body language and/or social interaction for a candidate member, are retrieved from a set of biometric sensors. The retrieved biometric sensor data for the candidate member is compared to the conduct attribute of members of the receptivity cohort. In response to the biometric sensor data for the candidate member matching the conduct attribute of members of the receptivity cohort, a recommendation is generated to add the candidate member to the receptivity cohort.

Abstract: A method of maintaining data described in a plurality of data models. An ontology is used to describe the data models. The data models are managed using the ontology and using a validation schema to validate object(s) governed by the ontology and derived from data-centric component(s) of content that has a semantically independent structure. Management of the data models is neutral relative to implementation of the content.

Abstract: Computer-implemented systems and methods for synthesis of concept definitions and concept relationships from a domain of data, utilizing different semantic processing protocols such as formal concept analysis and faceted classification synthesis from existing domain concepts that have a confidence gradient built into them. A cognitive of an input agent provides an input of an active concept which is matched against existing domain concepts. The resultant pool of relevant domain concepts is then used to derive virtual concept definitions using a semantic processing protocol. The derivation is then overlaid with a concept of relative proximity of an attribute from another within an attribute set. An additional layer of coherence is given by the relative proximity measure. The end result is a pool of related virtual concept definitions in a tree structure.

Abstract: A method and system for providing instance information data of at least one instance. The method has the steps of generating a semantic representation of the instance on the basis of at least one instance data source, providing a semantic representation of a domain on the basis of at least one structured domain data source, performing an integration of the semantic instance and domain representations to provide an integrated semantic representation and deriving automatically instance information data from the provided integrated semantic representation. The method and system allow to provide efficiently instance information data of a wide range of instances with technical entities and persons, in a particular patients in different domains such as radiology or anatomy.

Abstract: A determination method includes: generating, when a logical formula is received, another statement group that shares either one of individual statements and one or plural statements of statement groups with each of the individual statements and statement groups that are included in the logical formula or a changed logical formula acquired with the performance of logically equivalent conversion with regard to the logical formula, the logical formula or the changed logical formula including a logical disjunction of the individual statements or the statement groups that are logical conjunctions of the one or plural statements; and performing a determination process of the logical formula, wherein the logical formula is determined as not satisfied when a determination result indicating that the statements that are included in the other statement group are not satisfied is obtained in the determination process.

Abstract: Exemplary embodiments of the present invention disclose a method, computer program product, and system for updating an ontology when a set of evidences and a set of constraints are given as inputs. Exemplary embodiments categorize concepts into three sets, a definitely relevant set, a possibly relevant set, and an irrelevant set. Exemplary embodiments store the concepts from the definitely relevant set in the ontology and the concepts from the possibly relevant set in a residual ontology. Exemplary embodiments match concepts in the set of evidences to the concepts in the ontology or the concepts in the residual ontology. Exemplary embodiments determine to enhance the strength of the existing concepts in the ontology or the existing concepts in the residual ontology. Exemplary embodiments determine to expand the ontology or the residual ontology. Exemplary embodiments remove the concepts from the ontology or the residual ontology utilizing the set of constraints.

Abstract: One or more systems and methods for knowledge pattern search from networked agents are disclosed in various embodiments of the invention. A system and a related method can utilizes a knowledge pattern discovery process, which involves analyzing historical data, contextualizing, conceptualizing, clustering, and modeling of data to pattern and discover information of interest. This process may involve constructing a pattern-identifying model using a computer system by applying a context-concept-cluster (CCC) data analysis method, and visualizing that information using a computer system interface. In one embodiment of the invention, once the pattern-identifying model is constructed, the real-time data can be gathered using multiple learning agent devices, and then analyzed by the pattern-identifying model to identify various patterns for gains analysis and derivation of an anomalousness score.

Abstract: The present invention envisages a personalized plan generation system and a method that satisfies maximum user preferences and constraints; besides including a number of enabling features like of plan repair or revision with dynamically changing situations or contextual information. Moreover, the system is able to perform a collaborative planning by opinion mining in social networks to achieve better optimization. Significantly, the explanation for the selection of plan steps or a change in plan altogether can be expressed in natural language.

Abstract: A computer-implemented method is provided for generating an ontology document, the method comprising inputting a domain description including information about items in the domain and relationships between the items; accessing a data structure and an operation structure, wherein the data structure is a domain-independent model of items and relationships between items, the data structure comprising at least progenitor items each able to contain only progeny items created by the progenitor item as a consequence of the progenitor item accepting an operation from the operation structure invoked against it, the operation structure also being domain-independent; and applying the data structure and the operation structure to the domain description to generate an ontology document for use in producing a software artifact.

Abstract: Methods and systems for forecasting a future event in an event stream are provided herein. The event stream includes a number of events, wherein each of the events includes an event label and an associated time stamp. The system includes a processor that is adapted to execute stored instructions and a system memory. The system memory includes code configured to generate one or more decision graphs for predicting events with event labels chosen from a number of event labels based on the events within the event stream, wherein the decision graph includes decision nodes and leaf nodes, and wherein each of the decision nodes includes a question. The system memory also includes code configured to analyze event stream data using the decision graph and forecast a future event in the event stream based on the analysis of the event stream data.

Abstract: A system and method for using semantic understanding in storing and searching data and other information. A linearized tuple-based version of a conceptual graph can be created from a user input. A plurality of conceptual graphs, or portions thereof, can be compared to determine matches. An associative database can be created and/or searched using a hierarchy of conceptual graphs in tuple format, so that the data storage and searching of such database is optimized. The associative database can be used to integrate data from multiple different sources; form part of an Internet or other search engine; or used in other implementations. Also disclosed herein is a system and method for use of semantic understanding in searching and providing of content is described herein.

Abstract: This invention relates generally to classification systems. More particularly this invention relates to a system, method, and computer program to dynamically generate a domain of information synthesized by a classification system or semantic network. The invention discloses a method, system, and computer program providing a means by which an information store comprised of knowledge representations, such as a web site comprised of a plurality of web pages or a database comprised of a plurality of data instances, may be optimally organized and accessed based on relational links between ideas defined by one or more thoughts identified by an agent and one or more ideas embodied by the data instances. Such means is hereinafter referred to as a “thought network”.

Abstract: Systems and methods of a knowledge management networking are disclosed here. In one aspect, embodiments of the present disclosure include a method, which may be implemented on a system, of hosting a web-space having a plurality of objects, the plurality of objects to include one or more of, representations of a set of users, a set of web-items, and a set of nets; wherein a net of the set of nets is a subset of the web-space comprising a sub-plurality of the plurality of objects.

Abstract: A computer environment includes an editor application enabling generation of a specification (e.g. a graphic description) defining attributes of a navigable semantic network. An example navigable semantic network as defined by the specification can include multiple resource nodes and corresponding links defining relationships amongst the resource nodes. In addition to defining nodes and relationships, the specification can define display rules, navigation rules, etc. associated with the navigable semantic network. The computer environment can further include a compiler, a view instantiation engine, and a presentation engine. The compiler compiles the specification into a semantic network model. The view instantiation engine instantiates different portions of a semantic network as defined by the semantic network model. The presentation engine initiates display of the instantiated portion of the semantic network.

Abstract: A method resolves ambiguous spotted entity names in a data corpus by determining an activation level value for each of a plurality of nodes corresponding to a single ambiguous entity name. The activation levels for each of the nodes may be modified by inputting outside domain knowledge corresponding to the nodes to increase the activation value of the nodes, spotting entity names corresponding to the nodes to increase the activation value of the nodes, searching the data corpus to spot newly posted entity names to increase the activation value of the nodes, and searching the data corpus to reduce or deactivate the activation value of the nodes by eliminating false positives. The ambiguous entity name is assigned to the node determined to have the highest activation level and is then outputted to a user.

Abstract: A computing device receives a rule that includes information describing conditions associated with a consequence, and identifies rule components corresponding to the rule. The computing device creates a rule formula, based on the rule components, by creating a first-order logic version of the rule and creating a rule formula table based on the first-order logic version of the rule. The computing device stores the rule formula table in a relational database.

Abstract: A method for modifying a mapping from at least one application path of a data system to a conceptual path of an ontology system is provided. The application path addresses a part of the structure of the data system, and the conceptual path addresses a part of the structure of the ontology system. The method comprises the steps detecting a change to a part of the structure of the ontology system one or more of the conceptual paths is addressing and updating the mappings to reflect the change to the part of the structure of the ontology system.

Abstract: The present invention is directed to a system that includes a semantic reasoning engine that is configured to convert radar track data into a directed graph representation (DGR) of the predetermined surveillance region and iteratively combine the DGRs to create a weighted directed graph (WDG) aligned and superimposed with the digital map data. The WDG includes first WDG elements corresponding to moving objects detected by a radar system. The WDG is compared to historical data to obtain a surveillance detection parameter. An alarm message is generated if the surveillance detection parameter deviates from the historical data by a predetermined amount. An output device is coupled to the semantic reasoning engine and is configured to provide a representation of the digital map data, the WDG and the at least one alarm message.

Abstract: Embodiments of the invention relate to systems, methods, and computer program products for providing a rewards program. The system, method, and computer program product are configured to determine that a customer has completed an action; determine that the customer has earned a reward based on the action; determine a category associated with the reward; and apply the reward to the category. In some situations, the categories are default categories provided by the financial institution. In other situations, the categories are defined by the customer. The system determines which category an earned award is routed into using a decision engine that evaluates the award and/or the action completed by the customer and compares the award and/or action to rules, such as default rules, custom rules, or dynamic rules. The categories may also include goals and the system assists in tracking customer's progress towards the goal.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for estimating demographic compositions of television audiences from audience similarities. In an aspect, pairwise cosine similarities of segment of viewers of rated and unrated television programs are determined, demographic information of rated programs is attributed to the unrated programs from the cosine similarity measures and demographic information for the rated programs.

Abstract: A system, method, and computer-readable medium, is described that finds similarities among programming applications based on semantic anchors found within the source code of such applications. The semantic anchors may be API calls, such as Java's package and class calls of the JDK. Latent Semantic Indexing may be used to process the application and semantic anchor data and automatically develop a similarity matrix that contains numbers representing the similarity of one program to another.

Abstract: A method for creating a predictive model is disclosed herein, including the steps of determining trends and patterns in electronic data, using at least a first machine language algorithm, refining the determination of the algorithm, searching for social models that describe the identified trends and patterns using at least a second machine language algorithm, verifying causal links, constructing at least one model about human node behavior and interactions, utilizing the social models to do at least one of the following: validate hypotheses, predict future behavior, and examine hypothetical scenarios, automatically updating predictions when new data is introduced, using probabilistic techniques to learn hierarchical structure in unstructured text, continuously updating a set of themes, examining grammatical rules of each component of text, matching grammatical constituents to semantic roles, and reorganizing data into clusters of entities with common attributes.

Abstract: A computer program product includes a storage medium with program code configured to maintain descriptions of a plurality of information technology resources in a computer-readable storage medium. The program code is configured to maintain a plurality of evaluation strategies. Responsive to detecting a command to change a first property of the set of properties of a first information technology resource of the plurality of information technology resources, the program code is configured to determine that a first of the evaluation strategies associates at least one of the plurality of rules with a form of the change to the first property of the first information technology resource. Also, responsive to detecting the command, the program code is configured to evaluate the at least one of the plurality of rules and performs the operation of the at least one rule.

Abstract: A method for populating a data system is provided. The method includes the step of mapping at least one application path of the data system to at least one conceptual path of an ontology system. The application path addresses parts of the structure of the data system, and the conceptual path addresses parts of the structure of the ontology system. The method further includes the step of automatically populating the data system at a location addressed by the application path with data values contained in the conceptual path.