375 results about "Semantic network" patented technology

Electronic data files are broadly characterized as “messages” and a social network is constructed by analyzing one or more messages exchanged between various entities. Additionally, messages from structured and/or unstructured data stores are correlated using one or more common/related data elements from two or more messages. Further, the social network and the concepts contained in the exchanged messages (i.e. semantic network) can be visualized using a series of multi-aspect viewing tools. Finally, in conjunction with the social network and the semantic network, a message network based on the chronological relationship of the messages (event network) can be constructed to analyze and visualize how the messages relate to each other in a time-based reference model. Once visualized, the relationship of the concepts contained in the messages as well as the relationship between the entities and the timing involved in the exchange of messages can be analyzed for desired information.

A method and system for automatically extracting relations between concepts included in electronic text is described. Aspects the exemplary embodiment include a semantic network comprising a plurality of lemmas that are grouped into synsets representing concepts, each of the synsets having a corresponding sense, and a plurality of links connected between the synsets that represent semantic relations between the synsets. The semantic network further includes semantic information comprising at least one of: 1) an expanded set of semantic relation links representing: hierarchical semantic relations, synset/corpus semantic relations verb/subject semantic relations, verb/direct object semantic relations, and fine grain/coarse grain semantic relationship; 2) a hierarchical category tree having a plurality of categories, wherein each of the categories contains a group of one or more synsets and a set of attributes, wherein the set of attributes of each of the categories are associated with each of the synsets in the respective category; and 3) a plurality of domains, wherein one or more of the domains is associated with at least a portion of the synsets, wherein each domain adds information regarding a linguistic context in which the corresponding synset is used in a language. A linguistic engine uses the semantic network to performing semantic disambiguation on the electronic text using one or more of the expanded set of semantic relation links, the hierarchical category tree, and the plurality of domains to assign a respective one of the senses to elements in the electronic text independently from contextual reference.

A method and system for automatic data categorization in response to a user query. A document set is retrieved in response to the user query. A semantic parser parses the document set and produces semantic term-groups by parsing a semantic network of nodes. A seed ranker produces a plurality of advantageously spaced semantic seeds based on the semantic term-groups. A category accumulator stores the advantageously spaced semantic seeds. The semantic network of nodes is augmented with the advantageously spaced semantic seeds.

Methods and apparatus for analyzing tasks performed by computer users by (i) gathering usage data, (ii) converting logged usage data into a uniform format, (iii) determining or defining task boundaries, and (iv) determining a task analysis model by "clustering" similar tasks together. The task analysis model may be used to (i) help users complete a task (such help, for example, may be in the form of a gratuitous help function), and/or (ii) to target marketing information to users based on user inputs and the task analysis model. The present invention also provides a uniform semantic network for representing different types of objects in a uniform way.

The autonomous avatar driver is useful in association with language sources. A sourcer may receive dialog from the language source. It may also, in some embodiments, receive external data from data sources. A segmentor may convert characters, represent particles and split dialog. A parser may then apply a link grammar, analyze grammatical mood, tag the dialog and prune dialog variants. A semantic engine may lookup token frames, generate semantic lexicons and semantic networks, and resolve ambiguous co-references. An analytics engine may filter common words from dialog, analyze N-grams, count lemmatized words, and analyze nodes. A pragmatics analyzer may resolve slang, generate knowledge templates, group proper nouns and estimate affect of dialog. A recommender may generate tag clouds, cluster the language sources into neighborhoods, recommend social networking to individuals and businesses, and generate contextual advertising. Lastly, a response generator may generate responses for the autonomous avatar using the analyzed dialog. The response generator may also incorporate the generated recommendations.

Methods and apparatus for analyzing tasks performed by computer users by (i) gathering usage data, (ii) converting logged usage data into a uniform format, (iii) determining or defining task boundaries, and (iv) determining a task analysis model by "clustering" similar tasks together. The task analysis model may be used to (i) help users complete a task (such help, for example, may be in the form of a gratuitous help function), and/or (ii) to target marketing information to users based on user inputs and the task analysis model. The present invention also provides a uniform semantic network for representing different types of objects in a uniform way.

Methods and apparatus for analyzing tasks performed by computer users by (i) gathering usage data, (ii) converting logged usage data into a uniform format, (iii) determining or defining task boundaries, and (iv) determining a task analysis model by "clustering" similar tasks together. The task analysis model may be used to (i) help users complete a task (such help, for example, may be in the form of a gratuitous help function), and/or (ii) to target marketing information to users based on user inputs and the task analysis model. The present invention also provides a uniform semantic network for representing different types of objects in a uniform way.

User authentication apparatus controlling access to systems, inputs owner's login name and password and then extracts the owner's timing vectors from keystroke characteristics with which the owner forms a training set. A semantic network uses multiple links to indicate that different pattern components of user's behavioral access create different kinds of relationships and “symbolic representations”. A neural network is trained by using each of the owner's timing vectors in the training set as an input. When a user inputs the owner's login name and password, it's checked and the user's timing vector is extracted to type the user's password if checked and demoted in confidence level if otherwise. The user's timing vector is applied to neural network and difference between the input/output is compared with a predetermined threshold; and if the difference is greater than the threshold, is prohibited. Preferably this is aided by response time to personal questions.

Methods and apparatus for analyzing tasks performed by computer users by (i) gathering usage data, (ii) converting logged usage data into a uniform format, (iii) determining or defining task boundaries, and (iv) determining a task analysis model by "clustering" similar tasks together. The task analysis model may be used to (i) help users complete a task (such help, for example, may be in the form of a gratuitous help function), and/or (ii) to target marketing information to users based on user inputs and the task analysis model. The present invention also provides a uniform semantic network for representing different types of objects in a uniform way.

The invention belongs to the field of multimedia information retrieval and relates to a method for realizing thesaurus-based query expansion and sort in image retrieval. The method comprises a WordNet-based English word semantic similarity metric algorithm, a HowNet-based Chinese word semantic similarity metric algorithm, an expansion rule-based query expansion word selection and optimization algorithm and a retrieval result evaluation and optimization algorithm. In the method, an image search engine is improved by the relevant text processing method and the relevant semantic network dictionary; and the retrieval result is sorted through semantic expansion, user interaction and improved similarity measurement. Compared with the traditional method, the method has the advantages of high accuracy rate, high integrality and low space-time cost. The method has very important significance for performing high-efficiency image retrieval according to image high-layer semantic information and on the basis of a large-scale image data set, and has wide application value in the field of cross-linguistic and cross-media retrieval.

Methods and system for providing information selected from a large set of digital content to at least one user. One such method comprises receiving user context information associated with the at least one user and identifying or generating, using at least one processor executing stored program instructions, 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 at least one 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.

Methods and system of searching for content in a target set of content based on a reference set of content, a reference semantic network representing knowledge associated with the reference set of content, and a target semantic network representing knowledge associated with the target set of content. One such method comprises receiving a user-specified search query; obtaining, by using at least one processor executing stored program instructions, at least one concept semantically relevant to the user-specified search query by using the target semantic network and the reference semantic network; constructing a second search query by augmenting the first search query with one or more terms associated with the at least one obtained concept; providing, to the at least one user, content associated with search results obtained based at least in part on searching the target set of content by using the second search query, wherein any concept in the semantic network is represented by a data structure storing data associated with a node in the semantic network.

The present invention relates to methods and a system for providing at least one personal recommendation to a mobile device of a consumer, with regard to a predefined physical site, one of said method comprising: (a) providing a semantic network having a plurality of segmentation paths; (b) determining at least one segmentation path, within said plurality of segmentation paths, according to at least one predefined parameter, thereby giving rise to at least one relevant segmentation path, wherein each segmentation path is related to a predefined physical site and includes at least two interconnected nodes; (c) determining at least one personal recommendation according to said at least one relevant segmentation path; and (d) providing the at least one personal recommendation to a mobile device of the consumer.

A Domain Ontology Oriented Resource System (DOORS) and a Problem Oriented Registry of Tags And Labels (PORTAL) are infrastructure systems for resource metadata within a paradigm serving as a bridge between the original web and the semantic web. IRIS registers domain names while DNS publishes domain addresses with mapping of names to addresses for the original web. Analogously, PORTAL registers resource labels and tags while DOORS publishes resource locations and descriptions with mapping of labels to locations for the semantic web. They provide an analogous resource label system, semantic search applications, and the benefits of collaborative semantic networks. Advertising is supported in several ways. Businesses purchase the right to display their products or services in association with searches. Also, content providers accept placement of advertising. Ads are then selected for display based on the content displayed utilizing the invention to match service providers with advertisers.

A computer implemented method, data processing system, and computer program product for establishing document relevance by semantic network density. When a search query is received, one or more semantic networks are identified which contain nodes matching one or more terms in the search query. An edge density is determined for each node matching a term in the search query. A relevancy score is then calculated for each of the one or more semantic networks based on the edge densities of the nodes matching a term in the search query. Based on the relevancy score, the relevancy to the search query of a document associated with the one or more semantic networks may then be determined.

A method and computer program product for producing a concept semantic network (CSN) from an ontology. Each class, subclass, object, restriction, and property of the ontology is converted into a concept of the CSN. Each hierarchy in the ontology is converted to a concept hierarchy of the CSN.

A method embodied as a web application that enables the automated construction of project teams from profiles contained in data sources accessible through the World Wide Web. The data sources may include social networks, blogs, web pages, and postings on online discussion forums. The locations of these data sources are supplied by a system administrator (during configuration and maintenance) and by registered users of the web application. The web application allows the system administrator to create a set of templates describing the kinds of roles and skills required by the users of the web application. The web application identifies potential team members referenced in the information sources and constructs a semantic network describing the skill sets and team suitability of those potential team members. The web application allows a registered user to enter the roles and capabilities required for a project team they wish to create. Once the user has entered a description of their desired project team, the application automatically constructs candidate teams by analyzing the semantic network to identify appropriate candidate teams given constraints on roles and skills. Four methods for identifying teams from the semantic network are provided. The system then provides the user with a set of recommended team members. In an iterative process, the user adjusts constraints on the team member capabilities until a satisfactory team is identified. The web application allows the user to negotiate compensation with the selected team, and provides a web-based collaboration page that the user and team may use for communication and coordination.