Abstract: Embodiments disclose a method of obtaining relevancy scores for concepts found on a page of content. Methods disclosed rely on connectivity of concepts found in a page in relation to connectivity of the same concepts with other concepts in general, and the semantic relationships between the concepts found on a page to obtain relevancy of concepts.

Abstract: Data structures, systems, methods and computer program products that enable precise information retrieval and extraction, and thus facilitate relational and associative discovery are disclosed. The present invention utilizes a novel data structure termed a “Knowlet” which combines multiple attributes and values for relationships between concepts. While texts contain many re-iterations of factual statements, Knowlets record relationships between two concepts only once and the attributes and values of the relationships change based on multiple instances of factual statements, increasing co-occurrence or associations. The present invention's approach results in a minimal growth of the Knowlet space as compared to the text space and it thus useful where there is a vast data store, a relevant ontology/thesaurus, and a need for knowledge navigation and (relational, associative, and/or other) knowledge discovery.

Abstract: A system and method for ranking results derived from various analytical processes for a concept selector is disclosed. The method ranks the concepts extracted for information input to a concept selector by semantic mapping and contextual mapping techniques. Information is input to a concept selector. The concept selector may then analyze the input information to select list of matched synonyms, generate concept relationship maps, concept database maps for the matched concepts from its databases. In addition, content provided from the web page may also be analyzed by the concept selector for mapping the concepts. Further, obtained list of matched terms, keywords and concepts are sent to the ranking module for ranking the results. The ranking module may rank the results obtained based on pre-defined filtering techniques such as semantic rules, business rules and so on. The ranked results are output by the concept selector.

Abstract: Data structures, systems, methods and computer program products that enable precise information retrieval and extraction, and thus facilitate relational and associative discovery are disclosed. The present invention utilizes a novel data structure termed a “Knowlet” which combines multiple attributes and values for relationships between concepts. While texts contain many re-iterations of factual statements, Knowlets record relationships between two concepts only once and the attributes and values of the relationships change based on multiple instances of factual statements, increasing co-occurrence or associations. The present invention's approach results in a minimal growth of the Knowlet space as compared to the text space and it thus useful where there is a vast data store, a relevant ontology/thesaurus, and a need for knowledge navigation and (relational, associative, and/or other) knowledge discovery.

Abstract: Methods and computer program products utilizing a graphical user interface for navigating concepts found in data produced by intellectuals in a knowledge discovery process are disclosed. The present invention utilizes a graphical user interface and related facilities for enabling community-based contributions in identifying associations between concepts disclosed by intellectuals. The present invention's approach results in having concepts mapped to authors and tools for linking related concepts with groups of intellectuals and/or contributors.

Abstract: Systems, methods and computer program products for navigating concepts found in data produced by intellectuals in a knowledge discovery process are disclosed. The present invention utilizes data sources and facilities for enabling community-based contributions for identifying associations between concepts disclosed by intellectuals. The present invention's approach results in having concepts mapped to authors and tools for linking related concepts with groups of intellectuals and/or contributors.

Abstract: Data structures, systems, methods and computer program products that enable precise information retrieval and extraction, and thus facilitate relational and associative discovery are disclosed. The present invention utilizes a novel data structure termed a “Knowlet” which combines multiple attributes and values for relationships between concepts. While texts contain many re-iterations of factual statements, Knowlets record relationships between two concepts only once and the attributes and values of the relationships change based on multiple instances of factual statements, increasing co-occurrence or associations. The present invention's approach results in a minimal growth of the Knowlet space as compared to the text space and it thus useful where there is a vast data store, a relevant ontology/thesaurus, and a need for knowledge navigation and (relational, associative, and/or other) knowledge discovery.