Abstract: The present teaching relates to identifying related content and significance thereof with respect to some specified goal. Initial content is obtained based on a specified goal. Associated content is identified based on the semantics of the initial content and semantic-based temporal information. Different temporal relations are determined based on the specified goal and are extracted from content comprising the initial and associated content. With respect to each extracted temporal relation, determine a semantic analysis to be performed based on the specified goal. A summary is automatically generated for each of the semantic analysis results and is visualized to reveal semantic and temporal relations among different related content pieces. The visualization can be adjusted according to user input.

Abstract: The present teaching relates to method, system, medium, and implementations for modeling an entity based on textual information. When information about an entity to be modeled is received, textual information related to the entity is searched, including a plurality of documents related to at least one aspect of the entity. First aggregated semantic models are obtained for the plurality of documents. Each first aggregated semantic model represents one of the plurality of documents and includes a semantic feature vector and a semantic signature. Such first aggregated semantic models are clustered into at least one group, each of which corresponds to one of the at least one aspect of the entity and includes a set of first aggregated semantic models representing semantics of documents related to the aspect of the entity.

Abstract: Methods, systems, and computer program products for analyzing one or more perceived or technical problems or proposed solutions, and proposing a result are disclosed. In accordance therewith, a query is received as an input, one or more documents that are most closely semantically related to the query are retrieved, a set of concept terms derived from each of the query and the retrieved semantically related documents is obtained, a list of generic Solution Prompts, each of which generic Solution Prompt thereof includes a placeholder for insertion of a word or phrase from the set of concept terms, is provided, and a morphological analysis is applied to combine the list of generic Solution Prompts with the obtained set of concept terms to create a list of Specific Solution Prompts.

Abstract: The present teaching relates to method and system for assessing semantic distance. A query is received and processed, by a document representation constructor, to obtain a first query representation. The query is then processed by a query representation constructor to obtain a second query representation. Based on the first and second query representations, a dynamic norm is determined. Based on the second query representation, a plurality of documents are identified as being related to the query and a semantic distance between the query and the plurality of documents is determined based on the dynamic norm.

Abstract: A computer-based apparatus for searching confidential documents, including a computer with a memory element and a processor to execute instructions stored in the memory to receive a confidential document and related non-confidential information from a source entity. The processor executes the instructions to: store the confidential document and non-confidential information in the memory element; and restrict access to the confidential document stored in the memory element to the source entity and a library entity only, or to the first source entity only. The processor executes the computer readable instructions to: receive a search request from a searching entity including a search parameter; identify the search parameter as being applicable to the confidential document; and transmit for access by the searching entity, the non-confidential information. The library entity is different from the source entity.

Abstract: A computer based method for monitoring innovation activity including: accumulating first metadata associated with a first plurality of intellectual knowledge files; extracting a first plurality of patterns from the first plurality of intellectual knowledge files; creating a first plurality of concept spaces, using rules-based processing, the first metadata, and the first patterns; grouping, using rules-based processing, the first metadata, and the first plurality of patterns, the first plurality of intellectual knowledge files into first respective concept spaces in the first plurality of concept spaces; and generating a report, the report correlating the first plurality of intellectual knowledge files and the first respective concept spaces. The steps of accumulating, extracting, creating, grouping, and generating are performed by a general-purpose computer specially programmed to perform the steps of accumulating, extracting, creating, grouping, and generating.