SYSTEM AND METHOD FOR KNOWLEDGE RETRIEVAL, MANAGEMENT, DELIVERY AND PRESENTATION

• US 20120191716A1
• Filed: 06/24/2011
• Published: 07/26/2012
• Est. Priority Date: 06/24/2002
• Status: Abandoned Application

• Current Assignee: Nosa Omoigui
• Original Assignee: Nosa Omoigui
• Inventors: Omoigui, Nosa
• Application Number:
  US13/168,785
• Publication Number:
  US 20120191716A1
• Time in Patent Office: Days
• US Class Current: 707/740
• CPC Class Codes: H01L 27/14609 Pixel-elements with integrated switching, control, storage or amplification elements scanning details of imagers (circuitry of solid-state image sensors H04N25/00); circuitry of imagers H04N25/70
• CPC Class Codes: H01L 27/1463 Pixel isolation structures
• CPC Class Codes: H01L 27/14645 Colour imagers
• CPC Class Codes: H01L 27/14647 Multicolour imagers having a stacked pixel-element structure, e.g. npn, npnpn or MQW elements
• CPC Class Codes: H01L 31/035236 Superlattices; Multiple quantum well structures
• CPC Class Codes: Y02A 90/10 Information and communication technologies [ICT] supporting adaptation to climate change, e.g. for weather forecasting or climate simulation

Abstract

The present invention is directed to an integrated implementation framework and resulting medium for knowledge retrieval, management, delivery and presentation. The system includes a first server component that is responsible for adding and maintaining domain-specific semantic information and a second server component that hosts semantic and other knowledge for use by the first server component that work together to provide context and time-sensitive semantic information retrieval services to clients operating a presentation platform via a communication medium. Within the system, all objects or events in a given hierarchy are active Agents semantically related to each other and representing queries (comprised of underlying action code) that return data objects for presentation to the client according to a predetermined and customizable theme. This system provides various means for the client to customize and “blend” Agents and the underlying related queries to optimize the presentation of the resulting information.

Claims

1-2. -2. (canceled)

3. A system for knowledge retrieval, management, delivery and presentation, implemented on at least one computer capable of presenting at least one semantic relationship as part of a search result that presents at least one document in response to a query, the computer system comprising a computer storage medium having a plurality of computer software components embodied thereon, the computer software components comprising:

a knowledge indexing and classification component wherein information from both structured and unstructured information sources are semantically encoded to create a plurality of knowledge objects;

a knowledge integration component to perform the steps of;

creating a semantic network based on semantic associations between the plurality of knowledge objects having semantic encoded information;

hosting domain-specific, episodic and contextual information;

dynamically linking at least one knowledge object to domain-specific information creating a linkage network;

maintaining the semantic attributes and dynamic linkage network of knowledge objects in a data store;

a semantic query processing component to perform the steps of;

receiving at least one user input query for processing;

extracting at least one semantic query based on user input query;

inspecting the data store to determine at least one semantic relationship between the semantic query and the dynamically linked knowledge object in the linkage network based on one or more rules for determining the one semantic relationship;

semantically linking the semantic query with the dynamically linked knowledge object in the linkage network to create a relational node;

delivering a representation of the semantically linked relational node based on the user query to a client according to customizable user preferences.

4. A method for creating a semantic network of knowledge objects in a computer memory capable of storing at least one knowledge object having schema and semantic links and hosting domain-specific semantic information used to classify and categorize domain-specific information;

evaluating a schema of a first knowledge object;

obtaining domain-specific semantic information from a memory related to the first knowledge object schema if the schema of the first knowledge object lacks a domain-specific meaning; and

creating a semantic link between the first knowledge object and the domain-specific semantic information if the schema of the first knowledge object suggests association with domain-specific information.

5. A method for searching data products stored on a computer readable medium, implemented on at least one computer comprising:

building a natural language relationship of a plurality of data products forming a semantic linkage map, further comprising;

analyzing the text within the plurality of data products based on a series of predefined ontologies to determine at least one semantic concept, the semantic concept built from analysis of the language, word patterns, and a context of the text within each data product, the semantic concept containing text not found within the data product but inferentially related by connection in the semantic linkage map;

creating semantic metadata using the determined semantic concepts;

determining associations between the semantic metadata in the plurality of data products;

applying a semantic ranking to the semantic metadata;

indexing the ranked semantic metadata;

linking the ranked semantic metadata to create a linkage map receiving a search query of the built semantic linkage map further comprising;

analyzing the search query based on the series of predefined ontologies to determine at least one semantic concept in the search query based on at least one of a meaning and a context, the semantic concept containing text not found within the data product but inferentially related by connection in the semantic linkage map;

creating semantic metadata using the determined concepts;

comparing the semantic metadata to the indexed and ranked semantic metadata; and

displaying a list of data products in a rank order based on the compared semantic metadata.