Information DiscovEry Assistant that Learns (IDEAL)

Award Information
Agency: Department of Defense
Branch: Navy
Contract: N00014-12-C-0600
Agency Tracking Number: N112-152-1304
Amount: $482,560.00
Phase: Phase II
Program: SBIR
Awards Year: 2012
Solicitation Year: 2011
Solicitation Topic Code: N112-152
Solicitation Number: 2011.2
Small Business Information
Knowledge Based Systems, Inc.
1408 University Drive East, College Station, TX, -
DUNS: 555403328
HUBZone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 Perakath Benjamin
 Senior Research Scientist
 (979) 260-5274
 pbenjamin@kbsi.com
Business Contact
 Donielle Mayer
Title: Business Operations Manag
Phone: (979) 260-5274
Email: dmayer@kbsi.com
Research Institution
 Stub
Abstract
Knowledge Based Systems, Inc. (KBSI) proposes to establish innovative enabling methods that target the challenge of semantic information analysis to facilitate iterative and adaptive discovery of information content associated with imprecisely specified information needs. The resulting new technology is expected to empower analysts working on complex intelligence tasks by dynamically forming collaborative research groups of individuals who are currently investigating similar issues, while requiring minimal or no direct input from each analyst with respect to the goals of their current mission. KBSI proposes to design, build, and validate an Information DiscovEry Assistant that Learns (IDEAL) solution that addresses the challenges described above. IDEAL will be designed to provide the following advanced capabilities (1) perform semantic search across multiple data sources to discover data that is relevant to an analyst"s goals and tasks; (2) progressively refine the quality of information produced through iterative semantic search and knowledge discovery; (3) facilitate dynamic information sharing and collaboration by a group of human agents; and (4) provide learning and adaptation by using the results and analyst feedback from the previous search/analysis activities to incrementally refine the semantic mapping and search models over extended time.

* information listed above is at the time of submission.

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