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Leadership Agent for Multi-source Information Fusion in Counter-Terrorism

Award Information
Agency: Department of Defense
Branch: Army
Contract: W74V8H-04-P-0106
Agency Tracking Number: O032-2038
Amount: $99,869.00
Phase: Phase I
Program: SBIR
Solicitation Topic Code: OSD03-030
Solicitation Number: 2003.2
Timeline
Solicitation Year: 2003
Award Year: 2004
Award Start Date (Proposal Award Date): 2004-02-02
Award End Date (Contract End Date): 2005-08-02
Small Business Information
3721 Executive Center Drive, Suite 100
Austin, TX 78731
United States
DUNS: 883906273
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Michael Witbrock
 VP Research & Dir. Know.
 (512) 514-2951
 witbrock@cyc.com
Business Contact
 Mary Shepherd
Title: Sr. VP Finance and Admini
Phone: (512) 342-4002
Email: mary@cyc.com
Research Institution
N/A
Abstract

Current document search techniques are inadequate to handle queries whose answer requires establishing links among a number of (potentially obscure) facts. We propose to remedy this situation with a prototype system that applies statistical and knowledge-based methods to the problem of identifying chains of connections between terms and entities. We will extend existing predictive annotation methods for indexing entities by tagging them with Cyc concepts. In addition, our system will be capable of indexing entire facts, by applying Cyc's parsers to text sentences. Parsing a sentence into the CycL representation language results in a full semantic translation, so links among entities mentioned in a sentence will be transparent in the CycL representation. We propose also to demonstrate the discovery of "anonymous" links, by using technology we developed during the ARDA AQUAINT project. This module, the Holistic Query Expansion Algorithm (HQEA), is designed to process a textual query and produce a set of pairwise highly-correlated terms that connect all the terms within the original query into a coherent topic. Finally, a user-feedback mechanism will be developed to refine the performance of the Cyc-based semantic annotators.

* Information listed above is at the time of submission. *

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