Knowledge Engineering Environment for Army Intelligence Analysis and Interpretation

Award Information
Agency:
Department of Defense
Branch
Army
Amount:
$69,880.00
Award Year:
2004
Program:
SBIR
Phase:
Phase I
Contract:
W15P7T-04-C-G402
Agency Tracking Number:
A032-3181
Solicitation Year:
2003
Solicitation Topic Code:
A03-094
Solicitation Number:
2003.2
Small Business Information
CYCORP, INC.
3721 Executive Center Drive, Suite 100, Austin, TX, 78731
Hubzone Owned:
N
Socially and Economically Disadvantaged:
N
Woman Owned:
N
Duns:
883906273
Principal Investigator:
Michael Witbrock
VP Res. & Dir. Knowledge
(512) 514-2951
witbrock@cyc.com
Business Contact:
Mary Shepherd
Sr. VP Finance and Admini
(512) 342-4002
mary@cyc.com
Research Institution:
n/a
Abstract
Traditional methods for constructing knowledge-intensive systems have relied heavily on intervention from artificial intelligence specialists. The first step in this intervention is typically either: extensive human-directed interviews of subject-matter experts so that the knowledge can then be laboriously hand-encoded; or the training of SMEs in some highly-restricted intermediate representation. Such systems have been costly to produce, and have typically failed to model expert knowledge to any degree of complexity outside of very narrow domains. This failure has been a major obstacle to the development of systems that harness human reasoning with a computer's tireless attention to detail. We propose to investigate why knowledge engineers need to be in the loop, and provide requirements and high-level design to addresses many of these problems. Our focus will be on interfaces that operate in the SME's domain of discourse. As a concrete example, we will be looking at a mixed graphical/textual representation of the intelligence analysis process whereby complex rules can be expressed as simple questions in a context inherited from the workflow. Our experimentation to date has found that this representation is not only very intuitive for SMEs, but is also highly productive in comparison to more conventional rule-construction methods.

* information listed above is at the time of submission.

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