Context Based Data Abstraction

Award Information
Agency:
Department of Defense
Branch
Army
Amount:
$120,000.00
Award Year:
2010
Program:
SBIR
Phase:
Phase I
Contract:
W15P7T-10-C-B001
Agency Tracking Number:
A092-088-1486
Solicitation Year:
2009
Solicitation Topic Code:
A09-088
Solicitation Number:
2009.2
Small Business Information
DECISIVE ANALYTICS Corporation
1235 South Clark Street, Suite 400, Arlington, VA, 22202
Hubzone Owned:
N
Socially and Economically Disadvantaged:
N
Woman Owned:
N
Duns:
036593457
Principal Investigator:
Jonathan Day
Senior Engineer
(703) 414-5015
jonathan.day@dac.us
Business Contact:
Kelly McClelland
VP, Administration
(703) 414-5024
billingsj@wband.com
Research Institution:
n/a
Abstract
Conflicts in the world have shifted toward asymmetric warfare. As a result, the methodology for attaining situational awareness has been drastically altered as the number of variables directly impacting situational awareness (i.e. behavioral patterns and social networks), their rates of change, and the rate of data creation have dramatically increased. Providing commanders with only the most vital information has become a key challenge. Therefore, highly adaptive, automated, and flexible tools and systems are required that will provide solutions (i.e. actionable intelligence and situational awareness) on an ongoing basis. To address these issues, we propose the Automated Data Abstraction and Modeling (ADAM) system. ADAM is an automated approach that constructs abstract models for task completion backed by Bayesian Networks – predictive models capable of capturing and analyzing the impact of individual variables on the entire model. Each model will be focused on the completion of a specific task with the minimum amount of data required to ensure accurate results. ADAM will be domain agnostic and capable of producing a wide variety of models for the completion of highly specific tasks across any domain. These models will provide a highly adaptive, real-time analytic engine capable of reducing commanders’ and their staffs’ cognitive load.

* information listed above is at the time of submission.

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