Adaptive Toolkit for Pattern Discovery (ATPD)

Award Information
Agency:
Department of Defense
Amount:
$99,998.00
Program:
SBIR
Contract:
FA8750-06-C-0148
Solitcitation Year:
2006
Solicitation Number:
2006.1
Branch:
Air Force
Award Year:
2006
Phase:
Phase I
Agency Tracking Number:
F061-066-2374
Solicitation Topic Code:
AF06-066
Small Business Information
KNOWLEDGE BASED SYSTEMS, INC.
1408 University Drive East, College Station, TX, 77840
Hubzone Owned:
N
Woman Owned:
N
Socially and Economically Disadvantaged:
N
Duns:
555403328
Principal Investigator
 Perakath Benjamin
 Senior Research Scientist
 (979) 260-5274
 pbenjamin@kbsi.com
Business Contact
 Donielle Mayer
Title: Business Operations Manager
Phone: (979) 260-5274
Email: dmayer@kbsi.com
Research Institution
N/A
Abstract
We propose to research, design, and demonstrate an Adaptive Toolkit for Pattern Discovery (ATPD). We propose a hybrid approach that combines emerging machine learning techniques with advanced rule based methods to (i) automate the discovery of complex system-of-systems data utilization patterns and (ii) apply the learned usage patterns to dynamically update the reference ontology models being used for enterprise integration applications. The proposed ATPD capability will be used to (a) monitor information use across systems, (b) discover usage patterns, (c) analyze patterns for potential new (and useful) concepts and relations, and (d) offer intelligent assistance to ontology modelers about the integration of newly learned ontology concepts into the evolving reference ontology models. The Phase I effort will (i) establish ATPD requirements, (ii) design the ATPD architecture, and (iii) build and demonstrate a prototype ATPD. The ATPD methods and tools will be incrementally evaluated with test data and application scenarios at the 45th Space Wing, Cape Canaveral Air Force Station (CCAFS). The Phase II effort will harden the ATPD technology and build a focused and field-able ATPD application at 45th Space Wing, CCAFS.

* information listed above is at the time of submission.

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