MetaCORE: Metadata automated Categorization and Optimized Relevance Exploration

Award Information
Agency:
Department of Defense
Branch
Air Force
Amount:
$735,579.00
Award Year:
2007
Program:
SBIR
Phase:
Phase II
Contract:
FA8750-07-C-0057
Award Id:
79144
Agency Tracking Number:
F061-059-1336
Solicitation Year:
n/a
Solicitation Topic Code:
n/a
Solicitation Number:
n/a
Small Business Information
12 Gill Street, Suite 1400, Woburn, MA, 01801
Hubzone Owned:
N
Minority Owned:
N
Woman Owned:
N
Duns:
967259946
Principal Investigator:
Paul Allopenna
Cognitive Psychologist
(781) 935-3966
pallopenna@aptima.com
Business Contact:
Margaret Clancy
Chief Financial Officer
(781) 496-2424
clancy@aptima.com
Research Institution:
n/a
Abstract
To support net-centric warfare, the Air Force must automate the generation and maintenance of metadata about both new and legacy information products. Metadata will enable Warfighters to retrieve necessary information quickly enough for accelerated ops tempos from among the rapidly increasing number of accessible information products. The metadata must include standard, domain-defined, user-generated, and automatically-generated attributes. We will build the MetaCORE (Metadata automated Categorization and Optimized Relevance Exploration) application as a complete metadata system architecture that can automatically populate a central repository with metadata mined from new and non-standardized legacy information products. A key advantage of MetaCORE is that all metadata will be stored in RDF, a next generation web standard accompanied by a powerful query language that provides greater functionality over other metadata storage formats. The modular MetaCORE system will enable the creation, filtering, retrieval and discovery of metadata using best-of-breed technology. Foremost among the technology that we will initially use to ensure that MetaCORE can achieve the most difficult task of discovering meta-data types and populating textually related metadata such as categories and keywords are Probabilistic Latent Semantic Analysis (PLSA) and Probabilistic Support Vector Machines (PSVM).

* information listed above is at the time of submission.

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