Semantic Association Identification and Knowledge Discovery for National Security Applications

Semantic Association Identification and Knowledge Discovery for National Security Applications

Amit Sheth (University of Georgia, USA & Semagix, Inc., USA), Boanerges Aleman-Meza (University of Georgia, USA), I. Budak Arpinar (University of Georgia, USA), Clemens Bertram (Semagix, Inc., USA), Yashodhan Warke (Semagix, Inc., USA), Cartic Ramakrishanan (University of Georgia, USA), Chris Halaschek (University of Georgia, USA), Kemafar Anyanwu (University of Georgia, USA), David Avant (Semagix, Inc., USA), F. Sena Arpinar (Semagix, Inc., USA) and Krys Kochut (University of Georgia, USA)
Copyright: © 2005 |Pages: 21
DOI: 10.4018/jdm.2005010103
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Abstract

Public and private organizations have access to a vast amount of internal, deep Web and open Web information. Transforming this heterogeneous and distributed information into actionable and insightful information is the key to the emerging new classes of business intelligence and national security applications. Although the role of semantics in search and integration has been often talked about, in this paper we discuss semantic approaches to support analytics on vast amounts of heterogeneous data. In particular, we bring together novel academic research and commercialized Semantic Web technology. The academic research related to semantic association identification is built upon commercial Semantic Web technology for semantic metadata extraction. A prototypical demonstration of this research and technology is presented in the context of an aviation security application of significance to national security.

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