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Article
Semantic Association Identification and Knowledge Discovery for National Security Applications
Journal of Database Management
  • Amit P. Sheth, Wright State University - Main Campus
  • Boanerges Aleman-Meza
  • Ismailcem Budak Arpinar
  • Chris Halaschek
  • Cartic Ramakrishnan, Wright State University - Main Campus
  • Clemens Bertram
  • Yashodhan Warke
  • David Avant
  • F. Sena Arpinar
  • Kemafor Anyanwu
  • Krzysztof J. Kochut
Document Type
Article
Publication Date
1-1-2005
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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 meta data extraction. A prototypical demonstration of this research and technology is presented in the context of an aviation security application of significance to national security.

Citation Information
Amit P. Sheth, Boanerges Aleman-Meza, Ismailcem Budak Arpinar, Chris Halaschek, et al.. "Semantic Association Identification and Knowledge Discovery for National Security Applications" Journal of Database Management Vol. 16 Iss. 1 (2005) p. 33 - 53 ISSN: 10638016
Available at: http://works.bepress.com/amit_sheth/488/