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Contribution to Book
Semantic Analytics in Intelligence: Applying Semantic Association Discovery to Determine Relevance of Heterogeneous Documents
Advanced Topics in Database Research
  • Boanerges Aleman-Meza
  • Amit P. Sheth, Wright State University - Main Campus
  • Devanand Paliniswami
  • Matthew Eavenson
  • I. Budak Arpinar
Document Type
Book Chapter
Publication Date
1-1-2005
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Abstract

We describe an ontological approach for determining the relevance of documents based on the underlying concept of exploiting complex semantic relationships among real-world entities. This research builds upon semantic metadata extraction and annotation, practical domain-specific ontology creation, main-memory query processing, and the notion of semantic association. A prototype application illustrates the approach by supporting the identification of insider threats for document access. In this scenario, we describe how investigative assignments performed by intelligence analysts are captured into a context of investigation by including concepts and relationships from the ontology. A relevance measure for documents is computed using semantic analytics techniques. Additionally, a graph-based visualization component allows exploration of potential document access beyond the ‘need to know’. We also discuss how a commercial product using Semantic Web technology, Semagix Freedom, is used for metadata extraction when designing and populating an ontology from heterogeneous sources.

DOI
10.4018/978-1-59140-935-9.ch020
Citation Information
Boanerges Aleman-Meza, Amit P. Sheth, Devanand Paliniswami, Matthew Eavenson, et al.. "Semantic Analytics in Intelligence: Applying Semantic Association Discovery to Determine Relevance of Heterogeneous Documents" Advanced Topics in Database Research Vol. 5 (2005) p. 401 - 419 ISSN: 9781591409359
Available at: http://works.bepress.com/amit_sheth/211/