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Proceedings Paper

Social network analysis realization and exploitation
Author(s): Jack H. Davenport; James J. Nolan
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Paper Abstract

Intelligence analysts demand rapid information fusion capabilities to develop and maintain accurate situational awareness and understanding of dynamic enemy threats in asymmetric military operations. The ability to extract meaning in relationships between people, objects, and locations from a variety of unstructured text datasets is critical to proactive decision making. Additionally, the ability to automatically cluster text documents about entities and discover connections between those documents allows the analyst to navigate an extremely large collection of documents. Analysts also demand a temporal understanding of the extracted relationships between entities and connections between documents. We describe approaches to automatically realize the social networks via concept extraction, relationship extraction, and document connection algorithms; we also describe approaches to exploit the network by visualizing the results to the analyst such that changes over time are evident.

Paper Details

Date Published: 15 May 2015
PDF: 9 pages
Proc. SPIE 9499, Next-Generation Analyst III, 949906 (15 May 2015); doi: 10.1117/12.2184173
Show Author Affiliations
Jack H. Davenport, Decisive Analytics Corp. (United States)
James J. Nolan, Decisive Analytics Corp. (United States)


Published in SPIE Proceedings Vol. 9499:
Next-Generation Analyst III
Barbara D. Broome; Timothy P. Hanratty; David L. Hall; James Llinas, Editor(s)

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