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2011 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology
Semantic Filters in Intelligence Analysis
Lyon, France
August 22-August 27
ISBN: 978-0-7695-4513-4
It is a challenge to identify the relevant pieces for further intelligence analysis among a big chunk of data. Filters have been built to provide such a function in almost all the network traffic capture and analysis tools as well as signature-based intrusion detection systems. However, most filters only work on strings of words, numbers, and/or other symbols. This paper proposes a type of context-aware and semantically relevant filters. This proposal is built on the findings in ontological semantics [1]. A detailed case study is used to show the effectiveness and efficiency of this proposal. The result of this research indicates that a good filter for intelligence analysis should incorporate relevant linguistic theories, which can explain one major aspect of human intelligence at another level.
Index Terms:
Ontological semantics, filters, intelligence, analsysis
Citation:
Jim Q. Chen, "Semantic Filters in Intelligence Analysis," wi-iat, vol. 3, pp.265-268, 2011 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology, 2011
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