On Homeland Security and the Semantic Web: A Provenance and Trust Aware Inference Framework
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2005
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Abstract
Discovering and evaluating interesting patterns and semantic
associations in vast amount of information provided by many
different sources is an important and time-consuming work
for homeland security analysts. By publishing or converting
such information in semantic web language, intelligent
agents can automate the inference without compromising the
semantics. This paper describes how trust and provenance
can be represented/obtained in the Semantic Web and then be
used to evaluate trustworthiness of discovered semantic associations
and to make discovery process effective and efficient.