Proceedings of the AAAI Spring Symposium on AI Technologies for Homeland Security
On Homeland Security and the Semantic Web: A Provenance and Trust Aware Inference Framework
March 21, 2005
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 the trustworthiness of discovered semantic associations and to make the discovery process effective and efficient.
InProceedings
AAAI Press
AAAI
Downloads: 4614 downloads
Google Scholar Citations: 32 citations
Assertions
- (Publication) On Homeland Security and the Semantic Web: A Provenance and Trust Aware Inference Framework has resource (Resource) SEMDIS poster (March 2005)