SEMDIS poster (March 2005)

Li Ding, Pranam Kolari, Anupam Joshi, and Yelena Yesha

March 17, 2005

128000 bytes

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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 SemanticWeb and then be used to evaluate trustworthiness of discovered semantic associations and to make discovery process effective and efficient.



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