Vagueness in Description Logic Programs for the Semantic Web

This paper is directed towards an infrastructure for handling both uncertainty and vagueness in the Rules, Logic, and Proof layers of the Semantic Web. More concretely, we present probabilistic fuzzy description logic programs, which combine fuzzy description logics, fuzzy logic programs (with stratified nonmonotonic negation), and probabilistic uncertainty in a uniform framework for the Semantic Web. We define important concepts dealing with both probabilistic uncertainty and fuzzy vagueness, such as the expected truth value of a crisp sentence and the probability of a vague sentence. We then provide algorithms for query processing in probabilistic fuzzy description logic programs, and we also delineate a special case where query processing has a polynomial data complexity. Furthermore, we describe a shopping agent example, which gives evidence of the usefulness of probabilistic fuzzy description logic programs in realistic web applications. 1Dipartimento di Informatica e Sistemistica, Sapienza Università di Roma, Via Salaria 113, I-00198 Rome, Italy; e-mail: [email protected]. Institut für Informationssysteme, Technische Universität Wien, Favoritenstraße 9-11, A-1040 Vienna, Austria; e-mail: [email protected]. 2ISTI-CNR, Via G. Moruzzi 1, I-56124 Pisa, Italy; e-mail: [email protected]. Acknowledgements: This work has been partially supported by a Heisenberg Professorship of the German Research Foundation (DFG). Copyright © 2007 by the authors INFSYS RR 1843-07-02 I