Semantic Web Dog Food

Presented at: 4th European Semantic Web Conference (ESWC2007)

by Azzurra Ragone, Umberto Straccia, Tommaso Di Noia, Eugenio Di Sciascio, Francesco M. Donini

In this paper we propose an approach to semantic matchmaking that exploits various knowledge representation technologies to find most promising partners in peer-to-peer e-marketplaces. In particular we mix in a formal and principled way the semantic expressiveness of DLR-lite Logic Programs, fuzzy logic and utility theory. We adopt DLR-Lite Logic Programs to obtain a reasonable compromise between expressiveness and complexity to ensure the scalability of our approach to large e-marketplaces, and Fuzzy Logic to model logical specifications as soft constraints. Furthermore, fully exploiting the peer-to-peer paradigm, we consider in the matchmaking process preferences and corresponding utilities of both parties.

Keywords: DLR-Lite, Fuzzy Logic, P2P marketplace, Semantic matchmaking

Resource URI on the dog food server: http://data.semanticweb.org/conference/eswc/2007/paper-283

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