Abstract
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.
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Ragone, A., Straccia, U., Di Noia, T., Di Sciascio, E., Donini, F.M. (2007). Vague Knowledge Bases for Matchmaking in P2P E-Marketplaces. In: Franconi, E., Kifer, M., May, W. (eds) The Semantic Web: Research and Applications. ESWC 2007. Lecture Notes in Computer Science, vol 4519. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72667-8_30
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DOI: https://doi.org/10.1007/978-3-540-72667-8_30
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