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Vague Knowledge Bases for Matchmaking in P2P E-Marketplaces

  • Azzurra Ragone
  • Umberto Straccia
  • Tommaso Di Noia
  • Eugenio Di Sciascio
  • Francesco M. Donini
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4519)

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.

Keywords

Description Logic Soft Constraint Hard Constraint Conjunctive Query Fuzzy Predicate 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer Berlin Heidelberg 2007

Authors and Affiliations

  • Azzurra Ragone
    • 1
  • Umberto Straccia
    • 2
  • Tommaso Di Noia
    • 1
  • Eugenio Di Sciascio
    • 1
  • Francesco M. Donini
    • 3
  1. 1.SisInf Lab - Politecnico di Bari, Via Re David, 200, I-70125, BariItaly
  2. 2.ISTI - CNR, Via G. Moruzzi 1, 56124 PisaItaly
  3. 3.Università della Tuscia, via San Carlo, 32, I-01100, ViterboItaly

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