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Semantic Matchmaking as Non-Monotonic Reasoning: A Description Logic Approach

Tommaso Di Noia, Eugenio Di Sciascio, Francesco M. Donini
Matchmaking arises when supply and demand meet in an electronic marketplace, or when agents search for a web service to perform some task, or even when recruiting agencies match curricula and job profiles. In such open environments, the objective of a matchmaking process is to discover best available offers to a given request. We address the problem of matchmaking from a knowledge representation perspective, with a formalization based on Description Logics. We devise Concept Abduction and Concept Contraction as non-monotonic inferences in Description Logics suitable for modeling matchmaking in a logical framework, and prove some related complexity results. We also present reasonable algorithms for semantic matchmaking based on the devised inferences, and prove that they obey to some commonsense properties. Finally, we report on the implementation of the proposed matchmaking framework, which has been used both as a mediator in e-marketplaces and for semantic web services discovery. 1.
Keywords: 2007 descriptionlogic matchmaking turruta-eswc2008
Journal of Artificial Intelligence Research 29, pages 269-307, 2007
@article{DiNoiaJAIR2007,
  author = {Di Noia, Tommaso and Di Sciascio, Eugenio and Donini, Francesco M.},
  journal = {Journal of Artificial Intelligence Research},
  pages = {269-307},
  title = {Semantic Matchmaking as Non-Monotonic Reasoning: A Description Logic Approach},
  volume = 29,
  year = 2007,
  keywords = {2007 descriptionlogic matchmaking turruta-eswc2008},
  abstract = {Matchmaking arises when supply and demand meet in an electronic marketplace, or when agents search for a web service to perform some task, or even when recruiting agencies match curricula and job profiles. In such open environments, the objective of a matchmaking process is to discover best available offers to a given request. We address the problem of matchmaking from a knowledge representation perspective, with a formalization based on Description Logics. We devise Concept Abduction and Concept Contraction as non-monotonic inferences in Description Logics suitable for modeling matchmaking in a logical framework, and prove some related complexity results. We also present reasonable algorithms for semantic matchmaking based on the devised inferences, and prove that they obey to some commonsense properties. Finally, we report on the implementation of the proposed matchmaking framework, which has been used both as a mediator in e-marketplaces and for semantic web services discovery. 1.}
}