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Adaptive Hybrid Semantic Selection of SAWSDL Services with SAWSDL-MX2

Author

Listed:
  • Matthias Klusch

    (German Research Center for Artificial Intelligence (DFKI), Germany)

  • Patrick Kapahnke

    (German Research Center for Artificial Intelligence (DFKI), Germany)

  • Ingo Zinnikus

    (German Research Center for Artificial Intelligence (DFKI), Germany)

Abstract

In this paper, the authors present an adaptive, hybrid semantic matchmaker for SAWSDL services, called SAWSDL-MX2. It determines three types of semantic matching of an advertised service with a requested one, which are described in standard SAWSDL: logic-based, text-similarity-based and XML-tree edit-based structural similarity. Before selection, SAWSDL-MX2 learns the optimal aggregation of these different matching degrees off-line over a random subset of a given SAWSDL service retrieval test collection by exploiting a binary support vector machine-based classifier with ranking. The authors present a comparative evaluation of the retrieval performance of SAWSDL-MX2.

Suggested Citation

  • Matthias Klusch & Patrick Kapahnke & Ingo Zinnikus, 2010. "Adaptive Hybrid Semantic Selection of SAWSDL Services with SAWSDL-MX2," International Journal on Semantic Web and Information Systems (IJSWIS), IGI Global, vol. 6(4), pages 1-26, October.
    • Handle: RePEc:igg:jswis0:v:6:y:2010:i:4:p:1-26
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