Hybrid Adaptive Web Service Selection with SAWSDL-MX and WSDL-Analyzer

نویسندگان

  • Matthias Klusch
  • Patrick Kapahnke
  • Ingo Zinnikus
چکیده

In this paper, we present an adaptive, hybrid semantic matchmaker for SAWSDL services, called SAWSDL-MX2. It determines three kinds of semantic service similarity with a given service request, that are logic-based, text-based and structural similarity. In particular, the degree of structural service similarity is computed by the WSDL-Analyzer tool [12] by means of XMLS tree edit distance measurement, string-based and lexical comparison of the respective XML-based WSDL services. SAWSDL-MX2 then learns the optimal aggregation of these different matching degrees over a subset of a test collection SAWSDL-TC1 based on a binary support vector machine-based classifier. Finally, we compare the retrieval performance of SAWSDL-MX2 with a non-adaptive matchmaker variant SAWSDL-MX1 [1] and the straight forward combination of its logic-based only variant SAWSDL-M0 with WSDL-Analyzer.

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تاریخ انتشار 2009