SAWSDL-MX2: A Machine-Learning Approach for Integrating Semantic Web Service Matchmaking Variants

  • Authors:
  • Matthias Klusch;Patrick Kapahnke;Ingo Zinnikus

  • Affiliations:
  • -;-;-

  • Venue:
  • ICWS '09 Proceedings of the 2009 IEEE International Conference on Web Services
  • Year:
  • 2009

Quantified Score

Hi-index 0.00

Visualization

Abstract

In this paper, we present SAWSDL-MX2, a hybrid semantic Web service matchmaker for SAWSDL services. Building on our initial work in \cite{Klu_Kap_08}, we adopt logic-based as well astext similarity service selection for model references and add a structural approach from \cite{Zin_Rup_Fis_06}, which operates on the pure syntactic description of WSDL elements. The integration of these matching variants is accomplished using a Support Vector Machine (SVM) with non-linear kernel, thus automatically adapting an aggregation function based on previously experienced training data. Results of our performance evaluation based on the standard measures recall and precision over the SAWSDL-TC1 test collection as well as an exhaustive example for all basic matching variants are also given.