Semantic Web Service Clustering for Efficient Discovery Using an Ant-Based Method

  • Cristina Bianca Pop
  • Viorica Rozina Chifu
  • Ioan Salomie
  • Mihaela Dinsoreanu
  • Tudor David
  • Vlad Acretoaie
Part of the Studies in Computational Intelligence book series (SCI, volume 315)

Abstract

This paper presents an ant-inspired method for clustering semantic Web services. The method considers the degree of semantic similarity between services as the main clustering criterion. To measure the semantic similarity between two services we propose a matching method and a set of metrics. The proposed metrics evaluate the degree of match between the ontology concepts describing two services. We have tested the ant-inspired clustering method on the SAWSDL-TC benchmark and we have evaluated its performance using the Dunn Index, the Intra-Cluster Variance metric and an original metric we introduce in this paper.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Cristina Bianca Pop
    • 1
  • Viorica Rozina Chifu
    • 1
  • Ioan Salomie
    • 1
  • Mihaela Dinsoreanu
    • 1
  • Tudor David
    • 1
  • Vlad Acretoaie
    • 1
  1. 1.Department of Computer ScienceTechnical University of Cluj-NapocaCluj-NapocaRomania

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