A fuzzy matchmaking approach for Semantic Web Services with application to collaborative material selection

  • Authors:

  • Min Liu;Weiming Shen;Qi Hao;Junwei Yan;Li Bai

  • Affiliations:

  • The Key Laboratory of Embedded System and Service Computing, Ministry of Education, School of Electronic and Information Engineering, Tongji University, Shanghai 200092, PR China and National Rese ...;The Key Laboratory of Embedded System and Service Computing, Ministry of Education, School of Electronic and Information Engineering, Tongji University, Shanghai 200092, PR China and National Rese ...;National Research Council Canada, London, Ontario N6G 4X8, Canada;The Key Laboratory of Embedded System and Service Computing, Ministry of Education, School of Electronic and Information Engineering, Tongji University, Shanghai 200092, PR China;Shanghai Lixin University of Commerce, Shanghai 201620, PR China

  • Venue:
  • Computers in Industry
  • Year:
  • 2012

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Abstract

A critical step in the process of reusing existing WSDL-specified services for building web-based applications is the discovery of potentially relevant services. However, the category-based service discovery, such as UDDI, is clearly insufficient. Semantic Web Services, augmenting Web service descriptions using Semantic Web technology, were introduced to facilitate the publication, discovery, and execution of Web services at the semantic level. Semantic matchmaker enhances the capability of UDDI service registries in the Semantic Web Services architecture and it is able to recognize various degrees of matching for Web services. Based on the Semantic Web Service framework, semantic matchmaker, specification matching and probabilistic matching, this paper proposes a fuzzy matchmaking approach for Semantic Web Services to support a more automated and veracious service discovery process in collaborative manufacturing environments. In the proposed approach, the membership function is set up on the semantic information annotated on WSDL specification of a web service, and the similarity of service objects is evaluated by the similarity degree of service attributes. A collaborative material selection case study in the die casting process for thermoelectric fan housing is used to illustrate the proposed approach.