A similarity measure for OWL-S annotated Web services

Yasser Ganjisaffar, Hassan Abolhassani, Mahmood Neshati, Mohsen Jamali

Research output: Chapter in Book/Report/Conference proceedingConference contribution

37 Citations (Scopus)

Abstract

Measuring semantic similarity of web services has several benefits and most of the proposed service discovery algorithms are based on measuring the similarity of the requested service with each of the advertised services. In this paper, we propose a method for measuring the similarity of web services which are annotated with OWL-S ontology. First, a semantic similarity measure for determining the similarity of OWL concepts is discussed and then based on this measure, the functional similarity of services is defined. Then it is showed that the precision of algorithms that only take into account the functional properties of services for measuring their similarity are low. Therefore the textual descriptions of web services are also taken into account and the textual similarity of services is also calculated. Then it is showed how Neural Networks can be used for combining these two measures for a better compound measure. The proposed technique is applied to a sample test collection and experimental results are presented which demonstrate the effectiveness of the idea.

Original languageEnglish
Title of host publicationProceedings - 2006 IEEE/WIC/ACM International Conference on Web Intelligence (WI 2006 Main Conference Proceedings), WI'06
Pages621-624
Number of pages4
DOIs
Publication statusPublished - 1 Dec 2007
Event2006 IEEE/WIC/ACM International Conference on Web Intelligence, WI'06 - Hong Kong, China
Duration: 18 Dec 200622 Dec 2006

Other

Other2006 IEEE/WIC/ACM International Conference on Web Intelligence, WI'06
CountryChina
CityHong Kong
Period18/12/0622/12/06

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ASJC Scopus subject areas

  • Computer Networks and Communications
  • Software

Cite this

Ganjisaffar, Y., Abolhassani, H., Neshati, M., & Jamali, M. (2007). A similarity measure for OWL-S annotated Web services. In Proceedings - 2006 IEEE/WIC/ACM International Conference on Web Intelligence (WI 2006 Main Conference Proceedings), WI'06 (pp. 621-624). [4061441] https://doi.org/10.1109/WI.2006.26