A hybrid-sorting semantic matching method

Kan Li, Wensi Mu, Yong Luan, Shaohua An

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Semantic Web Service enables automated service discovery, and even execution. Discovering proper services which match the given request has become an important issue as Internet technology develops and service demands increase. Existing service matching methods in service discovering always cost too much time for obtaining precision and recall ratio. This paper proposes a semantic similarity computing algorithm which considers both information capacity and ontology concept distance. Based on this similarity computing algorithm, we present a hybrid-sorting web service matching method. Compare with other methods like OWLS-MX by experiments, our method reduce average query time and we even improve recall ratio and precision ratio. In addition, this method supports service composition, another important issue in service discovery.

Original languageEnglish
Title of host publicationAdvanced Data Mining and Applications - 9th International Conference, ADMA 2013, Proceedings
Pages404-413
Number of pages10
EditionPART 2
DOIs
Publication statusPublished - 2013
Event9th International Conference on Advanced Data Mining and Applications, ADMA 2013 - Hangzhou, China
Duration: 14 Dec 201316 Dec 2013

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 2
Volume8347 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference9th International Conference on Advanced Data Mining and Applications, ADMA 2013
Country/TerritoryChina
CityHangzhou
Period14/12/1316/12/13

Keywords

  • Semantic
  • service matching method
  • similarity computing algorithm

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