A learning ontology method for RESTful semantic web services

Yong Ju Lee, Chang Su Kim

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

32 Scopus citations

Abstract

The growing number of RESTful web services available on the web raises a challenging search problem as to how the desired web services should be located. Traditional keyword searching is inaccurate, and its limitations have been noted for several years. We propose a combination method of WADL and a learning ontology mechanism to enable RESTful semantic web services. These syntactic and semantic descriptions allow search engines to support a similarity search for RESTful web services. We describe an experimental study on a collection of 168 RESTful web services. The experimental results show that our method has higher performance in terms both of the rate of recall and precision compared to existing methods.

Original languageEnglish
Title of host publicationProceedings - 2011 IEEE 9th International Conference on Web Services, ICWS 2011
PublisherIEEE Computer Society
Pages251-258
Number of pages8
ISBN (Print)9780769544632
DOIs
StatePublished - 2011
Event2011 IEEE 9th International Conference on Web Services, ICWS 2011 - Washington, United States
Duration: 4 Jul 20119 Jul 2011

Publication series

NameProceedings - 2011 IEEE 9th International Conference on Web Services, ICWS 2011

Conference

Conference2011 IEEE 9th International Conference on Web Services, ICWS 2011
Country/TerritoryUnited States
CityWashington
Period4/07/119/07/11

Keywords

  • Ontology learnig
  • Parameter clustering
  • Pattern analysis
  • RESTful web services
  • Semantic web
  • Similarity search
  • WADL

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