A ranking method for social-annotation-based service discovery

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

Abstract

With the rapid growth of Web services, service discovery becomes an important and difficult issue. Traditional UDDI-based and WSDL-based methods of service discovery have low precision, and semantic-based service discovery methods are usually inefficient and time-consuming. We observe that social annotations can optimize both precision and efficiency of service discovery. In this paper, we propose a social-annotation-based service discovery method by using a learning to rank method, and propose two algorithms, Query Annotation Relevance (QAR) and Service Annotation Ranking (SAR), to calculate the dynamic Query-dependent feature and the static Query-independent feature respectively. Our experiments show that our method is effective for improving service discovery performance.

Original languageEnglish
Title of host publicationProceedings - 6th IEEE International Symposium on Service-Oriented System Engineering, SOSE 2011
Pages114-121
Number of pages8
DOIs
StatePublished - 2011
Event6th IEEE International Symposium on Service-Oriented System Engineering, SOSE 2011 - Irvine, CA, United States
Duration: 12 Dec 201114 Dec 2011

Publication series

NameProceedings - 6th IEEE International Symposium on Service-Oriented System Engineering, SOSE 2011

Conference

Conference6th IEEE International Symposium on Service-Oriented System Engineering, SOSE 2011
Country/TerritoryUnited States
CityIrvine, CA
Period12/12/1114/12/11

Keywords

  • Web service
  • service discovery
  • social annotation
  • tag

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