WTCluster: Utilizing Tags for Web Services Clustering

  • Liang Chen
  • Liukai Hu
  • Zibin Zheng
  • Jian Wu
  • Jianwei Yin
  • Ying Li
  • Shuiguang Deng
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7084)

Abstract

Clustering web services would greatly boost the ability of web service search engine to retrieve relevant ones. An important restriction of traditional studies on web service clustering is that researchers focused on utilizing web services’ WSDL (Web Service Description Language) documents only. The singleness of data source limits the accuracy of clustering. Recently, web service search engines such as Seekda! allow users to manually annotate web services using so called tags, which describe the function of the web service or provide additional contextual and semantical information. In this paper, we propose a novel approach called WTCluster, in which both WSDL documents and tags are utilized for web service clustering. Furthermore, we present and evaluate two tag recommendation strategies to improve the performance of WTCluster. The comprehensive experiments based on a dataset consists of 15,968 real web services demonstrate the effectiveness of WTCluster and tag recommendation strategies.

Keywords

Service Discovery Query Term Content Vector WSDL Document Service Discovery Problem 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Liang Chen
    • 1
  • Liukai Hu
    • 1
  • Zibin Zheng
    • 2
  • Jian Wu
    • 1
  • Jianwei Yin
    • 1
  • Ying Li
    • 1
  • Shuiguang Deng
    • 1
  1. 1.Zhejiang UniversityChina
  2. 2.The Chinese University of Hong KongChina

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