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Common Topic Group Mining for Web Service Discovery

  • Jian Wang
  • Panpan Gao
  • Yutao MaEmail author
  • Keqing He
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9464)

Abstract

Recent years have witnessed an increasing number of services published on the Internet. How to find suitable services according to user queries remains a challenging issue in the services computing field. Many prior studies have been reported towards this direction. In this paper, we propose a novel service discovery approach by mining and matching common topic groups. In our approach, we mine the common topic groups based on the service-topic distribution matrix generated by topic modeling, and the extracted common topic groups can then be leveraged to match user queries to relevant services, so as to make a better trade-off between the number of available services and the accuracy of service discovery. The results of experiments conducted on a publicly available data set show that compared with other widely used methods, our approach can improve the performance of service discovery by decreasing the number of candidate services.

Keywords

Web services discovery Common topic group Topic model 

Notes

Acknowledgements

The work is supported by the National Basic Research Program of China under grant No. 2014CB340404, the National Natural Science Foundation of China under grant Nos. 61202031, 61272111, and 61373037, and the central grant funded Cloud Computing demonstration project of China undertaken by Kingdee Software (China).

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.State Key Laboratory of Software EngineeringWuhan UniversityWuhanChina

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