Web Service Information Mining and Correlation Calculation Method Study

  • Huahua NingEmail author
  • Feng Chen
  • Pan Deng
  • Yao Zhao
  • Wei Yuan
  • Chaofan Bi
  • Biying Yan
Conference paper
Part of the Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering book series (LNICST, volume 142)


With the development of Internet technology, more and more web services are published on the Internet. How to efficiently and accurately obtain the specific services for users become more important. Based on this, web service vertical search engine emerged. This vertical search engine can improve the service retrieval efficiency compared with the traditional search engine. However there are still several deficiencies: required services are difficult to be filtered from the limited information that the users can refer; Moreover, sort principle of the search results are not transparent to users, they cannot reorder the search results according to their needs. This paper aims to solve this problem. Through mining service information, multi-dimensional information can be referred; through correlation calculation, users can search personalized information according to their needs, which enhances the power of web services retrieve and improves user experience of the search engine system.


Web service Information mining Correlation 



The work was supported by the National Natural Science Foundation of China (No. 61100066).


  1. 1. Accessed 20 May 2014
  2. 2. Accessed 20 May 2014
  3. 3.
    Rong, X.H., Deng, P., Chen, F.: A large-scale device collaboration resource selection method with multi-QoS constraint supported. Adv. Mater. Res. 143, 894–898 (2011)Google Scholar
  4. 4.
    Deng, P., Zhang, J.W., Rong, X.H., Chen, F.: A model of large-scale device collaboration system based on PI-Calculus for green communication. Telecommun. Syst. 52, 1313–1326 (2013)Google Scholar
  5. 5.
    Deng, P., Zhang, J.W., Rong, X.H., Chen, F.: Modeling the large-scale device control system based on PI-calculus. Adv. Sci. Lett. 4, 2374–2379 (2011)CrossRefGoogle Scholar
  6. 6.
    Rong, X.H., Chen, F., Deng, P., Ma, S.L.: A large-scale device collaboration mechanism. J. Comput. Res. Dev. 9, 1589–1596 (2011)Google Scholar
  7. 7.
    Chen, F., Rong, X.H., Deng, P., Ma, S.L.: A survey of device collaboration technology and system software. Acta Electronica Sinica 39, 440–447 (2011)Google Scholar
  8. 8.
    Zhang, J.W., Deng, P., Wan, J.F., Yan, B.Y., Rong, X.H., Chen, F.: A novel multimedia device ability matching technique for ubiquitous computing environments. EURASIP J. Wirel. Commun. Netw. 2013, 1–12 (2013)CrossRefGoogle Scholar
  9. 9.
    Willmott, S., Ronsdorf, H., Krempels, K.H.: Publish and search versus registries for semantic web service discovery. In: Proceedings of 2005 IEEE/WIC/ACM International Conference on IEEE , pp. 491–494 (2005)Google Scholar
  10. 10.
    Atkinson, C., Bostan, P., Hummel, O., et al.: A practical approach to web service discovery and retrieval. In: ICWS, pp. 241–248 (2007)Google Scholar
  11. 11.
  12. 12. Accessed 28 June 2014
  13. 13. Accessed 28 June 2014
  14. 14.
    Dekang, L.: An information-theoretic definition of similarity. In: Proceedings of the Fifteenth International Conference on Machine Learning, San Francisco, vol. 98, pp. 296–304 (1998)Google Scholar
  15. 15.
    Miller, G.A., Charles, W.G.: Contextual correlates of semantic similarity. Lang. Cogn. Process. 6(1), 1–28 (1991)CrossRefGoogle Scholar

Copyright information

© Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2015

Authors and Affiliations

  • Huahua Ning
    • 1
    Email author
  • Feng Chen
    • 1
  • Pan Deng
    • 1
  • Yao Zhao
    • 1
  • Wei Yuan
    • 1
  • Chaofan Bi
    • 1
  • Biying Yan
    • 1
  1. 1.Institute of Software Chinese Academy of SciencesBeijingPeople’s Republic of China

Personalised recommendations