A Web Service Selection Mechanism Based on User Ratings and Collaborative Filtering

Conference paper
Part of the Smart Innovation, Systems and Technologies book series (SIST, volume 20)

Abstract

As cloud computing is gaining its popularity, more and more services are deployed through Web service technology. How to quickly select a suitable service is an important issue. In recent studies on the Web service selection, the most approaches are based on service requirements and quality of services designated by the user but less take the user’s own evaluation into account.

In this paper, we propose a Web service selection mechanism based on user ratings and collaborative filtering. In this mechanism the quality of service of Web services, the feedback from the users and similarity among the users are taken into consideration for selecting Web services. The proposed method is verified by a case study of a travel information system and then the Mean Average Precision (MAP) is evaluated by the experiments.

Keywords

Web services Web service selection Feedback mechanism Personalization 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Yu, Q., Bouguettaya, A.: Guest Editorial: Special Section on Query Models and Efficient Selection of Web Services. IEEE Transactions on Services Computing 3(1), 161–162 (2010)CrossRefGoogle Scholar
  2. 2.
    Carenini, A., Cerizza, D., Comerio, M., Valle, E.D., De Paoli, F., Maurino, A., Palmonari, M., Sassi, M., Turati, A.: Semantic Web Service Discovery and Selection: a Test Bed Scenario. In: Proceedings of the 6th International Workshop on Evaluation of Ontology-based Tools and the Semantic Web Service Challenge (EON-SWSC-2008), Tenerife, Spain, June 1-2 (2008)Google Scholar
  3. 3.
    Crasso, M., Zunino, A., Campo, M.: A Survey of Approaches to Web Service Discovery in Service-Oriented Architectures. Journal of Database Management 22(1), 102–132 (2011)CrossRefGoogle Scholar
  4. 4.
    Balke, W.-T., Wagner, M.: Towards Personalized Selection of Web Services. In: WWW (Alternate Paper Tracks) 2003, Budapest, Hungary, May 20-24 (2003)Google Scholar
  5. 5.
    Wang, H.-C., Lee, C.-S., Ho, T.-H.: Combining Subjective and Objective QoS Factors for Personalized Web Service Selection. Expert Systems with Applications 32(2), 571–584 (2007)CrossRefGoogle Scholar
  6. 6.
    Ran, S.P.: A Model for Web Services Discovery with QoS. ACM SIGecom Exchanges 4(1), 1–10 (2003)CrossRefGoogle Scholar
  7. 7.
    Yu, H.Q., Reiff-Marganiec, S.: Non-functional Property based service selection: A survey and classification of approaches. In: Non Functional Properties and Service Level Agreements in Service Oriented Computing Workshop Co-located with the 6th IEEE European Conference on Web Services, Ireland, Dublin, November 12 (2008)Google Scholar
  8. 8.
    Singh, M.P., Huhns, M.N.: Service-Oriented Computing: Semantics, Processes, Agents. Wiley (2005)Google Scholar
  9. 9.
    Yu, Q., Bouguettaya, A.: Foundations for Efficient Web Service Selection. Springer (2010)Google Scholar
  10. 10.
    Yu, P.S.: Data mining and personalization technologies. In: Proceedings of the Sixth International Conference on Database Systems for Advanced Applications (1999)Google Scholar
  11. 11.
    Jannach, D., Zanker, M., Felfernig, A., Friedrich, G.: Recommender Systems: An Introduction. Cambridge University Press (2011)Google Scholar
  12. 12.
    Resnick, P., Varian, H.R.: Recommender Systems. Communications of the ACM 40(3), 56–89 (1997)CrossRefGoogle Scholar
  13. 13.
    Jester Datasets, University of California Berkeley, http://eigentaste.berkeley.edu/dataset/

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  1. 1.Department of Computer Science and Information EngineeringChung Hua UniversityHsinchu CityTaiwan

Personalised recommendations