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WS-Portal an Enriched Web Services Search Engine

  • Mustapha Aznag
  • Mohamed Quafafou
  • Zahi Jarir
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8954)

Abstract

With a growing number of web services, discovering services that can match with a user’s query becomes a big challenging task. It’s very tedious for a service consumer to select the appropriate one according to her/his needs. In this paper, we propose WS-Portal; An Enriched Web Services Search Engine which contains 7063 providers, 115 sub-classes of category and 22236 web services crawled from the Internet. In WS-Portal, severals technologies are employed to improve the effectiveness of web services discovery (i.e. web services clustering, tags recommendation, services rating and monitoring).

Keywords

Web services Discovery Tags Recommendation Monitoring Topic browsing Topic models 

References

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    Aznag, M., Quafafou, M., Jarir, Z.: Correlated topic model for web services ranking. Int. J. Adv. Comput. Sci. Appl. (IJACSA) 4(6), 283–291 (2013)Google Scholar
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    Aznag, M., Quafafou, M., Rochd, E.M., Jarir, Z.: Probabilistic topic models for web services clustering and discovery. In: Lau, K.-K., Lamersdorf, W., Pimentel, E. (eds.) ESOCC 2013. LNCS, vol. 8135, pp. 19–33. Springer, Heidelberg (2013) CrossRefGoogle Scholar
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    Aznag, M., Quafafou, M., Jarir, Z.: Multilabel Learning for Automatic Web Services Tagging. Int. J. Adv. Comput. Sci. Appl. (IJACSA) 5(8), 182–191 (2014)Google Scholar
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    Aznag, M., Quafafou, M., Jarir, Z.: Leveraging formal concept analysis with topic correlation for service clustering and discovery. In: 21th IEEE International Conference on Web Services (ICWS), Alaska, USA, July 2014Google Scholar
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    Rochd, E.M., Quafafou, M., Aznag, M.: Encoding local correspondence in topic models. In: IEEE International Conference on Tools with Artificial Intelligence (ICTAI), Washington, DC, USA, 4–6 November 2013Google Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.Aix-Marseille University, CNRS, LSIS UMR 7296MarseilleFrance
  2. 2.LISI Laboratory FSSMCadi Ayyad UniversityMarrakechMorocco

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