• DocumentCode
    2738177
  • Title

    Service recommendation with case-based reasoning

  • Author

    Pei Yang ; Ke Mao ; Xianzhong Zhong ; Feng Xu

  • Author_Institution
    Dept. of Control & Syst. Eng., Nanjing Univ., Nanjing, China
  • fYear
    2015
  • fDate
    9-11 April 2015
  • Firstpage
    631
  • Lastpage
    635
  • Abstract
    With the proliferating of Web services, how to efficiently and correctly recommend the appropriate service for process designer have attracted wide attentions from both industry and academia. The traditional service recommendation with the service interface semantic matching may not work properly, that is, the recommended service will be unusable or unavailable. In order to solve this problem, a new service recommendation approach with case-based reasoning (CBR) is proposed for the service composition system in this paper. Instead of acquiring complete ontology and semantic information, this method mined service processes designed before to obtain frequent process sequences for the service recommendation. Furthermore, the architecture of the service recommendation system with CBR is presented and the experiment is conducted. The experimental result shows the effectiveness of our approach.
  • Keywords
    Web services; case-based reasoning; ontologies (artificial intelligence); recommender systems; Web services; case-based reasoning; ontology; recommended service; service composition system; service interface semantic matching; service recommendation; Business; Cognition; Mathematics; Mobile ad hoc networks; Programming; Quality of service; Software; Web service; case-based reasoning; sequence mining; service recommendation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Networking, Sensing and Control (ICNSC), 2015 IEEE 12th International Conference on
  • Conference_Location
    Taipei
  • Type

    conf

  • DOI
    10.1109/ICNSC.2015.7116111
  • Filename
    7116111