• DocumentCode
    125342
  • Title

    Automatic Propagation of User Inputs in Service Composition for End-Users

  • Author

    Shaohua Wang ; Upadhyaya, Bipin ; Ying Zou ; Keivanloo, Iman ; Ng, Jason ; Ng, Timothy

  • Author_Institution
    Queen´s Univ., Kingston, ON, Canada
  • fYear
    2014
  • fDate
    June 27 2014-July 2 2014
  • Firstpage
    73
  • Lastpage
    80
  • Abstract
    End-users conduct various on-line activities. Quite often they re-visit websites and use services to perform repeated activities, such as on-line shopping. The end-users are required to enter the same information into various web services to accomplish such repeated tasks. Typing redundant information repetitively into such services negatively impacts the user experience. In this study, we propose an approach to prevent end-users from such unnecessary interruption. Our approach propagates user inputs across services by linking similar input and output parameters. Our approach also pre-fills values to the input parameters which could not be filled by the values from other input or output parameters. We propose a meta-data model for storing user inputs and an Input Parameter Context Model for identifying similar input or output parameters. We have implemented our approach and evaluated it on the real world services through an empirical study. Our overall approach can reduce on average 37% of input parameters through the execution of composed services.
  • Keywords
    Web services; Web sites; meta data; user interfaces; Web services; Websites; automatic propagation; input parameter context model; meta-data model; on-line shopping; redundant information; service composition; user input across services; Context; Context modeling; Electronic mail; Equations; Mathematical model; Semantics; Web services; information reuse; input parameter pre-filling; service composition;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Web Services (ICWS), 2014 IEEE International Conference on
  • Conference_Location
    Anchorage, AK
  • Print_ISBN
    978-1-4799-5053-9
  • Type

    conf

  • DOI
    10.1109/ICWS.2014.23
  • Filename
    6928883