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Personalised Web Experiences: Seamless Adaptivity across Web Service Composition and Web Content

  • Ian O’Keeffe
  • Vincent Wade
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5535)

Abstract

Users have become accustomed to a web that is more than an interactive hypermedia but is a complex mix of rich multimedia services and hypermedia content. Users are now contributors and active participants on the web. However, Pesonalisation technologies, such as Adaptive Hypermedia, have so far focused almost exclusively on adaptive content delivery resulting in their failure to become a high impact technologies. The absence of rich multimedia services in the current generation of Adaptive Hypermedia Systems means that they do not live up to the expectations of users. By providing personalised web experiences that combine both services and content in a seamless environment such systems could not only live up to the expectations of users but could exceed them. This paper presents a system that supports the adaptive selection and sequencing of both content and services in a unified manner. By applying techniques used in content based Adaptive Hypermedia to services with making use of the state of the art in service composition, this system delivers personalised web experiences that combine adaptively selected and sequenced content and services. The integration of appropriate content with services can improve the experience of the user as well as making the activity more efficient.

Keywords

Service Composition Business Process Execution Language Adaptive Selection Metadata Model Hierarchical Task Network 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Ian O’Keeffe
    • 1
  • Vincent Wade
    • 1
  1. 1.Centre for Next Generation Localisation, Knowledge and Data Engineering GroupSchool of Computer Science and Statistics, Trinity College DublinIreland

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