An Intelligent Recommender System for Web Resource Discovery and Selection

  • Liming Chen
  • Feng Tao
Part of the Studies in Computational Intelligence book series (SCI, volume 117)

The Web is now evolving from information sharing to resource provisioning as the emerging Web services and Grid technologies are widely accepted and practiced. Soon the Web will be populated with abundant resources that can be accessed, shared and reused, which will inevitably lead to resource overflow. This chapter introduces a semantic-enabled, knowledge-based intelligent recommender system for Web resource discovery, selection and effective use. The system is based on a novel hybrid approach, which draws on the functionality of Semantic Web Services to represent, expose and discover available resources, and exploits domain knowledge to guide resource selection and use. We propose an integrated system architecture and describe the underpinning semantic- and knowledge-based recommending mechanisms. A number of technologies and tools are developed, and further applied to a real world application – the UK e-Science GEODISE project, to demonstrate the system’s applicability and benefits.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Liming Chen
    • 1
  • Feng Tao
    • 2
  1. 1.School of Computing and MathematicsUniversity of UlsterUK
  2. 2.School of Electronics and Computer ScienceUniversity of SouthamptonUK

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