An Intelligent Recommender System for Web Resource Discovery and Selection

Liming Chen, Feng Tao

    Research output: Chapter in Book/Report/Conference proceedingChapter

    6 Citations (Scopus)

    Abstract

    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.
    Original languageEnglish
    Title of host publicationIntelligent Decision and Policy Making Support Systems
    PublisherSpringer
    Pages113-140
    Volume117
    ISBN (Print)978-3-540-78306-0
    DOIs
    Publication statusPublished - 16 Apr 2008

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  • Cite this

    Chen, L., & Tao, F. (2008). An Intelligent Recommender System for Web Resource Discovery and Selection. In Intelligent Decision and Policy Making Support Systems (Vol. 117, pp. 113-140). Springer. https://doi.org/10.1007/978-3-540-78308-4_7