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Collaboratively Shared Information Retrieval Model for e-Learning

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Advances in Web Based Learning – ICWL 2006 (ICWL 2006)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 4181))

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Abstract

Nowadays, the World Wide Web offers public search services by a number of Internet search engine companies e.g. Google [16], Yahoo! [17], etc. They own their internal ranking algorithms, which may be designed for either general-purpose information and/or specific domains. In order to fight for bigger market share, they have developed advanced tools to facilitate the algorithms through the use of Relevance Feedback (RF) e.g. Google’s Toolbar. Experienced by the black-box tests of the RF toolbar, all in all, they can acquire simple and individual RF contribution. As to this point, in this paper, we have proposed a collaboratively shared Information Retrieval (IR) model to complement the conventional IR approach (i.e. objective) with the collaborative user contribution (i.e. subjective). Not only with RF and group relevance judgments, our proposed architecture and mechanisms provide a unified way to handle general purpose textual information (herein, we consider e-Learning related documents) and provide advanced access control features [15] to the overall system.

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Author information

Authors and Affiliations

  1. Media Research Institute, Waseda University, 2-579-15 Mikajima, Tokorozawa, Saitama, 359-1192, Japan

    Shermann S. M. Chan

  2. Dept. Human Informatics and Cognitive Sciences, Waseda University, 2-579-15 Mikajima, Tokorozawa, Saitama, 359-1192, Japan

    Qun Jin

Authors
  1. Shermann S. M. Chan
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  2. Qun Jin
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Editor information

Editors and Affiliations

  1. Department of Computer Science, City University of Hong Kong, Hong Kong, China

    Wenyin Liu

  2. Department of Computer Science, City University of Hong Kong, 83 Tat Chee Avenue, Kowloon, Hong Kong, China

    Qing Li

  3. Department of Computer Science, University of Durham, South Road, DH1 3LE, Durham, UK

    Rynson W.H. Lau

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© 2006 Springer-Verlag Berlin Heidelberg

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Chan, S.S.M., Jin, Q. (2006). Collaboratively Shared Information Retrieval Model for e-Learning. In: Liu, W., Li, Q., W.H. Lau, R. (eds) Advances in Web Based Learning – ICWL 2006. ICWL 2006. Lecture Notes in Computer Science, vol 4181. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11925293_12

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  • DOI: https://doi.org/10.1007/11925293_12

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-49027-2

  • Online ISBN: 978-3-540-68509-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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