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Personalized News Categorization Through Scalable Text Classification

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Frontiers of WWW Research and Development - APWeb 2006 (APWeb 2006)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 3841))

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Abstract

Existing news portals on the WWW aim to provide users with numerous articles that are categorized into specific topics. Such a categorization procedure improves presentation of the information to the end-user. We further improve usability of these systems by presenting the architecture of a personalized news classification system that exploits user’s awareness of a topic in order to classify the articles in a ‘per-user’ manner. The system’s classification procedure bases upon a new text analysis and classification technique that represents documents using the vector space representation of their sentences. Traditional ‘term-to-documents’ matrix is replaced by a ‘term-to-sentences’ matrix that permits capturing more topic concepts of every document.

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Author information

Authors and Affiliations

  1. Research Academic Computer Technology Institute N. Kazantzaki, University Campus, GR-26500, Patras, Greece

    Ioannis Antonellis, Christos Bouras & Vassilis Poulopoulos

  2. Computer Engineering and Informatics Department, University of Patras, GR-26500, Patras, Greece

    Ioannis Antonellis, Christos Bouras & Vassilis Poulopoulos

Authors
  1. Ioannis Antonellis
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  2. Christos Bouras
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  3. Vassilis Poulopoulos
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Editor information

Editors and Affiliations

  1. School of ITEE, The University of Queensland, Australia

    Xiaofang Zhou

  2. School of Computer Science and Technology, Heilongjiang University, China

    Jianzhong Li

  3. School of Information Technology and Electrical Engineering, The University of Queensland, Brisbane, QLD, Australia

    Heng Tao Shen

  4. Institute of Industrial Science, The University of Tokyo, 4-6-1 Komaba, Meguro-ku, 153-8505, Tokyo, Japan

    Masaru Kitsuregawa

  5. Victoria University, Australia

    Yanchun Zhang

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© 2006 Springer-Verlag Berlin Heidelberg

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Antonellis, I., Bouras, C., Poulopoulos, V. (2006). Personalized News Categorization Through Scalable Text Classification. In: Zhou, X., Li, J., Shen, H.T., Kitsuregawa, M., Zhang, Y. (eds) Frontiers of WWW Research and Development - APWeb 2006. APWeb 2006. Lecture Notes in Computer Science, vol 3841. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11610113_35

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  • DOI: https://doi.org/10.1007/11610113_35

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-31142-3

  • Online ISBN: 978-3-540-32437-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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