Category Based Customization Approach for Information Retrieval

  • Kenro Aihara
  • Atsuhiro Takasu
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2109)


This paper proposes an customization technique to supporting interactive document retrieval in unorganized open information space like WWW. We assume that taxonomical thought is one of the most important and skilled operations for us when we organize or store information. The proposed methodology, therefore, handles hierarchical categories of documents. The system can be customized through users’ modification of categories. The features of the proposed approach are (1) visualization of document categories for interaction, (2) initialization of categories by hierarchical clustering method, (3) customization of categories by support vector machine techniques, (4) additional attributes for individual implicit cognitive aspects.


User Feedback Customization Visualization Text Categorization Human-Computer Interaction Support Vector Machine Information Retrieval 


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  1. 1.
    Salton, G., Buckley, C.: Term weighting approaches in automatic text retrieval. Information Processing and Management. 24(5) (1988) 513–523CrossRefGoogle Scholar
  2. 2.
    Aihara, K., Hori, K., Ohsuga, S.: Aiding the process of building knowledge out of chunks of information. Journal of Japanese Society for Artificial Intelligence. 11(3) (1996) 432–439 (in Japanese)Google Scholar
  3. 3.
    Boser, B., Guyon, I., Vapnik, V.: A training algorithm for optimal margin classifiers. Proceedings of the Fifth Annual ACM Workshop on Computational Learning Theory. (1992) 144–152Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2001

Authors and Affiliations

  • Kenro Aihara
    • 1
  • Atsuhiro Takasu
    • 1
  1. 1.National Institute of InformaticsTokyoJapan

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