Personalized Classification for Keyword-Based Category Profiles

  • Aixin Sun
  • Ee-Peng Lim
  • Wee-Keong Ng
Conference paper

DOI: 10.1007/3-540-45747-X_5

Part of the Lecture Notes in Computer Science book series (LNCS, volume 2458)
Cite this paper as:
Sun A., Lim EP., Ng WK. (2002) Personalized Classification for Keyword-Based Category Profiles. In: Agosti M., Thanos C. (eds) Research and Advanced Technology for Digital Libraries. ECDL 2002. Lecture Notes in Computer Science, vol 2458. Springer, Berlin, Heidelberg

Abstract

Personalized classification refers to allowing users to define their own categories and automating the assignment of documents to these categories. In this paper, we examine the use of keywords to define personalized categories and propose the use of Support Vector Machine (SVM) to perform personalized classification. Two scenarios have been investigated. The first assumes that the personalized categories are defined in a flat category space. The second assumes that each personalized category is defined within a pre-defined general category that provides a more specific context for the personalized category. The training documents for personalized categories are obtained from a training document pool using a search engine and a set of keywords. Our experiments have delivered better classification results using the second scenario. We also conclude that the number of keywords used can be very small and increasing them does not always lead to better classification performance.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2002

Authors and Affiliations

  • Aixin Sun
    • 1
  • Ee-Peng Lim
    • 1
  • Wee-Keong Ng
    • 1
  1. 1.Centre for Advanced Information Systems School of Computer EngineeringNanyang Technological UniversitySingapore

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