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A Poisson Model for User Accesses to Web Pages

  • Şule Gündüz
  • M. Tamer Özsu
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2869)

Abstract

Predicting the next request of a user as she visits Web pages has gained importance as Web-based activity increases. There are a number of different approaches to prediction. This paper concentrates on the discovery and modelling of the user’s aggregate interest in a session. This approach relies on the premise that the visiting time of a page is an indicator of the user’s interest in that page. Even the same person may have different desires at different times. Although the approach does not use the sequential patterns of transactions, experimental evaluation shows that the approach is quite effective in capturing a Web user’s access pattern. The model has an advantage over previous proposals in terms of speed and memory usage.

Keywords

Association Rule Poisson Model User Session Recommendation Model Page Request 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2003

Authors and Affiliations

  • Şule Gündüz
    • 1
  • M. Tamer Özsu
    • 2
  1. 1.Department of Computer EngineeringIstanbul Technical UniversityIstanbulTurkey
  2. 2.School of Computer ScienceUniversity of WaterlooWaterlooCanada

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