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Preprocessing and Mining Web Log Data for Web Personalization

  • M. Baglioni
  • U. Ferrara
  • A. Romei
  • S. Ruggieri
  • F. Turini
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2829)

Abstract

We describe the web usage mining activities of an on-going project, called ClickWorld, that aims at extracting models of the navigational behaviour of a web site users. The models are inferred from the access logs of a web server by means of data and web mining techniques. The extracted knowledge is deployed to the purpose of offering a personalized and proactive view of the web services to users. We first describe the preprocessing steps on access logs necessary to clean, select and prepare data for knowledge extraction. Then we show two sets of experiments: the first one tries to predict the sex of a user based on the visited web pages, and the second one tries to predict whether a user might be interested in visiting a section of the site.

Keywords

Registered User User Session Proactive Personalization Data Mart Site Page 
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

  • M. Baglioni
    • 1
  • U. Ferrara
    • 2
  • A. Romei
    • 1
  • S. Ruggieri
    • 1
  • F. Turini
    • 1
  1. 1.Dipartimento di InformaticaUniversità di PisaPisaItaly
  2. 2.KSolutions S.p.AS. Martino UlmianoItaly

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