User Modeling and User-Adapted Interaction

, Volume 11, Issue 1, pp 5–18

Predictive Statistical Models for User Modeling

  • Ingrid Zukerman
  • David W. Albrecht
Article

DOI: 10.1023/A:1011175525451

Cite this article as:
Zukerman, I. & Albrecht, D.W. User Modeling and User-Adapted Interaction (2001) 11: 5. doi:10.1023/A:1011175525451
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Abstract

The limitations of traditional knowledge representation methods for modeling complex human behaviour led to the investigation of statistical models. Predictive statistical models enable the anticipation of certain aspects of human behaviour, such as goals, actions and preferences. In this paper, we motivate the development of these models in the context of the user modeling enterprise. We then review the two main approaches to predictive statistical modeling, content-based and collaborative, and discuss the main techniques used to develop predictive statistical models. We also consider the evaluation requirements of these models in the user modeling context, and propose topics for future research.

content-based learningcollaborative learninglinear modelsTFIDF-based modelsMarkov modelsNeural networksclassificationsrule inductionBayesian networks
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© Kluwer Academic Publishers 2001

Authors and Affiliations

  • Ingrid Zukerman
    • 1
  • David W. Albrecht
    • 1
  1. 1.School of Computer Science and Software EngineeringMonash UniversityClaytonAustralia.