Article

User Modeling and User-Adapted Interaction

, Volume 11, Issue 1, pp 5-18

First online:

Predictive Statistical Models for User Modeling

  • Ingrid ZukermanAffiliated withSchool of Computer Science and Software Engineering, Monash University
  • , David W. AlbrechtAffiliated withSchool of Computer Science and Software Engineering, Monash University

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 learning collaborative learning linear models TFIDF-based models Markov models Neural networks classifications rule induction Bayesian networks