Predictive Statistical Models for User Modeling

By Ingrid Zukerman, David W. Albrecht. User modeling and user-adapted interaction, 2001

362 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Information Systems, Signal Processing

View Paper: https://www.semanticscholar.org/paper/cb71956a346a73692128fcbe162511c238a90aa2

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Stefano V. Albrecht
2. Peter Stone
3. Li Chen
4. Pearl Huan Z. Pu
5. A. Gertner
6. Wai Lam
7. Cristina Conati
8. Kurt VanLehn

In Information Systems

1. Li Chen
2. Rong Hu
3. Pearl Huan Z. Pu
4. A. Gertner
5. Wai Lam
6. Peter Stone
7. Cristina Conati
8. Kurt VanLehn

In Signal Processing

1. Peter Stone
2. A. Gertner
3. Wai Lam
4. Cristina Conati
5. Li Chen
6. Pearl Huan Z. Pu
7. Kurt VanLehn
8. Stefano V. Albrecht

Citations in the corpus

• Autonomous agents modelling other agents: A comprehensive survey and open problems (2017, background): “Since these early works in game theory and AI, the problem of modelling other agents has been an active area of research in many sub-communities, including classic game playing [106], computer Poker [232], automated negotiation [21], simulated robot soccer [173], human user modelling [289,194], huma”
• Using Bayesian Networks to Manage Uncertainty in Student Modeling (2002, methodology): “Evaluation of a statistical approach to student modeling can use techniques from both disciplines of machine learning and user modeling (Zukerman and Albrecht, 2001).”
• Empirical Evaluation of User Models and User-Adapted Systems (2001, neutral): “For a review of machine learning and predictive statistical models see Webb et al. (2001), and Zukerman and Albrecht (2001) respectively.”
• Techniques for Plan Recognition (2001, background): “The article in this special issue by Zukerman and Albrecht (2001) discusses recent research on predictive statistical techniques, and the article by Webb et al. (2001) discusses the role of machine learning in user modeling.”
• Introduction to the special topic section on mining Web resources for enhancing information retrieval (2007, background): “Zukerman and Albrecht (2001) categorized Web page recommendations into two main approaches: a contentbased system constructs a model based on the contents of the Livelink objects.”
• Evaluating recommender systems from the user’s perspective: survey of the state of the art (2012, background): “Zukerman and Albrecht (2001) provide a comprehensive overview of such recommender systems; other ways to classify recommender systems are discussed by Burke (2002), and Adomavicius and Tuzhilin (2005).”