Elaine Rich

Building and Exploiting User Models Degree Type: Ph.D. in Computer Science
Advisor(s): George Robertson
Graduated: May 1979

Abstract:

This thesis addresses the problems that must be considered if computers are going to treat their users as individuals with distinct personalities, goals, and so forth. It first outlines the issues, and then proposes stereotypes as a useful mechanism for building models of individual users on the basis of a small amount of information about them. In order to build user models quickly, a large amount of uncertain knowledge must be incorporated into the models.

The issue of how to resolve the conflicts that will arise among such inferences is discussed. A system, GRUNDY, that builds, with the aid of stereotypes, models of its users, and then exploits those models to guide it in its task, suggesting novels that people may find interesting, is described. GRUNDY’s performance is analyzed to provide some insight into how effective the user models are.

The techniques that were developed for GRUNDY are shown to be appropriate for at least two other domains. The tradeoffs involved in designing such a user modeler for an arbitrary system are discussed. The issues involved in the modification of the data base of stereotypes to better describe the system’s actual users is discussed. Some new questions raised by the ability to model individual users are raised.

Thesis Committee:
George Robertson (Chair)

Nico Habermann, Head, Computer Science Department