Abstract
This chapter surveys the field of user modeling in artificial intelligence dialog systems. First, reasons why user modeling has become so important in the last few years are pointed out, and definitions are proposed for the terms ‘user model’ and ‘user modeling component’. Research within and outside of artificial intelligence which is related to user modeling in dialog systems is discussed. In Section 2, techniques for constructing user models in the course of a dialog are presented and, in Section 3, recent proposals for representing a wide range of assumptions about a user’s beliefs and goals in a system’s knowledge base are surveyed. Examples for the application of user models in systems developed to date are then given, and some social implications discussed. Finally, unsolved problems like coping with collective beliefs or resource-limited processes are investigated, and prospects for application-oriented research are outlined. Although the survey is restricted to user models in natural-language dialog systems, most of the concepts and methods discussed can be extended to AI dialog systems in general.
This research was supported by the Special Collaborative Research Programme on Artificial Intelligence and Knowledge-Based Systems (SFB 314) of the German Science Foundation. We would like to thank G. Ferrari, Ch. Habel, M. Hecking, A. Jameson and an anonymous referee for their comments on earlier versions of this chapter. This is an extended and revised version of [WAHL86b].
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Wahlster, W., Kobsa, A. (1989). User Models in Dialog Systems. In: Kobsa, A., Wahlster, W. (eds) User Models in Dialog Systems. Symbolic Computation. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-83230-7_1
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