ABSTRACT
A user model in a natural language dialog system contains knowledge about particular users' beliefs, goals, attitudes, or other characteristics. User modeling facilitates cooperative adaptation to a user's conversational behavior and goals.
This paper proposes active strategies for acquiring knowledge about users. Current systems employ passive acquisition strategies, which build a model of the user by making inferences based on passive observation of the dialog. Passive acquisition is generally preferable to active querying, to minimize unnecessary dialog. However, in some cases the system should actively initiate subdialogs with the purpose of acquiring information about the user. We propose a method for identifying these conditions based upon maximizing expected utility.
