The Lumiere Project: Bayesian User Modeling for Inferring the Goals and Needs of Software Users

Eric Horvitz, Jack Breese, David Heckerman, David Hovel, Koos Rommelse

Decision Theory & Adaptive Systems Group
Microsoft Research
Redmond, Washington 98052-6399

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Abstract:

The Lumiere Project centers on harnessing probability and utility to provide assistance to computer software users. We review work on Bayesian user models that can be employed to infer a user's needs by considering a user's background, actions, and queries. Several problems were tackled in Lumiere research, including (1) the construction of Bayesian models for reasoning about the time-varying goals of computer users from their observed actions and queries, (2) gaining access to a stream of events from software applications, (3) developing a language for transforming system events into observational variables represented in Bayesian user models, (4) developing persistent profiles to capture changes in a user's expertise, and (5) the development of an overall architecture for an intelligent user interface. Lumiere prototypes served as the basis for the Office Assistant in the Microsoft Office '97 suite of productivity applications.

Keywords: Human-computer interface, goal recognition, Bayesian user modeling.

In: Proceedings of the Fourteenth Conference on Uncertainty in Artificial Intelligence, Madison, WI, July 1998, pages 256-265. Morgan Kaufmann: San Francisco.

Author Email: horvitz@microsoft.com, breese@microsoft.com, heckerma@microsoft.com,davidhov@microsoft.com