The Lumiere Project: Bayesian User Modeling for Inferring the Goals and Needs of Software Users
This work addresses the problem of providing intelligent assistance to software users, though it appears incremental as it builds on existing Bayesian modeling approaches.
The Lumiere Project tackled the problem of inferring software users' goals and needs by developing Bayesian user models, resulting in prototypes that were used as the basis for the Office Assistant in Microsoft Office '97.
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 users 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 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.