MUSETTE: a framework for knowledge capture from experience

In this article we present a new approach for modelling user’s experience in using a computer system, with the perspective of reusing this experience as knowledge in context for helping a user along his task. The MUSETTE (Modelling USEs and Tasks for Tracing Experience) approach relies on the capturing of a use trace conforming to a general use model, describing the objects and relations handled by the user of the computer system. This primitive trace can be seen as a task-neutral knowledge base, which can further be analysed with respect to explained task signatures, in order to locate emerging significant episodes, which can be re-used as useful contextual pieces of knowledge by software assistants. The advantages of this approach are demonstrated through four scenarios. We also present a Musette modelling of a real application and compare Musette to other approaches dealing with user’s tasks and uses.