User Models: The Problem of Disparity

A significant component of a user model in an information-seeking dialogue is the task-related plan motivating the information-seeker's queries. A number of researchers have modeled the plan inference process and used these models to design more robust natural language interfaces. However in each case, it has been assumed that the system's context model and the plan under construction by the information-seeker are never at variance. This paper addresses the problem of disparate plans. It presents a four phase approach and argues that handling disparate plans requires an enriched context model. This model must permit the addition of components suggested by the information seeker but not fully supported by the system's domain knowledge, and must differentiate among its components according to the kind of support accorded each component as a correct part of the information-seeker's overall plan. It is shown how a component's support should affect the system's hypothesis about the source of error once plan disparity is suggested.

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