David Heckerman and
Eric Horvitz
Decision Theory & Adaptive Systems Group
Microsoft Research
Redmond, Washington 98052-6399
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People using consumer software applications typically do not use technical jargon when querying an online database of help topics. Rather, they attempt to communicate their goals with common words and phrases that describe software functionality in terms of structure and objects they understand. We describe a Bayesian approach to modeling the relationship between words in a user's query for assistance and the informational goals of the user. After reviewing the general method, we describe several extensions that center on integrating additional distinctions and structure about language usage and user goals into the Bayesian models.
Keywords: Bayesian information retrieval, user modeling.
In: Proceedings of the Fourteenth Conference on Uncertainty in Artificial Intelligence, Madison, WI, July 1998, pages 230-237. Morgan Kaufmann: San Francisco.
Author Email: heckerma@microsoft.com, horvitz@microsoft.com