Dynamic User Model Construction with Bayesian Networks for Intelligent Information Queries

The complexity of" current soft.ware applications is overwhelming users. The need exists for inteUigent interface agents to address the problems of increasing taskload that is overwhelming the hunloax user. Interface agents could help alleviate user taskload by extracting and analyzing relevant information, and providing information abstractions of that informatiou, and providing timely, beneficial assistance to users. Central to providing assistance to a user is the issue of correctly determining the user’s intent. The C.lavin project is to build an intelligent natural language query information management system. Clavin must mMntain a dynamic user model of the relevant concepts in the user inquiries as they relate to the information sources. The primary goal of Clavin is to antonomously react to changes in user intent as well as the information sources, by dynamically constructing the appropriate queries relative to the changes identified. In this paper, we discuss the problems and issues that arise in achieving user-intent ascription through dynamic user model construction with Bayesian networks.