Dynamic User Model Construction with Bayesian Networks for Intelligent Information Queries

Eugene Santos Jr., University of Connecticut; Scott M. Brown, Air Force Research Laboratory; Moises Lejter and Grace Ngai, University of Connecticut; Sheila B. Banks and Martin R. Stytz, Calculated Insight

The complexity of current software applications is overwhelming users. The need exists for intelligent interface agents to address the problems of increasing taskload that is overwhelming the human user. Interface agents could help alleviate user taskload by extracting and analyzing relevant information, and providing information abstractions of that information, 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 Clavin project is to build an intelligent natural language query information management system. Clavin must maintain 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 autonomously react to changes in user intent as well as the information so urces, 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. http://www.engr.uconn.edu/cse/IDIS

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