An Effective Conversational Agent with User Modeling Based on Bayesian Network

Conversational agents interact with users using natural language interface. Especially in Internet space, their role has been recently highlighted as a virtual representative of a web site. However, most of them use simple pattern matching techniques without considering user’s goal. In this paper, we propose a conversational agent that utilizes user model constructed on Bayesian network for the responses consistent with user’s goal. The agent is applied to the active guide of a website, which shows that the user modeling based on Bayesian network helps to respond to user’s queries appropriately with the their goals.