Conversational agent is a system that provides user with proper information and maintains the context of dialogue based on natural language. When experts design the network for conversational agent of a domain, the network is usually very complicated and is hard to be understood. So the simplification of network by separating variables in the domain is helpful to design the conversational agent more efficiently. Composing Bayesian network as two stages, we aim to design conversational agent easily and analyze user's query in detail. Also, by using previous information of dialogue, it is possible to maintain the context of conversation. Actually implementing it for a guide of web pages, we can confirm the usefulness of the proposed architecture for conversational agent.
|Number of pages
|Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
|Published - 2004
All Science Journal Classification (ASJC) codes
- Theoretical Computer Science
- General Computer Science