Dialogue Management for Conversational Case-Based Reasoning

Two key objectives of conversational case-based reasoning (CCBR) systems are (1) eliciting case facts in a manner that minimizes the user’s burden in terms of resources such as time, information cost, and cognitive load, and (2) integrating CBR with other problem solving modalities. This paper proposes an architecture that addresses both these goals by integrating CBR with a discourse-oriented dialogue engine. The dialogue engine determines when CBR or other problem-solving techniques are needed to achieve pending discourse goals. Conversely, the CBR component has the full resources of a dialogue engine to handle topic changes, interruptions, clarification questions by either the user or the system, and other speech acts that arise in problem-solving dialogues.

• Type: Conference
• Year: 2004
• Where: EWCBR
• Authors: Karl Branting, James C. Lester, Bradford W. Mott
• Keywords: Artificial Intelligence, Conversational Case-based Reasoning, Dialogue Engine, Dialogue Engine Determines, EWCBR 2004