Conversational Case-Based Reasoning

  • Authors:

  • David W. Aha;Leonard A. Breslow;Héctor Muñoz-Avila

  • Affiliations:

  • Navy Center for Applied Research in Artificial Intelligence, Naval Research Laboratory, Code 5510, 4555 Overlook Ave, SW, Washington, DC 20375-5337, USA. aha@aic.nrl.navy.mil;Navy Center for Applied Research in Artificial Intelligence, Naval Research Laboratory, Code 5510, 4555 Overlook Ave, SW, Washington, DC 20375-5337, USA. breslow@aic.nrl.navy.mil;Department of Computer Science, University of Maryland, College Park, MD 20742-3255, USA. munoz@cs.umd.edu

  • Venue:
  • Applied Intelligence
  • Year:
  • 2001

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Abstract

Conversational case-based reasoning (CCBR) was the first widespread commercially successful form of case-based reasoning. Historically, commercial CCBR tools conducted constrained human-user dialogues and targeted customer support tasks. Due to their simple implementation of CBR technology, these tools were almost ignored by the research community (until recently), even though their use introduced many interesting applied research issues. We detail our progress on addressing three of these issues: simplifying case authoring, dialogue inferencing, and interactive planning. We describe evaluations of our approaches on these issues in the context of NaCoDAE and HICAP, our CCBR tools. In summary, we highlight important CCBR problems, evaluate approaches for solving them, and suggest alternatives to be considered for future research.