The vocabulary problem in human-system communication
Communications of the ACM
Case-based reasoning
An adaptive agent for case description in diagnostic CBR systems
Computers in Industry
Conversational Case-Based Reasoning
Applied Intelligence
Interactive Case-Based Reasoning in Sequential Diagnosis
Applied Intelligence
Redundancy Detection in Semistructured Case Bases
IEEE Transactions on Knowledge and Data Engineering
On the Role of Abstraction in Case-Based Reasoning
EWCBR '96 Proceedings of the Third European Workshop on Advances in Case-Based Reasoning
Supporting Dialogue Inferencing in Conversational Case-Based Reasoning
EWCBR '98 Proceedings of the 4th European Workshop on Advances in Case-Based Reasoning
Activating CBR Systems Through Autonomous Information Gathering
ICCBR '99 Proceedings of the Third International Conference on Case-Based Reasoning and Development
An Engineering Approach for Troubleshooting Case Bases
ICCBR '97 Proceedings of the Second International Conference on Case-Based Reasoning Research and Development
Induction in an abstraction space: a form of constructive induction
IJCAI'89 Proceedings of the 11th international joint conference on Artificial intelligence - Volume 1
Stratified case-based reasoning: reusing hierarchical problem solving episodes
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Exploiting Taxonomic and Causal Relations in Conversational Case Retrieval
ECCBR '02 Proceedings of the 6th European Conference on Advances in Case-Based Reasoning
A knowledge-intensive method for conversational CBR
ICCBR'05 Proceedings of the 6th international conference on Case-Based Reasoning Research and Development
Supporting generalized cases in conversational CBR
MICAI'05 Proceedings of the 4th Mexican international conference on Advances in Artificial Intelligence
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Conversational Case-Based Reasoning (CCBR) systems engage a user in a series of questions and answers to retrieve cases that solve his/her current problem. Help-desk and interactive troubleshooting systems are among the most popular implementations of the CCBR methodology. As in traditional CBR systems, features in a CCBR system can be expressed at varying levels of abstraction. In this paper, we identify the sources of abstraction and argue that they are uncontrollable in applications typically targeted by CCBR systems. We contend that ignoring abstraction in CCBR can cause representational inconsistencies, adversely affect retrieval and conversation performance, and lead to case indexing and maintenance problems. We propose an integrated methodology called Taxonomic CCBR that uses feature taxonomies for handling abstraction to correct these problems. We describe the benefits and limitations of our approach and examine issues for future research.