Conversational Case-Based Reasoning
Applied Intelligence
Interactive Case-Based Reasoning in Sequential Diagnosis
Applied Intelligence
Introduction to the Special Issue on Explanation in Case-Based Reasoning
Artificial Intelligence Review
Advances in conversational case-based reasoning
The Knowledge Engineering Review
Medical applications in case-based reasoning
The Knowledge Engineering Review
Conversational Case-Based Reasoning in Self-healing and Recovery
ECCBR '08 Proceedings of the 9th European conference on Advances in Case-Based Reasoning
minimizing dialog length in interactive case-based reasoning
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 2
Evaluating CBR systems using different data sources: a case study
ECCBR'06 Proceedings of the 8th European conference on Advances in Case-Based Reasoning
What evaluation criteria are right for CCBR? considering rank quality
ECCBR'06 Proceedings of the 8th European conference on Advances in Case-Based Reasoning
Knowledge discovery approach to automated cardiac SPECT diagnosis
Artificial Intelligence in Medicine
A novel case based reasoning approach to radiotherapy planning
Expert Systems with Applications: An International Journal
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In case-based reasoning (CBR) approaches to classification and diagnosis, a description of the problem to be solved is often assumed to be available in advance. Conversational CBR (CCBR) is a more interactive approach in which the system is expected to play an active role in the selection of relevant tests to help minimize the number of problem features that the user needs to provide. We present a new algorithm for CCBR called iNN(k ) and demonstrate its ability to achieve high levels of accuracy on a selection of datasets related to medicine and health care, while often requiring the user to provide only a small subset of the problem features required by a standard k -NN classifier. Another important benefit of iNN(k ) is a goal-driven approach to feature selection that enables a CCBR system to explain the relevance of any question it asks the user in terms of its current goal.