Gaining insight through case-based explanation

Conor Nugent, Dónal Doyle, Pádraig Cunningham
2008 Journal of Intelligent Information Systems  
Because CBR is an interpretable process, it is a reasoning mechanism that supports explanation. This can be done explicitly by the system designers incorporating explanation patterns in cases. This can be termed knowledge-intensive explanation in CBR. However, of more interest here is case-based explanation that works by allowing users to consider the relation between different cases. The recommendation of a decision support system can be explained by presenting similar cases that motivate the
more » ... ecommendation. Users can derive insight from similar cases that have different outcomes. The differences in outcome are due to the differences in the un-matching features (provided the effect is not due to noisy data). This is a more knowledge-light approach to case-based explanation. This is appropriate for weak-theory domains where the details of the causal interactions in the domain are not well understood; experts would however be able to express the direction of causal interactions. In this paper we present such a knowledge-light framework for Case-Based Explanation.
doi:10.1007/s10844-008-0069-0 fatcat:fwz4j3fbtbd5la24r3bjlrckoy