4 research outputs found

    Adaptation Knowledge Discovery from a Case Base

    Get PDF
    In case-based reasoning, the adaptation step depends in general on domain-dependent knowledge, which motivates studies on adaptation knowledge acquisition (AKA). CABAMAKA is an AKA system based on principles of knowledge discovery from databases. This system explores the variations within the case base to elicit adaptation knowledge. It has been successfully tested in an application of case-based decision support to breast cancer treatment

    Adaptation Knowledge Discovery from a Case Base

    Get PDF
    In case-based reasoning, the adaptation step depends in general on domain-dependent knowledge, which motivates studies on adaptation knowledge acquisition (AKA). CABAMAKA is an AKA system based on principles of knowledge discovery from databases. This system explores the variations within the case base to elicit adaptation knowledge. It has been successfully tested in an application of case-based decision support to breast cancer treatment

    Extracting Generic Cooking Adaptation Knowledge for the TAAABLE Case-Based Reasoning System

    Get PDF
    International audienceThis paper addresses the issue of interactive adaptation knowledge acquisition. It shows how the expert's involvement in this process can improve the quality and usefulness of the results. The approach is defended in the context of \taaable, a \cbr system which adapts recipes to user needs. In \taaable, adaptation knowledge takes the form of substitutions. A datamining process allows the discovery of specific substitutions in recipes. A second process, that must be driven by an expert, is needed to generalise these substitutions to make them usable on other recipes. For that, we defend an approach based on closed itemsets (CIs) for extracting generic substitutions starting from specific ones. We focus on a restrictive selection of objects, on a specific filtering on the form of the CIs and on a specific ranking on support and stability of the CIs. Experimentations demonstrate the feasibility of our approach and show some first results
    corecore