Case-based reasoning using dominance-based decision rules

M. Szelag, Salvatore Greco, J. Blaszczynski, R. Slowinski

    Research output: Chapter in Book/Report/Conference proceedingChapter (peer-reviewed)peer-review

    Abstract

    Case-based Reasoning (CBR) is a process of inferring conclusions related to a new situation by the analysis of similar cases known from the past experience. We propose to adopt in this process the Dominance-based Rough Set Approach (DRSA), that is able to handle monotonicity relationships of the type "the more similar is object y to object x with respect to the considered features, the closer is y to x in terms of the membership to a given fuzzy set X". At the level of marginal similarity concerning single features, we consider this similarity in ordinal terms only. The marginal similarities are aggregated within decision rules underlying the general monotonicity property of comprehensive closeness of objects with respect to their marginal similarities.
    Original languageEnglish
    Title of host publicationRough sets and knowledge technology: proceedings of the 6th international conference
    EditorsJ. Yao, S. Ramanna, G. Wang, Z. Suraj
    Place of PublicationBerlin
    PublisherSpringer
    Pages404-413
    Number of pages10
    Volume6954
    Edition9654
    ISBN (Print)9783642244247
    DOIs
    Publication statusPublished - Oct 2011

    Publication series

    NameLecture notes in computer science
    PublisherSpringer
    Number9654
    ISSN (Print)0302-9743

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