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Highlights: [•] Introduction of a metric for estimating dissimilarities among items’ attributes. [•] Introduction of a recommender which bases its rating estimations on dissimilarities. [•] A framework which combines recommenders with the dissimilarity recommender. [ABSTRACT FROM AUTHOR]

Abstract: We introduce a framework for mining event related dynamics based on conditional FCM (CFCM). For a given set of responses, the variation in the data is summarized by means of a small set of meaningful prototypes accompanied with a low-dimensional graph capturing their relative relationships. CFCM enables prototyping in a principled manner. User-defined constraints, which are imposed by the nature of experimental data and/or dictated by the neuroscientist''s intuition, direct the process of knowledge extraction and can robustify single-trial analysis. The method is introduced using simulated data and demonstrated using actual encephalographic data. [Copyright &y& Elsevier]