On discovery of soft associations with "most" fuzzy quantifier for item promotion applications
Information Sciences: an International Journal
Refinement of temporal constraints in fuzzy associations
International Journal of Approximate Reasoning
Proceedings of the 20th international conference companion on World wide web
Fuzzy machine learning and data mininga
Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery
FAR-miner: a fast and efficient algorithm for fuzzy association rule mining
International Journal of Business Intelligence and Data Mining
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This short correspondence is a reply to a recently published paper by Verlinde et al. (2006) in which the authors empirically compared fuzzy and nonfuzzy association analysis and, on the basis of their results, questioned the usefulness of a fuzzy approach. Although we highly welcome the critical examination of the topic and definitely agree that fuzzy extensions of existing methods call for a thorough justification, the empirical comparison presented in the aforementioned paper is in our opinion not objective and extensive enough to fully warrant the conclusions drawn from the results. Apart from some general comments on the claims raised in their paper, we present empirical results based on an alternative experimental setup that lead to different conclusions.