Fuzzy data mining: a literature survey and classification framework
International Journal of Networking and Virtual Organisations
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Aiming at the problem of the incisive boundary for mining association rules about quantative data using algorithm about boolean data, this paper gives a series of definitions of fuzzy association rules and proposes a mining algorithm based on prefix tree indexed on support for fuzzy association rules. The algorithm can store fuzzy pattern candidate sets and frequent sets compressibly by constructing prefix tree, which effectively saves the memory cost, besides it only scans database twice. The efficiency of the algorithm is verified by the experiment of evaluating water quality.