A Model-Based Frequency Constraint for Mining Associations from Transaction Data
作者:Michael Hahsler
摘要
Mining frequent itemsets is a popular method for finding associated items in databases. For this method, support, the co-occurrence frequency of the items which form an association, is used as the primary indicator of the associations's significance. A single, user-specified support threshold is used to decided if associations should be further investigated. Support has some known problems with rare items, favors shorter itemsets and sometimes produces misleading associations.
论文关键词:Data mining, associations, interest measures, mixture models, transaction data
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论文官网地址:https://doi.org/10.1007/s10618-005-0026-2