Effective Mining of Weighted Fuzzy Association Rules
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چکیده
Association rules (ARs) (Agrawal, Imielinski & Swami, 1993) are a well established data mining technique used to discover co-occurrences of items mainly in market basket data. An item is usually a product amongst a list of other products and an itemset is a combination of two or more products. The items in the database are usually recorded as binary data (present or not present). The technique aims to find association rules (with strong support and high confidence) in large databases. Classical Association Rule Mining (ARM) deals with the relationships among the items present in transactional databases (Agrawal & Srikant, 1994; Bodon, 2003). Typically, the algorithm first generates all large (frequent) itemsets (attribute sets) from which association rule (AR) sets are derived. A ABSTRACT
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تاریخ انتشار 2009