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ABSTRACT
Association rule mining is a key issue in data mining. However the classical models ignore the difference between the transactions; and the weighted association rule mining does not work on databases with only binary attributes. In this paper, we introduce a new measure wsupport, which does not require pre-assigned weights. It takes the quality of transactions into consideration, using link-based models. A fast miming algorithm is given and a large amount of experimental results is presented.
INDEX TERMS
Data mining, Clustering, classification, and association rules
CITATION
Ke Sun, Fengshan Bai, "Mining Weighted Association Rules without Preassigned Weights", IEEE Transactions on Knowledge & Data Engineering, vol. 20, no. , pp. 489-495, April 2008, doi:10.1109/TKDE.2007.190723
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