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Mining Weighted Association Rules without Preassigned Weights
April 2008 (vol. 20 no. 4)
pp. 489-495
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.

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Index Terms:
Data mining, Clustering, classification, and association rules
Ke Sun, Fengshan Bai, "Mining Weighted Association Rules without Preassigned Weights," IEEE Transactions on Knowledge and Data Engineering, vol. 20, no. 4, pp. 489-495, April 2008, doi:10.1109/TKDE.2007.190723
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