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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
Citation:
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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