Abstract
The association rule mining is an important topic in recent data mining research. In this paper, a new association rule mining method based on the multiple-dimensional item attributes is proposed through the Market Basket Analysis. The corresponding average weight support is defined, and the AWMAR algorithm is described in detail. Finally, the performance study and results analysis of the improved algorithm is presented. AWMAR algorithm is effective for mining the association rules with acceptable running time.
This work is supported by the NKBRSF of China (973) under grant No.G1999032705, the National ‘863’ High-Tech Program of China under grant No. 2002AA4Z3440.
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Duan, Y., Shiwei, T., Dongqing, Y., Song, M. (2004). Association Rule Mining Based on the Multiple-Dimensional Item Attributes. In: Wang, S., et al. Conceptual Modeling for Advanced Application Domains. ER 2004. Lecture Notes in Computer Science, vol 3289. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30466-1_24
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DOI: https://doi.org/10.1007/978-3-540-30466-1_24
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-23722-8
Online ISBN: 978-3-540-30466-1
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