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客户时序关联规则挖掘方法研究

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Keywords: 客户,时序关联规则,前缀映射累加树

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Abstract:

针对客户交易数据的特点,提出了一种基于前缀映射累加树的客户时序关联规则发现方法。将时间窗口内频繁项的信息映射到前缀映射累加树中,以降低频繁时序模式的搜索空间,提高时序关联规则的挖掘效率。另外,通过为特定的频繁项建立前缀映射累加树,可以挖掘特定的时序关联规则,并能以较精确的方式,发现具有一定模糊性的客户时序关联规则。实验结果表明,所提出的方法能够提高客户时序关联规则的挖掘效率。

References

[1]  ??WANG Fudong, LI Bing, XUE Jinsong, et al. Constraint-based association rule mining in CRM[J]. Computer Integrated Manufacturing Systems, 2004, 10(4):465-470 (in Chinese).[王扶东,李??兵,薛劲松,等.客户关系管理中基于约束的关联规则挖掘方法研究[J]. 计算机集成制造系统, 2004, 10(4): 465-470.]
[2]  ??DAS G, LIN K, MANNILA H, et al. Rule discovery from time series[A]. Proceedings of the 4th International Conference on Knowledge Discovery and Data Mining [C]. New York, NY,USA: AAAI Press, 1998. 16-22.
[3]  ??MANNILA H, TOIVONEN H, VERKAMO A I. Discovering frequent episodes in sequences[A].Proceedings of the 1st International Conference on Knowledge Discovery and Data Mining [C]. Montreal, Canada: AAAI Press, 1995. 210-215.
[4]  ??MANNILA H, TOIVONEN H. Discovering generalized episodes using minimal occurrences[A]. Proceedings of the 2nd International Conference on Knowledge Discovery and Data Mining [C].Menlo Park,CA,USA:AAAI Press, 1996. 146-151.
[5]  ??MANNILA H, TOIVONEN H, VERKAMO I A. Discovery of Frequent Episodes in Event Sequences[J]. Data Mining and Knowledge Discovery, 1997, 1(3): 259-289.
[6]  ??FENG L, LU H, YU J X,et al. Mining Inter-Transaction Associations with Templates[A]. Proceedings of the 8th International Conference on Information and Knowledge Management[C]. Kansas City,MO, USA:ACM Press, 1999. 225-233.
[7]  ??LU H, HAN J, FENG L. Stock movement prediction and N-dimensional inter-transaction association rules[A]. Proceedings of the ACM SIGMOD Workshop on Research Issues in Data Mining and Knowledge Discovery[C]. Seattle, WA, USA: ACM Press, 1998. 1-7.
[8]  ??RAINSFORD C P. Accommodating temporal semantics in data mining and knowledge discovery[D].Adelaide,South Australia,Australia: School of Computer and Information Science Faculty of Information Technology University of South Australia, 1999. 50-80.
[9]  ??HIPP J, GüNTZER U, NAKHAEIZADEH G. Algorithms for association rule mining-a general survey and comparison[J]. SIGKDD Explorations, 2000, 2(1): 58-64.

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