基于多最小支持度的加权关联规则挖掘算法

邹力鹍; 张其善

基于多最小支持度的加权关联规则挖掘算法

北京航空航天大学电子信息工程学院, 北京 100083

基金项目: 航空基金资助项目(2006ZC51032); 863资助项目(2006AA701424)

详细信息

作者简介:
邹力鹍(1977-),女,湖南新化人,博士生,likun_zou@163.com

中图分类号: TP 312
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- 被引次数: 0
出版历程
- 收稿日期: 2006-07-03
- 网络出版日期: 2007-05-31

Algorithm of weighted association rules mining with multiple minimum supports

School of Electronics and Information Engineering, Beijing University of Aeronautics and Astronautics, Beijing 100083, China

摘要

摘要: 针对交易数据库中数据项重要性不同的现象,提出了新的加权关联规则模型,并基于该模型设计了一个基于多最小支持度的加权关联规则挖掘新算法,允许用户设定多个最小支持度,为数据项设置不同的权重,从而解决数据项的重要性各不相同且出现频率不均匀的问题,发现更多有趣的规则.理论证明了相关性质,并实验验证了算法的有效性.
- 数据挖掘 /
- 加权关联规则 /
- 多支持度
Abstract: A new model of weighted association rule was presented in order to solve the problem that data item have not the same importance in datasets. Based on this model, a new algorithm of mining weighted association rules with multiple minimum supports was proposed. The algorithm allows the user to specify varied minimum supports and items weights to reflect the importance and frequency of each data item in datasets .The algorithm aims to deal with problem that items have different importance and varied frequency in transaction database and find more interesting rules which involve both frequent and rare items. The correlative properties of model and algorithm were given and the theories were proved. Finally, the algorithm was tested on the experimental data. Experiment results show that the new algorithm is effective for large databases.
- data mining /
- weighted association rule /
- multiple minimum supports

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参考文献(1)

[1] Agrawal R, Imielinski T, Swami A. Mining association rules between sets of items in large databases Proceedings of the 1993 ACM SIGMOD. Washington:ACM SIGMOD,1993 :207-216 [2] Jiawei Han, Jian Pei, Yiwen Yin. Mining frequent patterns without candidate generation Proceedings of the 19th ACM SIGMOD. Dallas, TX, USA:ACM SIGMOD,2000:1-12 [3] 欧阳为民,郑诚,蔡庆生.数据库中加权关联规则的发展[J]. 软件学报,2001,12(4):612-619 Ouyang Weimin, Zheng Cheng, Cai Qingsheng. Discovery of weighted association rules in databases[J]. Journal of Software,2001,12(4):612-619(in Chinese) [4] Cai C H, Fu Ada W C, Cheng C H, et al. Ming association rules with weighted items IEEE In Database Engineering and Applications Symposium. Cardiff:ACM SIGMOD,1998:68-77 [5] Feng Tao, Fionn Murtagh, Mohsen Farid. Weighted association rule mining using weighted support and significance framework Proceedings of the 2003 ACM SIGKDD. Washington, DC, USA:ACM SIGMOD, 2003:661-666 [6] Bing Liu,Hsu W, Ma Y . Mining association rules with multiple minimum supports Proceedings of the 1999 ACM SIGKDD. SanDiego,CA:ACM SIGMOD,1999:337-351 [7] 王振宇,白石磊,熊范纶.多最小支持度策略的关联规则挖掘方法[J].小微型计算机系统,2002,23(8):971-973 Wang Zhenyu, Bai Shilei, Xiong Fanlun. An approach of mining association rules with multiple minimum supports stratagem[J]. Mini Microsystem, 2002,23(8):971-973(in Chinese) [8] 段军,戴居丰.基于多支持度的挖掘加权关联规则算法[J].天津大学学报,2006,39(1):114-118 Duan Jun, Dai Jufeng. Algorithm of mining weighted association rules based on multiple supports[J].Journal of Tianjin University,2006,39(1):114-118(in Chinese)

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