Generalized Association Rule Base Mining and Its Algorithm
Association rule mining is one of the most important research areas in data mining. Yet there exist two big problems in process of acquiring rule by traditional mining algorithms, i.e., the quantity and the quality of rule. Presently there are many methods focus on resolving these two problems. Although these methods can reduce the amount of rules derived to some extent, but the total number is too big as ever. In this paper, we first propose the notations of upper closed itemset and generalized association rule base, and obtain a generalized association rule base of a database, which not only contains the whole information of all association rules, but also has conform structure that is convenient for practical applications. Also, We propose a mining algorithm of generalized association rule base. From our propositions and example, the algorithm is shown valid and can efficiently solve the problem of quantity of rule.
data mining upper closed itemset generalized association rule base
Tian-rui LI Yu-qi NIU Jun MA Yang XU
Department of mathematics, School of Science, Southwest Jiaotong University, Chengdu, 610031, China Department of mathematics, Xuchang University, Xuchang, 461000, China School of Electric Engineering, Southwest Jiaotong University, Chengdu, 610031, China
国际会议
成都
英文
919-922
2003-08-27（万方平台首次上网日期，不代表论文的发表时间）