Mining Class Association Rules with Synthesis Constraints

被引:1
|
作者
Nguyen, Loan T. T. [1 ,2 ]
Bay Vo [3 ]
Hung Son Nguyen [2 ]
Sinh Hoa Nguyen [4 ]
机构
[1] Nguyen Tat Thanh Univ, Fac Informat Technol, Ho Chi Minh City, Vietnam
[2] Univ Warsaw, Fac Math Informat & Mech, Warsaw, Poland
[3] Ho Chi Minh City Univ Technol, Fac Informat Technol, Ho Chi Minh City, Vietnam
[4] Polish Japanese Acad Informat Technol, Warsaw, Poland
关键词
Data mining; Class association rules; Left constraint; Right constraint; Synthesis constraints; ALGORITHM;
D O I
10.1007/978-3-319-54472-4_52
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Constraint-based methods for mining class association rules (CARs) have been developed in recent years. Currently, there are two kinds of constraints including itemset constraints and class constraints. In this paper, we solve the problem of combination of class constraints and itemset constraints are called synthesis constraints. It is done by applying class constraints and removing rules that do not satisfy itemset constraints after that. This process will consume more time when the number of rules is large. Therefore, we propose a method to mine all rules satisfying these two constraints by one-step, i.e., we will put these two constraints in the process of mining CARs. The lattice is also used to fast generate CARs. Experimental results show that our approach is more efficient than mining CARs using two steps.
引用
收藏
页码:556 / 565
页数:10
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