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Mining Class Association Rules with Synthesis Constraints

Autor
Nguyen, Loan TT
Nguyen, Hung Son
Vo, Bay
Nguyen, Thi Sinh Hoa
Data publikacji
2017
Abstrakt (EN)

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.

Słowa kluczowe EN
Data mining
Class association rules
Left constraint
Right constraint
Synthesis constraints
Dyscyplina PBN
informatyka
Strony od-do
556-565
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