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2017 | OriginalPaper | Buchkapitel

Mining Class Association Rules with Synthesis Constraints

verfasst von : Loan T. T. Nguyen, Bay Vo, Hung Son Nguyen, Sinh Hoa Nguyen

Erschienen in: Intelligent Information and Database Systems

Verlag: Springer International Publishing

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Abstract

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.

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Vorheriges Kapitel Mining Periodic High Utility Sequential Patterns

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Titel: Mining Class Association Rules with Synthesis Constraints
verfasst von: Loan T. T. Nguyen
Bay Vo
Hung Son Nguyen
Sinh Hoa Nguyen
Verlag: Springer International Publishing
Buch: Intelligent Information and Database Systems
Print ISBN: 978-3-319-54471-7

Electronic ISBN: 978-3-319-54472-4

Copyright-Jahr: 2017
DOI: https://doi.org/10.1007/978-3-319-54472-4_52

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