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Mining Class Association Rules with Synthesis Constraints

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Intelligent Information and Database Systems (ACIIDS 2017)

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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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This work was carried out during the tenure of an ERCIM ‘Alain Bensoussan’ Fellowship Programme.

This research is funded by NTTU Foundation for Science and Technology Development.

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Correspondence to Loan T. T. Nguyen .

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Nguyen, L.T.T., Vo, B., Nguyen, H.S., Nguyen, S.H. (2017). Mining Class Association Rules with Synthesis Constraints. In: Nguyen, N., Tojo, S., Nguyen, L., Trawiński, B. (eds) Intelligent Information and Database Systems. ACIIDS 2017. Lecture Notes in Computer Science(), vol 10191. Springer, Cham.

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  • Print ISBN: 978-3-319-54471-7

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