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An effective association rule mining scheme using a new generic basis

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Abstract

Association rule mining among itemsets is a fundamental task and is of great importance in many data mining applications including attacks in network data, stock market, financial applications, bioinformatics to find genetic disorders, etc. However, association rule extraction from a reasonable-sized database produces a large number of rules. As a result, many of them are redundant to other rules, and they are practically useless. To overcome this issue, methods for mining non-redundant rules are essentially required. To address such problem, we initially propose a definition for redundancy in sense of minimal knowledge and then a compact representation of non-redundant association rules which we call as compact informative generic basis. We also provide an improved version of the existing DCI_CLOSED algorithm (DCI_PLUS) to find out the frequent closed itemsets (FCI) with their minimal representative generators in combination with BitTable which represents a compact database form in a single scan of the original database. We further introduce an algorithm for constructing the compact informative generic basis from the FCI and their generators in an efficient way. We finally present an inference mechanism in which all association rules can be generated without accessing the database. Experiments are performed on the proposed method. The experimental results show that the proposed method outperforms the other existing related methods.

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Acknowledgments

The authors would like to thank the anonymous reviewers, the Editor and the Editor-in-Chief for providing constructive and generous feedbacks, which have improved significantly the content, quality and the presentation of this paper.

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Authors and Affiliations

  1. Department of Mathematics, Indian Institute of Technology, Kharagpur , 721 302, India

    Jayakrushna Sahoo & A. Goswami

  2. Center for Security, Theory and Algorithmic Research, International Institute of Information Technology, Hyderabad , 500 032, India

    Ashok Kumar Das

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  1. Jayakrushna Sahoo
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  3. A. Goswami
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Correspondence to A. Goswami.

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Sahoo, J., Das, A.K. & Goswami, A. An effective association rule mining scheme using a new generic basis. Knowl Inf Syst 43, 127–156 (2015). https://doi.org/10.1007/s10115-014-0732-4

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