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Survey on Association Rules Mining Algorithms

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Advancing Computing, Communication, Control and Management

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 56))

Abstract

In recent years, the association rule mining as an important component of data mining attracts many attentions. Up to now, there are many literatures on the association rules, scholars study the association rules mining deeply from improving the algorithm to proposing a new perspective, and thus, there is a great development in the field. In this paper, we perform a high-level overview of association rules mining methods, extensions and we also put forward some suggestions of the research in the future. With a rich body of literature on this theme, we organize our discussion into the following four themes: improving the algorithms to increase mining efficiency, proposing new algorithm to extend the notion of association rules, the integration of association rules and classification, the research on parameter such as support and confidence.

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Authors and Affiliations

  1. Sichuan university, Chengdu, China

    Mingzhu Zhang & Changzheng He

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  1. Mingzhu Zhang
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  2. Changzheng He
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Editors and Affiliations

  1. School of Electrical Engineering, Wuhan Institute of Technology , 430070, Wuhan, China

    Qi Luo

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© 2010 Springer-Verlag Berlin Heidelberg

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Zhang, M., He, C. (2010). Survey on Association Rules Mining Algorithms. In: Luo, Q. (eds) Advancing Computing, Communication, Control and Management. Lecture Notes in Electrical Engineering, vol 56. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-05173-9_15

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  • DOI: https://doi.org/10.1007/978-3-642-05173-9_15

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-05172-2

  • Online ISBN: 978-3-642-05173-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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