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A New Association Rule Mining Algorithm Based on Compression Matrix

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Computer Engineering and Networking

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 277))

Abstract

A new association rule mining algorithm based on matrix is introduced. It mainly compresses the transaction matrix efficiently by integrating various strategies. The new algorithm optimizes the known association rule mining algorithms based on matrix given by some researchers in recent years, which greatly reduces the temporal complexity and spatial complexity, and highly promotes the efficiency of association rule mining. It is especially feasible when the degree of the frequent itemset is high.

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References

  1. Agrawal, R., Imielinski, T., & Wami, A. S. (1993). Mining association rules between sets of items in large databases (pp. 207–216). Proceeding of the ACM SIGMOD Conference on Management of Data, Washington, DC.

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  2. Lv, T. X., & Liu, P. Y. (2011). Algorithm for generating strong association rules based on matrix. Application Research of Computers, 28(4), 1301–1303.

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  3. Cao, F. H. (2012). Improved association rule mining algorithm based on two matrixes. Electronic Science and Technology, 25(5), 126–128.

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  4. Xu, H. Z. (2012). The research of association rules data mining algorithms. Science Technology and Engineering, 12(1), 60–63.

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  5. He, B., & Xue, F. (2012). An improved algorithm for mining association rules. Computer Knowledge and Technology, 8(5), 1015–1017.

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Acknowledgment

This work is financially supported by the Natural Science Foundation of the Jiangxi Province of China under Grant No. 20122BAB201004.

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Authors and Affiliations

  1. College of Mathematics and Computer Science, Jiangxi Science and Technology Normal University,, Nanchang, 330000, China

    Sihui Shu

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  1. Sihui Shu
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Correspondence to Sihui Shu .

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Editors and Affiliations

  1. University of Texas at Dallas, Richardson, Texas, USA

    W. Eric Wong

  2. Chinese Academy of Sciences, Beijing, China, People’s Republic

    Tingshao Zhu

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© 2014 Springer International Publishing Switzerland

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Shu, S. (2014). A New Association Rule Mining Algorithm Based on Compression Matrix. In: Wong, W.E., Zhu, T. (eds) Computer Engineering and Networking. Lecture Notes in Electrical Engineering, vol 277. Springer, Cham. https://doi.org/10.1007/978-3-319-01766-2_33

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  • DOI: https://doi.org/10.1007/978-3-319-01766-2_33

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-01765-5

  • Online ISBN: 978-3-319-01766-2

  • eBook Packages: EngineeringEngineering (R0)

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