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On a Mathematical Relationship Between the Fixed Point and the Closed Itemset in Association Rule Mining

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AI 2005: Advances in Artificial Intelligence (AI 2005)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3809))

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Abstract

Association rule mining is one of important research topics in knowledge discovery and data mining. Recent promising direction of association rule mining is mainly to mine closed itemsets. Based on the Galois closed operators, a mathematical relationship between the fixed point and closed itemset in association rule mining is discussed and several properties are obtained. To mine all frequent closed itemsets is equal to build the fixed point lattice and mine its all points that satisfy support constraints. A new method for visualization of association rules based on the generalized association rule base is also proposed.

This work was partially supported by the National Natural Science Foundation of China (NSFC) under the grant No. 60474022.

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Authors and Affiliations

  1. Department of Mathematics, School of Science, Southwest Jiaotong University, Chengdu, 610031, P.R. China

    Tian-rui Li, Tianmin Huang & Yang Xu

  2. The Belgian Nuclear Research Centre (SCK∙CEN), Boeretang 200, B-2400, Mol, Belgium

    Tian-rui Li & Da Ruan

Authors
  1. Tian-rui Li
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  2. Da Ruan
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  3. Tianmin Huang
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  4. Yang Xu
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Editor information

Editors and Affiliations

  1. Guangxi Normal University, College of CS and IT, Guilin, China, and University of Technology, Faculty of Engineering and Information Technology, Sydney, Australia

    Shichao Zhang

  2. Department of Electrical and Computer Systems Engineering, Monash University, 3800, Melbourne, Victoria, Australia

    Ray Jarvis

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© 2005 Springer-Verlag Berlin Heidelberg

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Li, Tr., Ruan, D., Huang, T., Xu, Y. (2005). On a Mathematical Relationship Between the Fixed Point and the Closed Itemset in Association Rule Mining. In: Zhang, S., Jarvis, R. (eds) AI 2005: Advances in Artificial Intelligence. AI 2005. Lecture Notes in Computer Science(), vol 3809. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11589990_126

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  • DOI: https://doi.org/10.1007/11589990_126

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-30462-3

  • Online ISBN: 978-3-540-31652-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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