Mining multilevel association rules with dynamic concept hierarchy

Yin Bo Wan, Yong Liang, Li Ya Ding

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Citations (Scopus)

Abstract

Association rule mining has attracted wide attention in both research and application areas recently. The mining of multilevel association rules is one of the important branches of it. In most of the studies, multilevel rules will be mined through repeated mining from databases or mining the rules at each individually levels, it affects the efficiency, integrality and accuracy. In this paper, a novel method is proposed to improve this situation by analyzing the rules mined from primitive concept level to obtain multilevel rules. The proposed method also supports dynamic concept hierarchies.

Original languageEnglish
Title of host publicationProceedings of the 7th International Conference on Machine Learning and Cybernetics, ICMLC
Pages287-292
Number of pages6
DOIs
Publication statusPublished - 25 Dec 2008
Event7th International Conference on Machine Learning and Cybernetics, ICMLC - Kunming, China
Duration: 12 Jul 200815 Jul 2008

Publication series

NameProceedings of the 7th International Conference on Machine Learning and Cybernetics, ICMLC
Volume1

Conference

Conference7th International Conference on Machine Learning and Cybernetics, ICMLC
CountryChina
CityKunming
Period12/07/0815/07/08

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Keywords

  • Association rules
  • Concept hierarchy
  • FP-tree
  • Multi-level association rules
  • Rule mining

Cite this

Wan, Y. B., Liang, Y., & Ding, L. Y. (2008). Mining multilevel association rules with dynamic concept hierarchy. In Proceedings of the 7th International Conference on Machine Learning and Cybernetics, ICMLC (pp. 287-292). [4620419] (Proceedings of the 7th International Conference on Machine Learning and Cybernetics, ICMLC; Vol. 1). https://doi.org/10.1109/ICMLC.2008.4620419