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Study on the Application of Multi-level Association Rules Based on Granular Computing

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3 Author(s)
Yanguang Shen ; Sch. of Inf. & Electron. Eng., Hebei Univ. of Eng., Handan, China ; Jing Shen ; Yongjian Fan

For the issue that classical association rules can not mine multi-level association rules, we proposed a multi-level association rule mining method based on binary information granules in granular computing and multiple minimum supports, and gave the definition of the support and confidence based on binary information granules. In this new association rules method, we can reduce the generation search space of frequent itemsets, extract multi-level association information(including cross-level information), and find more effective rules.

Published in:

Intelligent Computation Technology and Automation (ICICTA), 2010 International Conference on  (Volume:3 )

Date of Conference:

11-12 May 2010