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A New Approach of Self-adaptive Discretization to Enhance the Apriori Quantitative Association Rule Mining

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4 Author(s)
Li Dancheng ; Northeastern Univ., Shenyang, China ; Zhang Ming ; Zhou Shuangshuang ; Zheng Chen

Apriori algorithm was widely applied in association rule mining. Generally, we have to specify different ranges manually to discretize numeral fields to nominal fields, which may weaken the result due to unfit partitions. This paper introduced an approach to make discretized partitions in a self adaptive way to enhance the numeral quantitative association rule mining result.

Published in:

Intelligent System Design and Engineering Application (ISDEA), 2012 Second International Conference on

Date of Conference:

6-7 Jan. 2012