基于领域知识和聚类的关联规则深层知识发现研究

doi:10.16381/j.cnki.issn1003-207x.2015.02.019

Abstract

Abstract: Second mining of the result of association rule mining is proposed in solution of the large numbers of redundant rules in the traditional association rules mining algorithm, and the algorithm for clustering of association rules is designed, then the novelty of the association rules is assessed after clustering based on the existing domain knowledge. It is insited that the association rules with more novelty and higher value can be stored in the domain knowledge base, and can be used for the decision or mining again. The algorithm proposed in this paper is effective to reduce the number of rules and also help to improve the novelty and precision of rule, which has a very high value for business applications. Finally the open source data from UCI is used to carry on the experiment to verify the effectiveness of the algorithm.

Key words: association rule, clustering, domain knowledge, post-processing

CLC Number:

ZHANG Ling-ling, ZHOU Quan-liang, TANG Guang-wen, LI Xing-sen, SHI Yong. Research on Algorithm of Post-processing Association Rules Based on Clustering and Domain Knowledge[J]. Chinese Journal of Management Science, 2015, 23(2): 154-161.

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Research on Algorithm of Post-processing Association Rules Based on Clustering and Domain Knowledge

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