基于聚类和互事务的双策略分析模型

F. Sun, Yonggong Ren, Yanyan Qi
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引用次数: 0

摘要

事务间关联规则挖掘主要用于挖掘不同事务之间的重要关联,但现有算法只注重效率或准确性。本文提出了基于聚类和双策略分析模型的事务间关联规则算法。算法采用双策略利益模型来判断事务间关联规则的完整性,弥补了挖掘漏洞,避免了错误规则的产生,提高了挖掘算法的质量;并利用聚类分析去除数据库中的大量冗余数据,提高了算法的效率。实验结果表明,该算法提高了事务间关联规则算法的准确性和效率。关键词:双策略利益模型;聚类分析;马尔可夫模型
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Dual-strategy Analysis Model Based on Clustering and Inter-transaction
Inter-transactional association rules mining is mainly used in mining significant association between different transaction, but the existing algorithm only focus on the efficiency or accuracy. In this study, we propose the inter-transactional association rules algorithm based on cluster and dual-strategy analysis model. The algorithm adopts dual-strategy interest model to judge the integrity of the inter-transactional association rules, make up for mining bugs, avoid the generation of false rules, improve the quality of the mining algorithm; And use of cluster analysis to remove a large number of redundant data in database, improve the efficiency of the algorithm. The experimental results show that the proposed algorithm improves accuracy and efficiency of inter-transactional association rules algorithm. Keywords-Dual-strategy interest model;cluster analysis;Markov model
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