基于强相关的改进数据挖掘算法研究

Chun-hong Hu, Zhengqiang Wang
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摘要

关联规则在商业中的广泛应用使其成为数据挖掘中最活跃的研究方向之一。近年来,事务数据库中具有统计显著性的强相关项对的挖掘得到了一定的重视。为了进一步降低关系数据库中候选项对的测试成本,我们根据1NF的特性开发了锥算法。提出的TaperR算法可以减少候选对的数量,提高效率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Research on Improved Data-Mining Algorithm Based on Strong Correlation
The extensive application of association rules in commerce enables itself to be one of the most active research directions in data mining. Recently, the mining of strong correlation item pairs with statistical significance in transaction database receives a certain value. In order to further reduce the cost of testing candidate item pairs in relational database, we have developed the Taper algorithm according to 1NF property. The developed TaperR algorithm can cut the number of candidate pairs to improve effciency.
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