Associate rule minimization using boolean algebra set function

Pornsak Deekumpa, P. Sooraksa
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引用次数: 4

Abstract

Associated rule mining has become a common subject in data mining research field that is very popular used for marketing basket analysis. The discovery knowledge pattern mined can provide insight to the data holder as well as be invaluable in important task, such as decision making and strategic planning. This paper presents an associated rule mining technique that significantly helping for improvement of the decision making or planning. As a minimization mining strategy, we adopt the minimization using algebra set function and association rule mining methods. Our goal is to minimize the number of associated rule. This paper is of reviews preliminaries method presented a minimization algorithm and also tested with the well known data. The experimental results also show that our algorithm is an efficient method one.
关联规则最小化使用布尔代数集函数
关联规则挖掘已经成为数据挖掘研究领域的一个常见课题,在市场购物篮分析中得到了广泛的应用。挖掘出的发现知识模式不仅可以为数据持有者提供洞察,而且在决策制定和战略规划等重要任务中具有不可估量的价值。本文提出了一种相关的规则挖掘技术,对改进决策或规划有重要的帮助。作为最小化挖掘策略,我们采用了代数集函数最小化和关联规则挖掘方法。我们的目标是最小化相关规则的数量。本文综述了初步的方法,提出了一种最小化算法,并用已知的数据进行了测试。实验结果表明,该算法是一种有效的方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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