关键因素提取的Apriori算法研究

Yan Peng, Tian Zhou
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引用次数: 2

摘要

企业战略决策是根据企业现在和过去的情况,对企业未来的计划进行预测和分析。它对企业的成败起着重要的作用。从影响企业战略决策的诸多因素中提取关键因素,有助于企业做出合理有效的决策,甚至有利于企业的长远发展。关联规则挖掘可以分析多个因素之间的联系关系和因果关系。在众多的关联规则挖掘方法中,我们选择了Apriori算法。Apriori算法是一种基本的关联规则挖掘算法。通过对事务群中属性值的分析,可以得出不同属性之间的相关性。基于平衡计分卡(BSC),我们从客户、内部运营流程和研究创新三个方面选择了五个影响战略决策的候选因素。首先,我们对基于实践调查的数据进行整理。其次,利用Apriori找出这些因素之间的关联,最后得出企业创新对企业声誉有直接影响的结论。该实验是Apriori在企业决策中的应用,具有很强的实用性,为企业的战略决策提供了很好的辅助。
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 the Apriori algorithm in extracting the key factor
Business strategic decision making is designed to predict and analysis the future plan of the enterprise based on the situation now and the past. It plays an important role in the success or failure of the enterprise. Extracting the key factors in many elements that affect the enterprises' strategic decision making will help the company make the reasonable and effective decision, even the long-term development of the enterprise. The association rules mining can analyze the connection relationship and the causality in many factors. Among the numerous association rules mining methods, we choose the Apriori algorithm. Apriori Algorithm is one of the basic Association Rules Mining. It can reach a correlation between different properties through analyzing attribute value in group of affairs. Based on the balance score card (BSC), we choose five candidate factors that affect the strategic decision in three areas including the customer, the internal operational process and the study innovation. First of all, we sort out the data that based on the practice survey. Secondly, we find out the association between these factors with Apriori and the last we reach a conclusion that the enterprise innovation has a direct influence to the corporate reputation. This experiment which is of great practicability is an application of Apriori in enterprise decision and provides a good assistance for enterprise in strategic decision making.
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