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Analysis of Procedure of Project Decision Based on Data Mining of Rough Sets

机译:基于粗糙集数据挖掘的项目决策程序分析

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摘要

In the paper, the procedure of project decision based on data mining of Rough Sets is discussed. This paper takes an E-Commerce project as a case study. The risk decision of E-Commerce project is sort of multiple attribute decision-making processes. It is certain that we have to deal with massive data. So data mining technology is necessary, for it can abstract implicit regularity from massive data. In this paper, the reduction algorithm based on Rough Sets is proposed as a practical data mining technology. In the paper, the procedure of project decision is analyzed. And a new decision method is proposed in order to solve the risk decision problem of an E-Commerce project. The factor set is established including condition attribute and decision attribute. Then experts qualitatively describe risk factors and create a decision table, and the attribute reduction algorithm based on Rough Sets is used to eliminate the redundant risk factor and its value of decision table. Finally, the minimum decision rules are created based on data mining results. And the rules with explain meanings are abstracted in the case study. We can make proper decision from the rules to improve precision and explanatory ability in practice.
机译:本文讨论了基于粗糙集数据挖掘的项目决策过程。本文以电子商务项目为例。电子商务项目的风险决策是一种多属性决策过程。可以肯定,我们必须处理海量数据。因此数据挖掘技术是必要的,因为它可以从海量数据中提取隐式规则。本文提出了一种基于粗糙集的约简算法作为一种实用的数据挖掘技术。本文分析了项目决策过程。为了解决电子商务项目的风险决策问题,提出了一种新的决策方法。建立包括条件属性和决策属性的因子集。然后专家定性描述风险因素并创建决策表,并采用基于粗糙集的属性约简算法消除冗余风险因素及其决策表的价值。最后,根据数据挖掘结果创建最小决策规则。案例研究中抽象了具有解释意义的规则。我们可以根据规则做出适当的决定,以提高实践的准确性和解释能力。

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