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Z - CRIME: A data mining tool for the detection of suspicious criminal activities based on decision tree

机译:Z-CRIME:一种基于决策树的可疑犯罪活动检测数据挖掘工具

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Data mining is the extraction of knowledge from large databases. One of the popular data mining techniques is Classification in which different objects are classified into different classes depending on the common properties among them. Decision Trees are widely used in Classification. This paper proposes a tool which applies an enhanced Decision Tree Algorithm to detect the suspicious e-mails about the criminal activities. An improved ID3 Algorithm with enhanced feature selection method and attribute- importance factor is applied to generate a better and faster Decision Tree. The objective is to detect the suspicious criminal activities and minimize them. That's why the tool is named as “Z-Crime” depicting the “Zero Crime” in the society. This paper aims at highlighting the importance of data mining technology to design proactive application to detect the suspicious criminal activities.
机译:数据挖掘是从大型数据库中提取知识。流行的数据挖掘技术之一是分类,其中根据对象之间的共同属性将不同的对象分为不同的类。决策树在分类中被广泛使用。本文提出了一种工具,该工具应用了增强的决策树算法来检测有关犯罪活动的可疑电子邮件。一种具有增强的特征选择方法和属性重要性因子的改进的ID3算法被应用于生成更好,更快的决策树。目的是发现可疑犯罪活动并将其最小化。这就是为什么将该工具命名为“ Z-犯罪”的原因,它描述了社会中的“零犯罪”。本文旨在强调数据挖掘技术对于设计主动应用程序以检测可疑犯罪活动的重要性。

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