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An improved optimized clustering technique for crime detection

机译:一种改进的优化聚类技术,用于犯罪侦查

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Data mining automates the finding predictive records procedure in big databases. Clustering is a most famous method in data mining and is an important methodology that is performed based on the similarity principle. The segregation of a big database is a stimulating and task of time consuming. It concludes two different stages: first, feature extraction maps all documents or record to a point in the space of high-dimensional, then algorithms for clustering automatically grouping the points into a cluster hierarchy. Clustering has various applications in different fields. Few of the fields include criminology, text mining, image resolution, machine learning. Crime detection has become one of the most attractive field as the crime rate in India and whole world is increasing at a greater pace. We as citizens of a country have to contribute towards its detection and removal. Thus, a comprehensive survey carried about the basics of clustering has given in this paper. Moreover, proposed work was given that gives the idea of the work going to be done in the upcoming time.
机译:数据挖掘使大型数据库中的查找预测记录过程自动化。聚类是数据挖掘中最著名的方法,并且是基于相似性原理执行的重要方法。大型数据库的隔离是一个令人费解的工作,并且非常耗时。它总结了两个不同的阶段:首先,特征提取将所有文档或记录映射到高维空间中的某个点,然后进行聚类的算法将这些点自动分组为一个聚类层次结构。群集在不同领域中具有各种应用程序。很少领域包括犯罪学,文本挖掘,图像分辨率,机器学习。随着印度乃至全世界犯罪率的增长,犯罪侦查已成为最有吸引力的领域之一。我们作为一个国家的公民,必须为其发现和清除作出贡献。因此,本文对聚类的基础进行了全面的调查。此外,给出了拟议的工作,使人们对即将到来的时间将要完成的工作有一个想法。

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