文章基本信息

标题：Enhanced Dbscan Algorithm
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作者：Priyamvada Paliwal ; Meghna Sharma
期刊名称：International Journal of Computer Trends and Technology
电子版ISSN：2231-2803
出版年度：2013
卷号：4
期号：4-3
出版社：Seventh Sense Research Group
摘要：The DBSCAN algorithm can identify clusters in large spatial data sets by looking at the local density of database elements, using only one input parameter. This paper presents a comprehensive study of DBSCAN algorithm and the enhanced version of DBSCAN algorithm The salient of this paper to present enhanced DBSCAN algorithm with its implementation with the complexity and the difference between the older version of DBSCAN algorithm. And there are also additional features described with this algorithm for finding outliers.
关键词：Density-based spatial clustering of applications with noise; Threshold Distance; Minimum Points; Cluster; Density