| 一种基于密度和网格的高效聚类算法(英文) |
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| 引用本文： | 刘章雄,刘宴兵,罗来明.一种基于密度和网格的高效聚类算法(英文)[J].重庆邮电学院学报(自然科学版),2010(2). |
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| 作者姓名： | 刘章雄 刘宴兵 罗来明 |
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| 作者单位： | 重庆邮电大学计算机学院;重庆聚购科技发展有限公司; |
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| 基金项目： | The Natural Science Foundation Project of CQ CSTC(CSTC,2009AB2053);;The Science and Technology Research Project of Chongqing Municipal Education Commission of China(KJ080505) |
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| 摘 要： | 聚类已成为数据挖掘的主要方法之一,能够帮助人们在大量的数据中发现隐藏信息。目前最具典型的密度聚类算法是DBSCAN(density-based spatial clustering of applications with noise),它能够在空间数据库中很好地发现任意形状的簇并有效地处理噪声,但是它的计算复杂度相对较大。因此,采用划分数据集和聚簇合并方法,提出了一种基于密度和网格的高效聚类算法DGCA,并通过人工合成数据集和真实数据集对该聚类算法进行理论验证。实验结果表明该算法在效率性能和质量方面比DBSCAN都得到了提高。
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| 关 键 词： | 密度聚类 网格聚类 DBSCAN 聚类合并 |
An efficient density and grid based clustering algorithm |
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| LIU Zhang-xiong,LIU Yan-bing,LUO Lai-ming.An efficient density and grid based clustering algorithm[J].Journal of Chongqing University of Posts and Telecommunications(Natural Sciences Edition),2010(2). |
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| Authors: | LIU Zhang-xiong LIU Yan-bing LUO Lai-ming |
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| Institution: | 1.School of Computer Science;Chongqing University of Posts and Telecommunications;Chongqing 400065;P.R.China;2.Chongqing Jugou Technology Development Co.;Ltd.;P.R.China |
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| Abstract: | Clustering is one of the basic data mining tasks that can be used to help to understand the hidden information present in data sets density-based spatial clustering of applications with noise(DBSCAN),which is a typical density-based clustering algorithm,can detect arbitrary shaped clusters and handle noise well,but its computational complexity is unacceptable.In this paper,we present an efficient density and grid based clustering algorithm(DGCA)to enhance the performance of DBSCAN by partitioning data into ... |
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