Research and implementation of density based clustering algorithm for complex clusters

Computer Engineering and Applications ›› 2007, Vol. 43 ›› Issue (35): 162-165.

• 数据库与信息处理 • Previous Articles Next Articles

Research and implementation of density based clustering algorithm for complex clusters

SONG Yu-chen¹,SONG Fei-yan²,MENG Hai-dong²

1.School of Economics and Management，Inner Mongolia Univ. of Science and Technology，Baotou，Inner Mongolia 014010，China
2.School of Resource and Safety engineering，Inner Mongolia Univ. of Sci. and Technology，Baotou，Inner Mongolia 014010，China

Received:1900-01-01 Revised:1900-01-01 Online:2007-12-11 Published:2007-12-11
Contact: SONG Yu-chen

基于密度复杂簇聚类算法研究与实现

宋宇辰¹,宋飞燕²,孟海东²

1.内蒙古科技大学经济管理学院，内蒙古包头 014010
2.内蒙古科技大学资源与安全工程学院，内蒙古包头 014010

通讯作者: 宋宇辰

Abstract

Abstract: For model recognition，data analysis，image processing，market research and so on，the key technique is to handle complexly distributed clusters efficiently.On the basis of analysis and research of traditional clustering algorithms，a clustering algorithm based on density and adaptive density-reachable is presented in this paper.Experimental results show that the algorithm can handle clusters of arbitrary shapes，sizes and densities.At the same time，this algorithm can evidently reduce time and space complexity as compared with other density-based algorithms.

Key words: clustering algorithm, complex cluster, density-based, adaptive density-reachable

摘要： 聚类算法在模式识别、数据分析、图像处理、以及市场研究的应用中，需要解决的关键技术是如何有效地聚类各种复杂的数据对象簇。在分析与研究现有聚类算法的基础上，提出了一种基于密度和自适应密度可达的改进算法。实验证明，该算法能够有效聚类任意分布形状、不同密度、不同尺度的簇；同时，算法的计算复杂度与传统基于密度的聚类算法相比有明显的降低。

关键词: 聚类算法, 复杂簇, 基于密度, 自适应密度可达

SONG Yu-chen¹,SONG Fei-yan²,MENG Hai-dong². Research and implementation of density based clustering algorithm for complex clusters[J]. Computer Engineering and Applications, 2007, 43(35): 162-165.

宋宇辰¹,宋飞燕²,孟海东². 基于密度复杂簇聚类算法研究与实现[J]. 计算机工程与应用, 2007, 43(35): 162-165.

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Research and implementation of density based clustering algorithm for complex clusters

基于密度复杂簇聚类算法研究与实现

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