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一种基于四叉树的快速聚类算法 被引量：6

Fast clustering algorithm based on Quad-tree
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摘要 以DBSCAN算法为基础,提出一种基于四叉树的快速聚类算法。新算法选择处于核心点的中空球形邻域中的点作为种子点来扩展类,大大减少区域查询的次数,降低I/O开销;使用快速生成的四叉树进行区域查询,在提高查询效率的同时,有效缩短构造空间索引的时间。文中对二维模拟数据和真实数据进行测试,结果表明新算法是有效的。 On the DBSCAN algorithm, a fast clustering algorithm based on quad-tree was proposed. It chose the points in the cirque-shaped neighborhood of a core point as seeds to expand the cluster, which decreased the execution frequency of region query and reduced the I/O cost. It used a fast-created quad-tree to execute region query, which not only improved the query efficiency, but also shortened the time of constructing a spatial index. Experiment results show that the new algorithm is effective.
作者 栾丽华 吉根林
机构地区 南京师范大学计算机科学系
出处 《计算机应用》 CSCD 北大核心 2005年第5期1001-1003,共3页 journal of Computer Applications
基金 江苏省重点实验室开放基金资助项目(KSJ03064)
关键词 聚类 DBSCAN 四叉树 clustering DBSCAN quad-tree
分类号 TP301.6 [自动化与计算机技术—计算机系统结构]
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参考文献6

  • 1周水庚,周傲英,曹晶.基于数据分区的DBSCAN算法[J].计算机研究与发展,2000,37(10):1153-1159. 被引量：99
  • 2ESTER M, KRIEGEL HP, SANDER J,et al. A Density-Based Algorithm for Discovering Clusters in Large Spatial Databases with Noise[A]. Proc. of 2nd Int. Conf. on Knowledge Discovery and Data Mining (KDD-96)[C]. Portland, Oregon, 1996.
  • 3BECKMANN N. KRIEGEL HP, SCHNEIDER R,et al. The R^*-tree: An Efficient and Robust Access Method for Points and Rectangles[A]. Proc. ACM SIGMOD[C], 1990.322-331.
  • 4AHN HK, MAMOULIS N, WONG HM. A Survey on Multidimensional Access Methods[R]. Research report, Hong Kong University of Science and Technology, Hong Kong, 1997.
  • 5STONEBRAKER M, FREW J, GARDELS K,et al. The SEQUOIA 2000 Storage Benchmark[A]. Proc. ACM SIGMOD Int. Conf. on Management of Date[C]. Washington, 1993.2-11.
  • 6钱卫宁,周傲英.从多角度分析现有聚类算法(英文)[J].软件学报,2002,13(8):1382-1394. 被引量：86

二级参考文献41

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计算机应用
2005年 第5期

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