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| BIRCH聚类算法优化及并行化研究 | |
| 引用本文： | 朱映辉,江玉珍. BIRCH聚类算法优化及并行化研究[J]. 计算机工程与设计, 2007, 28(18): 4345-4346,4369 |
| 作者姓名： | 朱映辉 江玉珍 |
| 作者单位： | 韩山师范学院,数学与信息技术学院,广东,潮州,521041;韩山师范学院,数学与信息技术学院,广东,潮州,521041 |
| 摘 要： | 为了提高聚类质量,针对BIRCH算法中在聚类精度方面所存在的不足,提出了聚类特征树中的不同簇应使用不同阀值的思想,较好地改善了对体积相差悬殊的簇不能很好聚类的问题.并且深入地研究和分析了如何在集群系统中进行快速聚类,提出了自定义数据类型、采用数据并行思想和非均匀数据划分策略等几点改进意见.最后实验结果表明,通过改进能够获得比较理想的运行时间和加速比性能. |
| 关 键 词： | 集群 数据挖掘 聚类 聚类质量 并行化 |
| 文章编号： | 1000-7024（2007）18-4345-02 |
| 修稿时间： | 2006-10-10 |
Research of BIRCH clustering algorithm optimization and parallelism |
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| ZHU Ying-hui,JIANG Yu-zhen. Research of BIRCH clustering algorithm optimization and parallelism[J]. Computer Engineering and Design, 2007, 28(18): 4345-4346,4369 | |
| Authors: | ZHU Ying-hui JIANG Yu-zhen |
| Affiliation: | College of Mathematics and Information Technology, Hanshan Normal University, Chaozhou 521041, China |
| Abstract: | To improve the quality of clustering, considering the insufficiency of clustering precision which exists in the BIRCH algorithm, the idea of different threshold should be set in different cluster in CF-tree is implemented. An in-depth study and analysis is carried out on how to accelerate clustering in cluster system. Subsequently, some creative schemes such as custom datatype, data parallelism, and asymmetric data-partition are put forward. Finally, a result of the better performance is obtained after the improvement is verified by an experiment. |
| Keywords: | cluster data mining clustering quality of clustering parallelism |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ | |