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| 基于集群环境的K-Means聚类算法的并行化 | |
| 引用本文： | 王辉,张望,范明. 基于集群环境的K-Means聚类算法的并行化[J]. 河南科技大学学报(自然科学版), 2008, 29(4) |
| 作者姓名： | 王辉 张望 范明 |
| 作者单位： | 河南科技大学电子信息工程学院,河南,洛阳,471003;河南科技大学现代教育技术与信息中心,河南,洛阳,471003 |
| 基金项目： | 国家自然科学基金，教育部科学技术基金 |
| 摘 要： | K-Means聚类算法在面对海量数据时,时间和空间的复杂性已成为K-Means聚类算法的瓶颈.在充分研究传统K-Means聚类算法的基础上,提出了基于集群环境的并行K-Means聚类算法的设计思想,给出了其加速比估算公式,并通过实验证明了该算法的正确性和有效性. |
| 关 键 词： | 集群 并行 K-Means聚类算法 |
Research on Parallelism of K-Means Clustering Algorithm Based on Cluster |
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| WANG Hui,ZHANG Wang,FAN Ming. Research on Parallelism of K-Means Clustering Algorithm Based on Cluster[J]. Journal of Henan University of Science & Technology:Natural Science, 2008, 29(4) | |
| Authors: | WANG Hui ZHANG Wang FAN Ming |
| Affiliation: | WANG Huia,ZHANG Wanga,FAN Mingb(a.Electronic Information Engineering College,b.Modern Education Technology & Information Center,Henan University of Science & Technology,Luoyang 471003,China) |
| Abstract: | The complexity of time and spatial is becoming the difficulty of K-Means clustering algorithm while it deals with the huge amounts of data sets.Based on the study of the traditional K-Means clustering algorithm,the design concept of the parallel K-Means algorithm is discussed and a formula of the speedup ratio is proposed.The accuracy and validity of the algorithm through experiments are proved. |
| Keywords: | Cluster Parallelism K-Means clustering algorithm |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ | |