Parallel Design of Hash and K-means Algorithm in the Context of Big Data

摘要：

　　In order to further improve the efficiency of K - means algorithm on the large-scale data clustering, this paper conducts deep analysis and research on the optimization of K - means clustering algorithm and proposes a selected program of initial clustering center based on Hash algorithm, hashing mass high-dimensional data to a compression space to excavate the clustering relations, so as to make the selected initial clustering center tend to be convergent state as far as possible and to greatly reduce the number of iterations of clustering, improved the accuracy of clustering.

关键词： K-means Hash mass data

作者: Xing Lei Zhang Xiang Guo Zhengkun Guo Fuwang

作者单位: China Aviation Integrated Technology Research Institute, Beijing

会议类型: 国际会议

会议名称: 2019 6th International Conference on Machinery, Mechanics, Materials and Computer Engineering (MMMCE 2019)(2019 第六届机械、材料和计算机工程国际会议)

会议地点: 呼和浩特

会议语种:英文

页码: 660-664

在线出版日期: 2019-07-27（万方平台首次上网日期，不代表论文的发表时间）