| 英文标题 | Survey of K-means algorithm on big data |
| 作者英文名 | Ren Yuanhang |
| 机构英文名 | School of Information & Software Engineering,University of Electronic Science & Technology of China,Chengdu 610054,China |
| 英文摘要 | Among all the clustering problems, the K-means problem is probably the most well-known one. How to obtain a theoretically guaranteed solution of K-means efficiently for the big data can be a key problem. This paper surveyed the progress of this problem. Firstly, this paper defined the K-means problem and introduced relevant backgrounds. Secondly, it introduced separately and described in details the techniques for theoretical guarantee and speed up. Finally, it summarized the main results and forecasted the future directions of K-means algorithms on big data. |
| 英文关键词 | clustering; K-means; sampling; sub-linear time algorithms; theoretical guarantee |