Clustering categorical data streams
文献类型：期刊论文
| 作者 | He zengyou; Xu xiaofei; Deng shengchun; Huang Joshua zhexue |
| 刊名 | Advances in Intelligent Systems
 |
| 出版日期 | 2011 |
| 卷号 | 11期号:4页码:185-192 |
| 英文摘要 | In this paper, we propose an efficient clustering algorithm for analyzing categorical data streams. It has been proved that the proposed algorithm uses small memory footprints. We provide empirical analysis on the performance of the algorithm in clustering both synthetic and real data streams. © 2011 IOS Press and the authors. All rights reserved.(10 refs) |
| 收录类别 | EI |
| 原文出处 | http://content.iospress.com/download/journal-of-computational-methods-in-sciences-and-engineering/jcm00363?id=journal-of-computational-methods-in-sciences-and-engineering%2Fjcm00363 |
| 语种 | 英语 |
| 源URL | [http://ir.siat.ac.cn:8080/handle/172644/3554]  |
| 专题 | 深圳先进技术研究院_数字所 |
| 作者单位 | Advances in Intelligent Systems |
| 推荐引用方式 GB/T 7714 | He zengyou,Xu xiaofei,Deng shengchun,et al. Clustering categorical data streams[J]. Advances in Intelligent Systems,2011,11(4):185-192. |
| APA | He zengyou,Xu xiaofei,Deng shengchun,&Huang Joshua zhexue.(2011).Clustering categorical data streams.Advances in Intelligent Systems,11(4),185-192. |
| MLA | He zengyou,et al."Clustering categorical data streams".Advances in Intelligent Systems 11.4(2011):185-192. |
入库方式： OAI收割
来源：深圳先进技术研究院
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