MR-DBSCAN: An efficient parallel density-based clustering algorithm using MapReduce
文献类型：会议论文
| 作者 | Yaobin He; Haoyu Tan; Wuman Luo; Huajian Mao; Di Ma; Shengzhong Feng; Jianping Fan |
| 出版日期 | 2011 |
| 会议名称 | 2011 17th IEEE International Conference on Parallel and Distributed Systems, ICPADS 2011 |
| 会议地点 | Tainan, Taiwan |
| 英文摘要 | Data clustering is an important data mining technology that plays a crucial role in numerous scientific applications. However, it is challenging due to the size of datasets has been growing rapidly to extra-large scale in the real world. Meanwhile, MapReduce is a desirable parallel programming platform that is widely applied in kinds of data process fields. In this paper, we propose an efficient parallel density-based clustering algorithm and implement it by a 4-stages MapReduce paradigm. Furthermore, we adopt a quick partitioning strategy for large scale non-indexed data. We study the metric of merge among bordering partitions and make optimizations on it. At last, we evaluate our work on real large scale datasets using Hadoop platform. Results reveal that the speedup and scale up of our work are very efficient. |
| 收录类别 | EI |
| 语种 | 英语 |
| 源URL | [http://ir.siat.ac.cn:8080/handle/172644/3588]  |
| 专题 | 深圳先进技术研究院_数字所 |
| 作者单位 | 2011 |
| 推荐引用方式 GB/T 7714 | Yaobin He,Haoyu Tan,Wuman Luo,et al. MR-DBSCAN: An efficient parallel density-based clustering algorithm using MapReduce[C]. 见:2011 17th IEEE International Conference on Parallel and Distributed Systems, ICPADS 2011. Tainan, Taiwan. |
入库方式： OAI收割
来源：深圳先进技术研究院
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