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	Dboost: A Fast Algorithm for DBSCAN-based Clustering on High Dimensional Data
	Zhang, Yuxiao ; Wang, Xiaorong ; Li, Bingyang ; Chen, Wei ; Wang, Tengjiao ; Lei, Kai
	2016
关键词	DBSCAN High dimensionality WAND
英文摘要	DBSCAN is a classic density-based clustering technique, which is well known in discovering clusters of arbitrary shapes and handling noise. However, it is very time-consuming in density calculation when facing high dimensional data, which makes it inefficient in many areas, such as multi-document summarization, product recommendation, etc. Therefore, how to efficiently calculate the density on high dimensional data becomes one key issue for DBSCAN-based clustering technique. In this paper, we propose a fast algorithm for DBSCAN-based clustering on high dimensional data, named Dboost. In our algorithm, a ranked retrieval technique adaption named WAND(#) is novelly applied to improving the density calculations without accuracy loss, and we further improve this acceleration by reducing the invoking times of WAND(#). Experiments were conducted on wire voltage data, Netflix dataset and microblog corpora. The results showed that an acceleration of over 50 times were achieved on wire voltage data and Netflix dataset, and 100 more times can be expected on microblog data.; CPCI-S(ISTP); zhangyuxiao@pku.edu.cn; xrwang@epri.sgcc.com.cn; beyondlee1982@163.com; pekingchenwei@pku.edu.cn; tjwang@pku.edu.cn; leik@pku.edu.cn; 245-256; 9652
语种	英语
出处	20th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD)
DOI标识	10.1007/978-3-319-31750-2_20
内容类型	其他
源URL	[http://ir.pku.edu.cn/handle/20.500.11897/460069]
专题	信息科学技术学院
推荐引用方式 GB/T 7714	Zhang, Yuxiao,Wang, Xiaorong,Li, Bingyang,et al. Dboost: A Fast Algorithm for DBSCAN-based Clustering on High Dimensional Data. 2016-01-01.

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