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	Predicting the visualization intensity for interactive spatio-temporal visual analytics: a data-driven view-dependent approach
	Li, Jing; Zhang, Tong; Liu, Qing; Yu, Manzhu
刊名	INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE
	2017
卷号	31期号:1
关键词	Compute unified device architecture (CUDA) intensity prediction interactive visualization spatio-temporal data clustering
ISSN号	1365-8816
DOI	10.1080/13658816.2016.1194424
URL标识	查看原文
收录类别	SSCI
语种	英语
内容类型	期刊论文
URI标识	http://www.corc.org.cn/handle/1471x/3799114
专题	武汉大学
推荐引用方式 GB/T 7714	Li, Jing,Zhang, Tong,Liu, Qing,et al. Predicting the visualization intensity for interactive spatio-temporal visual analytics: a data-driven view-dependent approach[J]. INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE,2017,31(1).
APA	Li, Jing,Zhang, Tong,Liu, Qing,&Yu, Manzhu.(2017).Predicting the visualization intensity for interactive spatio-temporal visual analytics: a data-driven view-dependent approach.INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE,31(1).
MLA	Li, Jing,et al."Predicting the visualization intensity for interactive spatio-temporal visual analytics: a data-driven view-dependent approach".INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE 31.1(2017).

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