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	UrbanWater Quality Prediction based on Multi-task Multi-view Learning
	Ye Liu; Yu Zheng; Yuxuan Liang; Shuming Liu; David S. Rosenblum
	2016
会议名称	IJCAI 2016
会议地点	New York
英文摘要	Urban water quality is of great importance to our daily lives. Prediction of urban water quality help control water pollution and protect human health. In this work, we forecast the water quality of a station over the next few hours, using a multitask multi-view learning method to fuse multiple datasets from different domains. In particular, our learning model comprises two alignments. The first alignment is the spaio-temporal view alignment, which combines local spatial and temporal information of each station. The second alignment is the prediction alignment among stations, which captures their spatial correlations and performs copredictions by incorporating these correlations. Extensive experiments on real-world datasets demonstrate the effectiveness of our approach.
收录类别	EI
语种	英语
内容类型	会议论文
源URL	[http://ir.siat.ac.cn:8080/handle/172644/10318]
专题	深圳先进技术研究院_数字所
作者单位	2016
推荐引用方式 GB/T 7714	Ye Liu,Yu Zheng,Yuxuan Liang,et al. UrbanWater Quality Prediction based on Multi-task Multi-view Learning[C]. 见:IJCAI 2016. New York.

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