UM
Visual Analytics in Urban Computing: An Overview
Zheng, Yixian1; Wu, Wenchao1; Chen, Yuanzhe1; Qu, Huamin1; Ni, Lionel M.2
2016-07
Source PublicationIEEE Transactions on Big Data
Volume2Issue:3Pages:276-296
AbstractNowadays, various data collected in urban context provide unprecedented opportunities for building a smarter city through urban computing. However, due to heterogeneity, high complexity and large volumes of these urban data, analyzing them is not an easy task, which often requires integrating human perception in analytical process, triggering a broad use of visualization. In this survey, we first summarize frequently used data types in urban visual analytics, and then elaborate on existing visualization techniques for time, locations and other properties of urban data. Furthermore, we discuss how visualization can be combined with automated analytical approaches. Existing work on urban visual analytics is categorized into two classes based on different outputs of such combinations: 1) For data exploration and pattern interpretation, we describe representative visual analytics tools designed for better insights of different types of urban data. 2) For visual learning, we discuss how visualization can help in three major steps of automated analytical approaches (i.e., cohort construction; feature selection & model construction; result evaluation & tuning) for a more effective machine learning or data mining process, leading to sort of artificial intelligence, such as a classifier, a predictor or a regression model. Finally, we outlook the future of urban visual analytics, and conclude the survey with potential research directions. © 2015 IEEE.
DOI10.1109/TBDATA.2016.2586447
Language英语
The Source to ArticleEngineering Village
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Document TypeJournal article
CollectionUniversity of Macau
Affiliation1.Hong Kong University of Science and Technology, Kowloon, Hong Kong;
2.University of Macau, Taipa Macau, China
Recommended Citation
GB/T 7714
Zheng, Yixian,Wu, Wenchao,Chen, Yuanzhe,et al. Visual Analytics in Urban Computing: An Overview[J]. IEEE Transactions on Big Data,2016,2(3):276-296.
APA Zheng, Yixian,Wu, Wenchao,Chen, Yuanzhe,Qu, Huamin,&Ni, Lionel M..(2016).Visual Analytics in Urban Computing: An Overview.IEEE Transactions on Big Data,2(3),276-296.
MLA Zheng, Yixian,et al."Visual Analytics in Urban Computing: An Overview".IEEE Transactions on Big Data 2.3(2016):276-296.
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