SalienTime: User-driven Selection of Salient Time Steps for Large-Scale Geospatial Data Visualization-Reference-Cited by-同舟云学术

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SalienTime: User-driven Selection of Salient Time Steps for Large-Scale Geospatial Data Visualization

Published:2024-05-11 Issue: Volume: Page:1-19
ISSN:
Container-title:Proceedings of the CHI Conference on Human Factors in Computing Systems
language:
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Author:

Chen Juntong¹^ORCID,Huang Haiwen¹^ORCID,Ye Huayuan¹^ORCID,Peng Zhong²^ORCID,Li Chenhui¹^ORCID,Wang Changbo³^ORCID

Affiliation:

1. School of Computer Science and Technology, East China Normal University, China

2. State Key Laboratory of Estuarine and Coastal Research, East China Normal University, China

3. School of Computer Science and Software Engineering, East China Normal University, China

Funder

Shanghai Committee of Science and Technology, China

the Science and Technology Commission of Shanghai Municipality, China

NSFC

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3613904.3642944

Reference78 articles.

1. D³ Data-Driven Documents

2. J. B. Brooke. 1996. SUS: A ’quick and Dirty’ Usability Scale.

3. GPU accelerated t-distributed stochastic neighbor embedding

4. Importance-Driven Time-Varying Data Visualization

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1. GeoVis: a data-driven geographic visualization recommendation system via latent space encoding;Journal of Visualization;2024-04-16

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