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Guodao Sun

Researcher at Zhejiang University of Technology

Publications -  37
Citations -  641

Guodao Sun is an academic researcher from Zhejiang University of Technology. The author has contributed to research in topics: Visualization & Computer science. The author has an hindex of 10, co-authored 23 publications receiving 472 citations. Previous affiliations of Guodao Sun include Microsoft & Zhejiang University.

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A Survey of Visual Analytics Techniques and Applications: State-of-the-Art Research and Future Challenges

TL;DR: This report reviews and classifies recent work into a set of application categories including space and time, multivariate, text, graph and network, and other applications, and relates each application category to the key steps in visual analytics, including visual mapping, model-based analysis, and user interactions.
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EvoRiver: Visual Analysis of Topic Coopetition on Social Media

TL;DR: This model provides a close functional approximation of the coopetition process by depicting how different groups of influential users affect coop Competition, and designs EvoRiver, a time-based visualization that allows users to explore coop competition-related interactions and to detect dynamically evolving patterns, as well as their major causes.
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A survey on automatic infographics and visualization recommendations

TL;DR: This survey reviews and classifies automatic tools and papers of visualization recommendations into a set of application categories including network-graph visualizations, annotationVisualizations, and storytelling visualization.
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StreamExplorer: A Multi-Stage System for Visually Exploring Events in Social Streams

TL;DR: A novel framework by which to handle complex social streams on a budget PC is proposed, which features an online method to detect important time periods and a tailored GPU-assisted Self-Organizing Map method, which clusters the tweets of subevents stably and efficiently.
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Embedding Spatio-Temporal Information into Maps by Route-Zooming

TL;DR: A novel visualization technique called route-zooming that can embed spatio-temporal information into a map seamlessly for occlusion-free visualization of both spatial and temporal data is presented.