GAMES Webinar 2017-21期(Visualization 2017论文报告)| 汪云海(山东大学),赵珣(香港科技大学)

【GAMES Webinar 2017-21期(Visualization 2017论文报告)】

报告嘉宾1: 汪云海,山东大学

报告时间:2017年11月9日(星期四)晚20:00 – 20:45(北京时间)




如何创造有效、美观的可视化表征以达到“一眼洞穿真相”的效果,一直是可视化领域的研究目标。经过学者们多年的努力,我们已经有了很多新颖的可视化表达方法,包括常用的折线图、散点图、平行坐标等。但对于普通用户来说,许多炫目的可视化技术往往“只可远观而不能亵玩”,因为用户难以权衡哪种方法最能有效的呈现数据特征。即使户选择了某种可视化方法,该方法所对应的复杂可视化视觉编码参数仍然可能使其陷入“选择困境”。 为解决该困境,我们提出了任务驱动的自动可视化技术,本次报告将分享我们最近的一些相关工作。


汪云海,山东大学计算机科学与技术学院预聘制副教授。2011年于中科院计算机网络信息中心获博士学位, 2011年至2015先后担任中国科学院深圳先进技术研究院可视计算研究中心助理研究员、副研究员,2015年12月加入山东大学。近年来,在国外著名期刊如ACM TOG、 IEEE TVCG、CGF等发表SCI论文20余篇,更多信息见:



报告时间:2017年11月9日(星期四)晚20:45 – 21:30(北京时间)


报告题目:SkyLens: Visual Analysis of Skyline on Multi-dimensional Data


Skyline queries have wide-ranging applications in fields that involve multi-criteria decision making, including tourism, retail industry, and human resources. By automatically removing incompetent candidates, skyline queries allow users to focus on a subset of superior data items (i.e., the skyline), thus reducing the decision-making overhead. However, users are still required to interpret and compare these superior items manually before making a successful choice. This task is challenging because of two issues. First, people usually have fuzzy, unstable, and inconsistent preferences when presented with multiple candidates. Second, skyline queries do not reveal the reasons for the superiority of certain skyline points in a multi-dimensional space. To address these issues, we propose SkyLens, a visual analytic system aiming at revealing the superiority of skyline points from different perspectives and at different scales to aid users in their decision making. Two scenarios demonstrate the usefulness of SkyLens on two datasets with a dozen of attributes. A qualitative study is also conducted to show that users can efficiently accomplish skyline understanding and comparison tasks with SkyLens.


Xun Zhao is a Ph.D. candidate in the Department of Computer Science and Engineering at Hong Kong University of Science and Technology (HKUST), supervised by Prof. Huamin Qu and Prof. Dik Lee . She obtained her B.Sc. degree in Hua Zhong University of Science and Technology (HUST) majored in Automation. Her research interest lies in the intersection of Machine Learning, Data Visualization, and Human-Computer Interaction.




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Liu, Ligang

刘利刚,中国科学技术大学教授,曾获得中国科学院“百人计划”、国家优青、杰青,从事计算机图形学研究。分别于1996年及2001年于浙江大学获得应用数学学士及博士学位。曾于微软亚洲研究院、浙江大学、哈佛大学工作或访问。曾获微软青年教授奖、陆增镛CAD&CG高科技奖一等奖、国家自然科学奖二等奖等奖项。负责创建了中科大《计算机图形学前沿》暑期课程及CCF CAD&CG专委图形学在线交流平台GAMES。

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