�ݺ�ߣshows by User: ycwu8

�ݺ�ߣshows by User: ycwu8 / http://www.slideshare.net/images/logo.gif �ݺ�ߣshows by User: ycwu8 / Sun, 27 Oct 2013 22:20:43 GMT �ݺ�ߣShare feed for �ݺ�ߣshows by User: ycwu8 Visual Analysis of Topic Competition on Social Media /slideshow/visual-analysis-of-topic-competition-on-social-media/27631416 vast13topicomp-131027222043-phpapp01
How do various topics compete for public attention when they are spreading on social media? What roles do opinion leaders play in the rise and fall of competitiveness of various topics? In this study, we propose an expanded topic competition model to characterize the competition for public attention on multiple topics promoted by various opinion leaders on social media. To allow an intuitive understanding of the estimated measures, we present a timeline visualization through a metaphoric interpretation of the results. The visual design features both topical and social aspects of the information diffusion process by compositing ThemeRiver with storyline style visualization. ThemeRiver shows the increase and decrease of competitiveness of each topic. Opinion leaders are drawn as threads that converge or diverge with regard to their roles in influencing the public agenda change over time. To validate the effectiveness of the visual analysis techniques, we report the insights gained on two collections of Tweets: the 2012 United States presidential election and the Occupy Wall Street movement. The slide deck was made by Panpan Xu and presented by her in IEEE VAST 2013. More details about this project can be found from the project page: http://www.ycwu.org/projects/vast13.html]]>
How do various topics compete for public attention when they are spreading on social media? What roles do opinion leaders play in the rise and fall of competitiveness of various topics? In this study, we propose an expanded topic competition model to characterize the competition for public attention on multiple topics promoted by various opinion leaders on social media. To allow an intuitive understanding of the estimated measures, we present a timeline visualization through a metaphoric interpretation of the results. The visual design features both topical and social aspects of the information diffusion process by compositing ThemeRiver with storyline style visualization. ThemeRiver shows the increase and decrease of competitiveness of each topic. Opinion leaders are drawn as threads that converge or diverge with regard to their roles in influencing the public agenda change over time. To validate the effectiveness of the visual analysis techniques, we report the insights gained on two collections of Tweets: the 2012 United States presidential election and the Occupy Wall Street movement. The slide deck was made by Panpan Xu and presented by her in IEEE VAST 2013. More details about this project can be found from the project page: http://www.ycwu.org/projects/vast13.html]]> Sun, 27 Oct 2013 22:20:43 GMT /slideshow/visual-analysis-of-topic-competition-on-social-media/27631416 ycwu8@slideshare.net(ycwu8) Visual Analysis of Topic Competition on Social Media ycwu8 How do various topics compete for public attention when they are spreading on social media? What roles do opinion leaders play in the rise and fall of competitiveness of various topics? In this study, we propose an expanded topic competition model to characterize the competition for public attention on multiple topics promoted by various opinion leaders on social media. To allow an intuitive understanding of the estimated measures, we present a timeline visualization through a metaphoric interpretation of the results. The visual design features both topical and social aspects of the information diffusion process by compositing ThemeRiver with storyline style visualization. ThemeRiver shows the increase and decrease of competitiveness of each topic. Opinion leaders are drawn as threads that converge or diverge with regard to their roles in influencing the public agenda change over time. To validate the effectiveness of the visual analysis techniques, we report the insights gained on two collections of Tweets: the 2012 United States presidential election and the Occupy Wall Street movement. The slide deck was made by Panpan Xu and presented by her in IEEE VAST 2013. More details about this project can be found from the project page: http://www.ycwu.org/projects/vast13.html <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/vast13topicomp-131027222043-phpapp01-thumbnail.jpg?width=120&height=120&fit=bounds" /><br> How do various topics compete for public attention when they are spreading on social media? What roles do opinion leaders play in the rise and fall of competitiveness of various topics? In this study, we propose an expanded topic competition model to characterize the competition for public attention on multiple topics promoted by various opinion leaders on social media. To allow an intuitive understanding of the estimated measures, we present a timeline visualization through a metaphoric interpretation of the results. The visual design features both topical and social aspects of the information diffusion process by compositing ThemeRiver with storyline style visualization. ThemeRiver shows the increase and decrease of competitiveness of each topic. Opinion leaders are drawn as threads that converge or diverge with regard to their roles in influencing the public agenda change over time. To validate the effectiveness of the visual analysis techniques, we report the insights gained on two collections of Tweets: the 2012 United States presidential election and the Occupy Wall Street movement. The slide deck was made by Panpan Xu and presented by her in IEEE VAST 2013. More details about this project can be found from the project page: http://www.ycwu.org/projects/vast13.html

Visual Analysis of Topic Competition on Social Media from Yingcai Wu

]]> 4496 10 https://cdn.slidesharecdn.com/ss_thumbnails/vast13topicomp-131027222043-phpapp01-thumbnail.jpg?width=120&height=120&fit=bounds presentation White http://activitystrea.ms/schema/1.0/post

http://activitystrea.ms/schema/1.0/posted

0 Perceptually Based Depth-Ordering Enhancement for Direct Volume Rendering /slideshow/perceptually-based-depthordering-enhancement-for-direct-volume-rendering-27594117/27594117 vis13-light-perceptiontest-131026073901-phpapp01
Visualizing complex volume data usually renders selected parts of the volume semi-transparently to see inner structures of the volume or provide a context. This presents a challenge for volume rendering methods to produce images with unambiguous depthordering perception. Existing methods use visual cues such as halos and shadows to enhance depth perception. Along with other limitations, these methods introduce redundant information and require additional overhead. This paper presents a new approach to enhancing depth-ordering perception of volume rendered images without using additional visual cues. We set up an energy function based on quantitative perception models to measure the quality of the images in terms of the effectiveness of depth-ordering and transparency perception as well as the faithfulness of the information revealed. Guided by the function, we use a conjugate gradient method to iteratively and judiciously enhance the results. Our method can complement existing systems for enhancing volume rendering results. Our work has appeared in IEEE TVCG and was selected for presentation in IEEE VIS 2013. Project page: http://research.microsoft.com/en-us/um/people/ycwu/projects/tvcg13_perception.html]]>
Visualizing complex volume data usually renders selected parts of the volume semi-transparently to see inner structures of the volume or provide a context. This presents a challenge for volume rendering methods to produce images with unambiguous depthordering perception. Existing methods use visual cues such as halos and shadows to enhance depth perception. Along with other limitations, these methods introduce redundant information and require additional overhead. This paper presents a new approach to enhancing depth-ordering perception of volume rendered images without using additional visual cues. We set up an energy function based on quantitative perception models to measure the quality of the images in terms of the effectiveness of depth-ordering and transparency perception as well as the faithfulness of the information revealed. Guided by the function, we use a conjugate gradient method to iteratively and judiciously enhance the results. Our method can complement existing systems for enhancing volume rendering results. Our work has appeared in IEEE TVCG and was selected for presentation in IEEE VIS 2013. Project page: http://research.microsoft.com/en-us/um/people/ycwu/projects/tvcg13_perception.html]]> Sat, 26 Oct 2013 07:39:01 GMT /slideshow/perceptually-based-depthordering-enhancement-for-direct-volume-rendering-27594117/27594117 ycwu8@slideshare.net(ycwu8) Perceptually Based Depth-Ordering Enhancement for Direct Volume Rendering ycwu8 Visualizing complex volume data usually renders selected parts of the volume semi-transparently to see inner structures of the volume or provide a context. This presents a challenge for volume rendering methods to produce images with unambiguous depthordering perception. Existing methods use visual cues such as halos and shadows to enhance depth perception. Along with other limitations, these methods introduce redundant information and require additional overhead. This paper presents a new approach to enhancing depth-ordering perception of volume rendered images without using additional visual cues. We set up an energy function based on quantitative perception models to measure the quality of the images in terms of the effectiveness of depth-ordering and transparency perception as well as the faithfulness of the information revealed. Guided by the function, we use a conjugate gradient method to iteratively and judiciously enhance the results. Our method can complement existing systems for enhancing volume rendering results. Our work has appeared in IEEE TVCG and was selected for presentation in IEEE VIS 2013. Project page: http://research.microsoft.com/en-us/um/people/ycwu/projects/tvcg13_perception.html <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/vis13-light-perceptiontest-131026073901-phpapp01-thumbnail.jpg?width=120&height=120&fit=bounds" /><br> Visualizing complex volume data usually renders selected parts of the volume semi-transparently to see inner structures of the volume or provide a context. This presents a challenge for volume rendering methods to produce images with unambiguous depthordering perception. Existing methods use visual cues such as halos and shadows to enhance depth perception. Along with other limitations, these methods introduce redundant information and require additional overhead. This paper presents a new approach to enhancing depth-ordering perception of volume rendered images without using additional visual cues. We set up an energy function based on quantitative perception models to measure the quality of the images in terms of the effectiveness of depth-ordering and transparency perception as well as the faithfulness of the information revealed. Guided by the function, we use a conjugate gradient method to iteratively and judiciously enhance the results. Our method can complement existing systems for enhancing volume rendering results. Our work has appeared in IEEE TVCG and was selected for presentation in IEEE VIS 2013. Project page: http://research.microsoft.com/en-us/um/people/ycwu/projects/tvcg13_perception.html

Perceptually Based Depth-Ordering Enhancement for Direct Volume Rendering from Yingcai Wu

]]> 1151 4 https://cdn.slidesharecdn.com/ss_thumbnails/vis13-light-perceptiontest-131026073901-phpapp01-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post

http://activitystrea.ms/schema/1.0/posted

0 Perceptually Based Depth-Ordering Enhancement for Direct Volume Rendering /slideshow/perceptually-based-depthordering-enhancement-for-direct-volume-rendering/27594068 vis13-light-perceptiontest-131026073418-phpapp01
�ݺ�ߣ deck for our new TVCG paper which was presented by Lin Zheng in IEEE Vis 2013.]]>
�ݺ�ߣ deck for our new TVCG paper which was presented by Lin Zheng in IEEE Vis 2013.]]> Sat, 26 Oct 2013 07:34:17 GMT /slideshow/perceptually-based-depthordering-enhancement-for-direct-volume-rendering/27594068 ycwu8@slideshare.net(ycwu8) Perceptually Based Depth-Ordering Enhancement for Direct Volume Rendering ycwu8 �ݺ�ߣ deck for our new TVCG paper which was presented by Lin Zheng in IEEE Vis 2013. <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/vis13-light-perceptiontest-131026073418-phpapp01-thumbnail.jpg?width=120&height=120&fit=bounds" /><br> �ݺ�ߣ deck for our new TVCG paper which was presented by Lin Zheng in IEEE Vis 2013.

Perceptually Based Depth-Ordering Enhancement for Direct Volume Rendering from Yingcai Wu

]]> 330 2 https://cdn.slidesharecdn.com/ss_thumbnails/vis13-light-perceptiontest-131026073418-phpapp01-thumbnail.jpg?width=120&height=120&fit=bounds presentation Black http://activitystrea.ms/schema/1.0/post

http://activitystrea.ms/schema/1.0/posted

0 StoryFlow - Visually Tracking Evolution of Stories /slideshow/storyflow-visually-tracking-evolution-of-stories/27553922 storyflowclean-131024221243-phpapp02
Storyline visualizations, which are useful in many applications, aim to illustrate the dynamic relationships between entities in a story. However, the growing complexity and scalability of stories pose great challenges for existing approaches. In this paper, we propose an efficient optimization approach to generating an aesthetically appealing storyline visualization, which effectively handles the hierarchical relationships between entities over time. The approach formulates the storyline layout as a novel hybrid optimization approach that combines discrete and continuous optimization. The discrete method generates an initial layout through the ordering and alignment of entities, and the continuous method optimizes the initial layout to produce the optimal one. The efficient approach makes real-time interactions (e.g., bundling and straightening) possible, thus enabling users to better understand and track how the story evolves. This work was presented in IEEE InfoVis 2013. Project page: http://www.ycwu.org/projects/infovis13.html]]>
Storyline visualizations, which are useful in many applications, aim to illustrate the dynamic relationships between entities in a story. However, the growing complexity and scalability of stories pose great challenges for existing approaches. In this paper, we propose an efficient optimization approach to generating an aesthetically appealing storyline visualization, which effectively handles the hierarchical relationships between entities over time. The approach formulates the storyline layout as a novel hybrid optimization approach that combines discrete and continuous optimization. The discrete method generates an initial layout through the ordering and alignment of entities, and the continuous method optimizes the initial layout to produce the optimal one. The efficient approach makes real-time interactions (e.g., bundling and straightening) possible, thus enabling users to better understand and track how the story evolves. This work was presented in IEEE InfoVis 2013. Project page: http://www.ycwu.org/projects/infovis13.html]]> Thu, 24 Oct 2013 22:12:43 GMT /slideshow/storyflow-visually-tracking-evolution-of-stories/27553922 ycwu8@slideshare.net(ycwu8) StoryFlow - Visually Tracking Evolution of Stories ycwu8 Storyline visualizations, which are useful in many applications, aim to illustrate the dynamic relationships between entities in a story. However, the growing complexity and scalability of stories pose great challenges for existing approaches. In this paper, we propose an efficient optimization approach to generating an aesthetically appealing storyline visualization, which effectively handles the hierarchical relationships between entities over time. The approach formulates the storyline layout as a novel hybrid optimization approach that combines discrete and continuous optimization. The discrete method generates an initial layout through the ordering and alignment of entities, and the continuous method optimizes the initial layout to produce the optimal one. The efficient approach makes real-time interactions (e.g., bundling and straightening) possible, thus enabling users to better understand and track how the story evolves. This work was presented in IEEE InfoVis 2013. Project page: http://www.ycwu.org/projects/infovis13.html <img style="border:1px solid #C3E6D8;float:right;" alt="" src="https://cdn.slidesharecdn.com/ss_thumbnails/storyflowclean-131024221243-phpapp02-thumbnail.jpg?width=120&height=120&fit=bounds" /><br> Storyline visualizations, which are useful in many applications, aim to illustrate the dynamic relationships between entities in a story. However, the growing complexity and scalability of stories pose great challenges for existing approaches. In this paper, we propose an efficient optimization approach to generating an aesthetically appealing storyline visualization, which effectively handles the hierarchical relationships between entities over time. The approach formulates the storyline layout as a novel hybrid optimization approach that combines discrete and continuous optimization. The discrete method generates an initial layout through the ordering and alignment of entities, and the continuous method optimizes the initial layout to produce the optimal one. The efficient approach makes real-time interactions (e.g., bundling and straightening) possible, thus enabling users to better understand and track how the story evolves. This work was presented in IEEE InfoVis 2013. Project page: http://www.ycwu.org/projects/infovis13.html

StoryFlow - Visually Tracking Evolution of Stories from Yingcai Wu

]]> 9188 11 https://cdn.slidesharecdn.com/ss_thumbnails/storyflowclean-131024221243-phpapp02-thumbnail.jpg?width=120&height=120&fit=bounds presentation White http://activitystrea.ms/schema/1.0/post

http://activitystrea.ms/schema/1.0/posted

0 https://cdn.slidesharecdn.com/profile-photo-ycwu8-48x48.jpg?cb=1523672679 www.ycwu.org https://cdn.slidesharecdn.com/ss_thumbnails/vast13topicomp-131027222043-phpapp01-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/visual-analysis-of-topic-competition-on-social-media/27631416 Visual Analysis of Top... https://cdn.slidesharecdn.com/ss_thumbnails/vis13-light-perceptiontest-131026073901-phpapp01-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/perceptually-based-depthordering-enhancement-for-direct-volume-rendering-27594117/27594117 Perceptually Based Dep... https://cdn.slidesharecdn.com/ss_thumbnails/vis13-light-perceptiontest-131026073418-phpapp01-thumbnail.jpg?width=320&height=320&fit=bounds slideshow/perceptually-based-depthordering-enhancement-for-direct-volume-rendering/27594068 Perceptually Based Dep...