Jiayi Xu

TL;DR: TelCoVis is presented, an interactive visual analytics system, which helps analysts leverage their domain knowledge to gain insight into the co-occurrence in urban human mobility based on telco data by means of biclustering techniques that allow analysts to better explore coordinated relationships among different regions and identify interesting patterns.

TL;DR: The goal is to improve an analyst’s understanding of the SVM modeling process through a suite of visualization techniques that allow users to have full interactive visual control over the entire SVM training process.

TL;DR: This paper presents a suite of visual communication and interaction techniques to support the transfer learning process, and a pioneering visual-assisted transfer learning methodology is proposed in the context of classification.

TL;DR: A novel spatio-temporal flow map layout to visualize when and where people from different locations move into the same places and make contact is proposed and integrated into existing spatiotemporal visualization techniques to form a suite of techniques for visualizing the movement and contact patterns.

TL;DR: This work addresses the challenging problem of incorporating context information into the community analysis with a novel visual analysis mechanism and proposes an enhanced parallel coordinates representation to depict the context and community structures, which allows for interactive data exploration and community investigation.