CHI '86 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
The perspective wall: detail and context smoothly integrated
CHI '91 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Cone Trees: animated 3D visualizations of hierarchical information
CHI '91 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
A review and taxonomy of distortion-oriented presentation techniques
ACM Transactions on Computer-Human Interaction (TOCHI)
CHI '94 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Communications of the ACM
Proceedings of the 8th annual ACM symposium on User interface and software technology
Readings in information visualization: using vision to think
Readings in information visualization: using vision to think
Fisheyes are good for large steering tasks
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Efficient Analysis of Graph Properties on Context-free Graph Languages (Extended Abstract)
ICALP '88 Proceedings of the 15th International Colloquium on Automata, Languages and Programming
Straight-Line Drawing Algorithms for Hierarchical Graphs and Clustered Graphs
GD '96 Proceedings of the Symposium on Graph Drawing
Techniques for non-linear magnification transformations
INFOVIS '96 Proceedings of the 1996 IEEE Symposium on Information Visualization (INFOVIS '96)
Degree-of-interest trees: a component of an attention-reactive user interface
Proceedings of the Working Conference on Advanced Visual Interfaces
ACM Transactions on Intelligent Systems and Technology (TIST) - Special Section on Intelligent Mobile Knowledge Discovery and Management Systems and Special Issue on Social Web Mining
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Presenting large amounts of information in a limited screen space is a significant challenge in the field of Information Visualization. With the rapid development and growing use of small handheld devices such as PDAs this issue has become more important. Many Focus+Context techniques have been developed to address it but very few of them would effectively aid visualization applications for small handheld devices.In this paper we propose a new approach for visualizing a clustered graph by adding filtering to geometric distortion. Different from most existing techniques, our approach focuses on contextual information. Beginning with the assumption that not all contextual information is necessary to visualize a user's interests, we propose an approach for filtering out some "useless" context to compensate for the small screen size.Samples of applying the proposed approach to visualization of a rooted tree and a clustered graph on a small screen are presented. The limitations are also discussed.