CHI '86 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Interactive graph layout: the exploration of large graphs
Interactive graph layout: the exploration of large graphs
WebOFDAV — navigating and visualizing the Web on-line with animated context swapping
WWW7 Proceedings of the seventh international conference on World Wide Web 7
Authoritative sources in a hyperlinked environment
Journal of the ACM (JACM)
The Eyes Have It: A Task by Data Type Taxonomy for Information Visualizations
VL '96 Proceedings of the 1996 IEEE Symposium on Visual Languages
Intelligent 3d graph exploration with time-travel features
ICCVG'12 Proceedings of the 2012 international conference on Computer Vision and Graphics
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When the amount of information in visualization becomes large enough, users can not perceive all elements at the same time. This problem can be solved by removing parts of the information through the process of Filtering. In this paper, we present a novel method for filtering a graph by measuring the important role property of a node. The basic idea of this approach is to quantify the importance of a node as the degree to which it has direct and indirect relationships with the other nodes in a graph. All the nodes are ranked according to their Node Importance Scores, and those less important nodes and their associated edges are then removed or invisible. In comparison with the rule_based approach, our approach is a structure_based one that makes use of the linkage of nodes rather than their semantics. It can therefore be applied to filter any kinds of connected graphs. The examples and applications provided have demonstrated that our approach can effectively reduce the visual complexities.