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dc.contributor.authorArchambault, Danielen_US
dc.contributor.authorMunzner, Tamaraen_US
dc.contributor.authorAuber, Daviden_US
dc.contributor.editorK. Museth and T. Moeller and A. Ynnermanen_US
dc.date.accessioned2014-01-31T07:10:59Z
dc.date.available2014-01-31T07:10:59Z
dc.date.issued2007en_US
dc.identifier.isbn978-3-905673-45-6en_US
dc.identifier.issn1727-5296en_US
dc.identifier.urihttp://dx.doi.org/10.2312/VisSym/EuroVis07/067-074en_US
dc.description.abstractGrouse is a feature-based approach to steerable exploration of a graph and an associated hierarchy. Steerability allows exploration to begin immediately, rather than requiring a costly layout of the entire graph as an initial step. In a feature-based approach, the subgraph inside a metanode of the graph hierarchy is laid out with a well- chosen algorithm appropriate for its topological structure. Grouse preserves the input hierarchy, which provides meaningful information to the user when its metanodes correspond to features of interest. When a metanode in the hierarchy is opened, a limited number of metanodes are laid out again along the path between the opened node and the root. We demonstrate the effectiveness of Grouse on datasets from IMDB, the Internet Movie Database, where nodes are actors and cliques represent movies. The combination of feature-based layout and limited relayout computation does not fragment features in the hierarchy and improves the number of levels in the hierarchy that can be seen at once over previous approaches.en_US
dc.publisherThe Eurographics Associationen_US
dc.subjectCategories and Subject Descriptors (according to ACM CCS): H.5.0 [Information Systems]: Information Interfaces and Presentation: General; G.2.2 [Discrete Mathematics]: Graph Theory: Graph Algorithmsen_US
dc.titleGrouse: Feature-Based, Steerable Graph Hierarchy Explorationen_US
dc.description.seriesinformationEurographics/ IEEE-VGTC Symposium on Visualizationen_US


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