Visualizing community centric network layouts
We present our COMmunity Boundary (COMB) and COMmunity Circles (COMC) network layout algorithms that focus on revealing the structure of discovered communities and the relationships between these communities. We believe this information is vital when developing new community mining algorithms as it...
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| creator | Fagnan, J. Zaiane, O. Goebel, R. |
| description | We present our COMmunity Boundary (COMB) and COMmunity Circles (COMC) network layout algorithms that focus on revealing the structure of discovered communities and the relationships between these communities. We believe this information is vital when developing new community mining algorithms as it allows the viewer to more quickly assess the quality of a mining result without appealing to large tables of statistics. To implement our algorithms we have introduced numerous modifications to the existing Fruchterman-Reingold layout, including support for multi-sized vertices, removal of the bounding frame, introduction of circular bounding boxes, and a novel slotting system. Our evaluation argues that both COMB and COMC outperform existing alternatives in their ability to reveal community structure and emphasize inter-community relations. |
| doi_str_mv | 10.1109/IV.2012.61 |
| format | Conference Proceeding |
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| identifier | ISSN: 1550-6037 |
| ispartof | 2012 16th International Conference on Information Visualisation, 2012, p.321-330 |
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| source | IEEE Electronic Library (IEL) Conference Proceedings |
| subjects | Communities Feeds Force Inference algorithms Layout Proteins Visualization |
| title | Visualizing community centric network layouts |
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