DocumentCode :
3262154
Title :
Visualizing community centric network layouts
Author :
Fagnan, Justin ; Zaïane, Osmar ; Goebel, Randy
Author_Institution :
Dept. of Comput. Sci., Univ. of Alberta, Edmonton, AB, Canada
fYear :
2012
fDate :
11-13 July 2012
Firstpage :
321
Lastpage :
330
Abstract :
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.
Keywords :
data mining; data visualisation; network theory (graphs); COMB; COMC; Fruchterman-Reingold layout; bounding frame removal; circular bounding boxes; community boundary network layout algorithms; community centric network layout visualization; community circles network layout algorithms; community mining algorithms; multisized vertices; slotting system; Communities; Feeds; Force; Inference algorithms; Layout; Proteins; Visualization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Information Visualisation (IV), 2012 16th International Conference on
Conference_Location :
Montpellier
ISSN :
1550-6037
Print_ISBN :
978-1-4673-2260-7
Type :
conf
DOI :
10.1109/IV.2012.61
Filename :
6295833
Link To Document :
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