DocumentCode :
3432472
Title :
Discovering community membership in biological networks with node topology potential
Author :
Xiao, Liping ; Wang, Shuliang ; Li, Jingjing
Author_Institution :
Institute of Chinese Electrical, System Engineering, Beijing 100840, China
fYear :
2012
fDate :
11-13 Aug. 2012
Firstpage :
541
Lastpage :
546
Abstract :
In this paper, a novel approach is proposed to discover community membership in complex networks with node topology potential, along with the experiment on complex biological networks. The concept of physical field is brought into networks. Nodes will have a certain topology potential since they can affect and be affected by the others nearby. And this topology potential is an index to measure the interaction among nodes. Based on the distributing feature of node topology potential, the community memberships are uncovered. A biological network is finally experimented to show the effectiveness of the proposed algorithm.
Keywords :
Artificial neural networks; Communications technology; Communities; Robustness; Shape; community membership; complex biological networks; data field; node topology potential;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Granular Computing (GrC), 2012 IEEE International Conference on
Conference_Location :
Hangzhou, China
Print_ISBN :
978-1-4673-2310-9
Type :
conf
DOI :
10.1109/GrC.2012.6468676
Filename :
6468676
Link To Document :
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