DocumentCode :
1658268
Title :
Simulate to Detect: A Multi-agent System for Community Detection
Author :
Cazabet, Remy ; Amblard, Frederic
Author_Institution :
IRIT, Toulouse Univ., Toulouse, France
Volume :
2
fYear :
2011
Firstpage :
402
Lastpage :
408
Abstract :
Community detection in social networks is a well-known problem encountered in many fields. Many traditional algorithms have been proposed to solve it, with recurrent problems: impossibility to deal with dynamic networks, sensitivity to noise, no detection of overlapping communities, exponential running time. This paper proposes a multi-agent system that replays the evolution of a network and, in the same time, reproduces the rise and fall of communities. After presenting the strengths and weaknesses of existing community detection algorithms, we describe the multi-agent system we propose. Then, we compare our solution with existing works, and show some advantages of our method, in particular the possibility to dynamically detect the communities.
Keywords :
multi-agent systems; social networking (online); community detection; dynamic network; multiagent system; social network; Benchmark testing; Communities; Complexity theory; Facebook; Image edge detection; Multiagent systems; Community detection; Dynamic networks; Multi-agent simulation; Social Networks;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Web Intelligence and Intelligent Agent Technology (WI-IAT), 2011 IEEE/WIC/ACM International Conference on
Conference_Location :
Lyon
Print_ISBN :
978-1-4577-1373-6
Electronic_ISBN :
978-0-7695-4513-4
Type :
conf
DOI :
10.1109/WI-IAT.2011.50
Filename :
6040665
Link To Document :
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