Paper Info
Title
Simulate to Detect: A Multi-agent System for Community Detection
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.
Year
DOI
Venue
2011
10.1109/WI-IAT.2011.50
IAT
Keywords
Field
DocType
social network,traditional algorithm,dynamic network,overlapping community,recurrent problem,multi-agent system,well-known problem,community detection,community detection algorithm,edge detection,multi agent system,multi agent systems,social networks
Social network,Computer science,Impossibility,Multi-agent system,Artificial intelligence,Strengths and weaknesses,Machine learning,Distributed computing
Conference
Citations 
PageRank 
References 
11
0.66
2
Authors
2
Name
Order
Citations
PageRank
Cazabet Remy11319.71
Frédéric Amblard243051.43