Title :
A New Community Detection Algorithm Based on Makov-Chains and a Team Formation Model
Author :
McSweeney, Patrick J. ; Mehrotra, Kishan ; Oh, Jae C.
Author_Institution :
Dept. of Eng. & Comput. Sci., Syracuse Univ., Syracuse, NY, USA
Abstract :
Detecting community structure in complex networks is an active area of research that locates dense regions of connections in networks. We suggest a novel algorithm for community detection using a new node-node association metric (based on Markov chains) and a team formation model.
Keywords :
Markov processes; complex networks; information networks; Markov chains; community detection algorithm; complex networks; node-node association metric; team formation model; Algorithm design and analysis; Complex networks; Computer networks; Computer science; Detection algorithms; Iterative algorithms; Optimization methods; Partitioning algorithms; Q measurement; Social network services; Community Detection; Complex Networks; Social Networks;
Conference_Titel :
Social Network Analysis and Mining, 2009. ASONAM '09. International Conference on Advances in
Conference_Location :
Athens
Print_ISBN :
978-0-7695-3689-7
DOI :
10.1109/ASONAM.2009.57
