Autor:	Darmaillac, Yves, Loustau, Sébastien
Rok vydání:	2016
Předmět:	Computer Science - Social and Information Networks Physics - Physics and Society Statistics - Machine Learning
Druh dokumentu:	Working Paper
Popis:	We introduce a novel algorithm of community detection that maintains dynamically a community structure of a large network that evolves with time. The algorithm maximizes the modularity index thanks to the construction of a randomized hierarchical clustering based on a Monte Carlo Markov Chain (MCMC) method. Interestingly, it could be seen as a dynamization of Louvain algorithm (see Blondel et Al, 2008) where the aggregation step is replaced by the hierarchical instrumental probability. Comment: 12 pages, in progress, experiments are coming
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/1612.01489 Zobrazit plný text záznamu View this record from Arxiv