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ISCIS
2005
Springer
13 years 11 months ago
Computing Communities in Large Networks Using Random Walks
Dense subgraphs of sparse graphs (communities), which appear in most real-world complex networks, play an important role in many contexts. Computing them however is generally expe...
Pascal Pons, Matthieu Latapy
CORR
2010
Springer
185views Education» more  CORR 2010»
13 years 5 months ago
Estimating and Sampling Graphs with Multidimensional Random Walks
Estimating characteristics of large graphs via sampling is a vital part of the study of complex networks. Current sampling methods such as (independent) random vertex and random w...
Bruno F. Ribeiro, Donald F. Towsley
CSDA
2010
118views more  CSDA 2010»
13 years 5 months ago
Grapham: Graphical models with adaptive random walk Metropolis algorithms
Recently developed adaptive Markov chain Monte Carlo (MCMC) methods have been applied successfully to many problems in Bayesian statistics. Grapham is a new open source implementat...
Matti Vihola
SIGMETRICS
2010
ACM
147views Hardware» more  SIGMETRICS 2010»
13 years 4 months ago
On random walks in direction-aware network problems
Graph theory provides a powerful set of metrics and conceptual ideas to model and investigate the behavior of communication networks. Most graph-theoretical frameworks in the netw...
Ali Tizghadam, Alberto Leon-Garcia
COLING
2010
13 years 22 days ago
FactRank: Random Walks on a Web of Facts
Fact collections are mostly built using semi-supervised relation extraction techniques and wisdom of the crowds methods, rendering them inherently noisy. In this paper, we propose...
Alpa Jain, Patrick Pantel