2011 · 606 citations · 19 references
ComputingComputer ScienceAlgorithmsData StructuresParallel ComputingGraph AlgorithmsGraph-based LearningSocial Network AnalysisClusteringCompressionGraph CompressionGraph DecompositionsGraph SparsificationLabel PropagationScalable ClusteringScalable Graph Algorithms
We continue the line of research on graph compression started with WebGraph, but we move our focus to the compression of social networks in a proper sense (e.g., LiveJournal): the approaches that have been used for a long time to compress web graphs rely on a specific ordering of the nodes (lexicographical URL ordering) whose extension to general social networks is not trivial. In this paper, we propose a solution that mixes clusterings and orders, and devise a new algorithm, called Layered Label Propagation, that builds on previous work on scalable clustering and can be used to reorder very large graphs (billions of nodes). Our implementation uses task decomposition to perform aggressively on multi-core architecture, making it possible to reorder graphs of more than 600 millions nodes in a few hours.
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Finding and evaluating community structure in networks
Michelle G. Newman, Michelle Girvan · Physical Review E · 2004 · 14.1K citations · Full text
Santo Fortunato · Physics Reports · 2009 · 11.3K citations · Full text
Paolo Boldi, Sebastiano Vigna · 2004 · 1.2K citations