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2008
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SNAP, Small-world Network Analysis and Partitioning: An open-source parallel graph framework for the exploration of large-scale

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SNAP, Small-world Network Analysis and Partitioning: An open-source parallel graph framework for the exploration of large-scale
We present SNAP (Small-world Network Analysis and Partitioning), an open-source graph framework for exploratory study and partitioning of large-scale networks. To illustrate the capability of SNAP, we discuss the design, implementation, and performance of three novel parallel community detection algorithms that optimize modularity, a popular measure for clustering quality in social network analysis. In order to achieve scalable parallel performance, we exploit typical network characteristics of small-world networks, such as the low graph diameter, sparse connectivity, and skewed degree distribution. We conduct an extensive experimental study on real-world graph instances and demonstrate that our parallel schemes, coupled with aggressive algorithm engineering for smallworld networks, give significant running time improvements over existing modularity-based clustering heuristics, with little or no loss in clustering quality. For instance, our divisive clustering approach based on appro...
David A. Bader, Kamesh Madduri
Added 31 May 2010
Updated 31 May 2010
Type Conference
Year 2008
Where IPPS
Authors David A. Bader, Kamesh Madduri
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