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» On Generating Random Network Structures: Connected Graphs
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114
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IPPS
2009
IEEE
15 years 7 months ago
Compact graph representations and parallel connectivity algorithms for massive dynamic network analysis
Graph-theoretic abstractions are extensively used to analyze massive data sets. Temporal data streams from socioeconomic interactions, social networking web sites, communication t...
Kamesh Madduri, David A. Bader
ICDM
2010
IEEE
230views Data Mining» more  ICDM 2010»
14 years 10 months ago
Clustering Large Attributed Graphs: An Efficient Incremental Approach
In recent years, many networks have become available for analysis, including social networks, sensor networks, biological networks, etc. Graph clustering has shown its effectivenes...
Yang Zhou, Hong Cheng, Jeffrey Xu Yu
WWW
2008
ACM
16 years 1 months ago
Statistical properties of community structure in large social and information networks
A large body of work has been devoted to identifying community structure in networks. A community is often though of as a set of nodes that has more connections between its member...
Jure Leskovec, Kevin J. Lang, Anirban Dasgupta, Mi...
94
Voted
CAS
2008
118views more  CAS 2008»
15 years 16 days ago
A Novel Method for Measuring the Structural Information Content of Networks
In this paper we first present a novel approach to determine the structural information content (graph entropy) of a network represented by an undirected and connected graph. Such...
Matthias Dehmer
PDP
2007
IEEE
15 years 6 months ago
Parallel-External Computation of the Cycle Structure of Invertible Cryptographic Functions
We present an algorithm to compute the cycle structure of large directed graphs where each node has exactly one outgoing edge. Such graphs appear as state diagrams of finite stat...
Andreas Beckmann, Jorg Keller