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IPPS
2009
IEEE
13 years 11 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
CPHYSICS
2006
124views more  CPHYSICS 2006»
13 years 4 months ago
Collision-free spatial hash functions for structural analysis of billion-vertex chemical bond networks
State-of-the-art molecular dynamics (MD) simulations generate massive datasets involving billion-vertex chemical bond networks, which makes data mining based on graph algorithms s...
Cheng Zhang, Bhupesh Bansal, Paulo S. Branicio, Ra...
BMCBI
2008
115views more  BMCBI 2008»
13 years 4 months ago
BioGraphE: high-performance bionetwork analysis using the Biological Graph Environment
Background: Graphs and networks are common analysis representations for biological systems. Many traditional graph algorithms such as k-clique, k-coloring, and subgraph matching h...
George Chin Jr., Daniel G. Chavarría-Mirand...
PODC
2011
ACM
12 years 7 months ago
Coordinated consensus in dynamic networks
We study several variants of coordinated consensus in dynamic networks. We assume a synchronous model, where the communication graph for each round is chosen by a worst-case adver...
Fabian Kuhn, Rotem Oshman, Yoram Moses
COMSWARE
2008
IEEE
13 years 6 months ago
Extracting dense communities from telecom call graphs
Social networks refer to structures made of nodes that represent people or other entities embedded in a social context, and whose edges represent interaction between entities. Typi...
Vinayaka Pandit, Natwar Modani, Sougata Mukherjea,...