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KDD
2009
ACM
173views Data Mining» more  KDD 2009»
14 years 8 months ago
Constant-factor approximation algorithms for identifying dynamic communities
We propose two approximation algorithms for identifying communities in dynamic social networks. Communities are intuitively characterized as "unusually densely knit" sub...
Chayant Tantipathananandh, Tanya Y. Berger-Wolf
WSC
2008
13 years 10 months ago
Modeling and simulation of e-mail social networks: A new stochastic agent-based approach
Understanding how the structure of a network evolves over time is one of the most interesting and complex topics in the field of social networks. In our attempt to model the dynam...
Fabian Menges, Bud Mishra, Giuseppe Narzisi
ECAL
2007
Springer
13 years 11 months ago
Evolution of Cooperation in a Population of Selfish Adaptive Agents
Often the selfish and strong are believed to be favored by natural selection, even though cooperative interactions thrive at all levels of organization in living systems. Recent em...
Jorge M. Pacheco, Tom Lenaerts, Francisco C. Santo...
NIPS
2008
13 years 9 months ago
Non-stationary dynamic Bayesian networks
Abstract: Structure learning of dynamic Bayesian networks provide a principled mechanism for identifying conditional dependencies in time-series data. This learning procedure assum...
Joshua W. Robinson, Alexander J. Hartemink
IPPS
2009
IEEE
14 years 2 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