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KDD
2009
ACM
173views Data Mining» more  KDD 2009»
14 years 9 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
HICSS
2008
IEEE
114views Biometrics» more  HICSS 2008»
14 years 3 months ago
On Structural Analysis of Large Networks
Containing much valuable information, networks such as the World Wide Web, social networks and metabolic networks draw increasingly attention in scientific communities. Network cl...
Nurcan Yuruk, Xiaowei Xu, Thomas A. J. Schweiger
ICDM
2010
IEEE
232views Data Mining» more  ICDM 2010»
13 years 6 months ago
gSkeletonClu: Density-Based Network Clustering via Structure-Connected Tree Division or Agglomeration
Community detection is an important task for mining the structure and function of complex networks. Many pervious approaches are difficult to detect communities with arbitrary size...
Heli Sun, Jianbin Huang, Jiawei Han, Hongbo Deng, ...
SDM
2010
SIAM
182views Data Mining» more  SDM 2010»
13 years 10 months ago
HCDF: A Hybrid Community Discovery Framework
We introduce a novel Bayesian framework for hybrid community discovery in graphs. Our framework, HCDF (short for Hybrid Community Discovery Framework), can effectively incorporate...
Keith Henderson, Tina Eliassi-Rad, Spiros Papadimi...
COMSWARE
2008
IEEE
13 years 10 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,...