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AAAI
2007
13 years 7 months ago
Probabilistic Community Discovery Using Hierarchical Latent Gaussian Mixture Model
Complex networks exist in a wide array of diverse domains, ranging from biology, sociology, and computer science. These real-world networks, while disparate in nature, often compr...
Haizheng Zhang, C. Lee Giles, Henry C. Foley, John...
CIKM
2009
Springer
13 years 11 months ago
Potential collaboration discovery using document clustering and community structure detection
Complex network analysis is a growing research area in a wide variety of domains and has recently become closely associated with data, text and web mining. One of the most active ...
Cristian Klen dos Santos, Alexandre Evsukoff, Beat...
WWW
2009
ACM
14 years 5 months ago
Extracting community structure through relational hypergraphs
Social media websites promote diverse user interaction on media objects as well as user actions with respect to other users. The goal of this work is to discover community structu...
Yu-Ru Lin, Jimeng Sun, Paul Castro, Ravi B. Konuru...
ICDM
2009
IEEE
125views Data Mining» more  ICDM 2009»
13 years 11 months ago
A Fully Automated Method for Discovering Community Structures in High Dimensional Data
—Identifying modules, or natural communities, in large complex networks is fundamental in many fields, including social sciences, biological sciences and engineering. Recently s...
Jianhua Ruan
CSE
2009
IEEE
13 years 11 months ago
Inferring Unobservable Inter-community Links in Large Social Networks
Abstract—Social networks can be used to model social interactions between individuals. In many circumstances, not all interactions between individuals are observed. In such cases...
Heath Hohwald, Manuel Cebrián, Arturo Canal...