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COMSWARE
2008
IEEE
13 years 9 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,...
IJAR
2010
152views more  IJAR 2010»
13 years 6 months ago
Structural-EM for learning PDG models from incomplete data
Probabilistic Decision Graphs (PDGs) are a class of graphical models that can naturally encode some context specific independencies that cannot always be efficiently captured by...
Jens D. Nielsen, Rafael Rumí, Antonio Salme...
SDM
2009
SIAM
162views Data Mining» more  SDM 2009»
14 years 5 months ago
Link Propagation: A Fast Semi-supervised Learning Algorithm for Link Prediction.
We propose Link Propagation as a new semi-supervised learning method for link prediction problems, where the task is to predict unknown parts of the network structure by using aux...
Hisashi Kashima, Tsuyoshi Kato, Yoshihiro Yamanish...
ICASSP
2011
IEEE
12 years 11 months ago
Content preference estimation in online social networks: Message passing versus sparse reconstruction on graphs
We design two different strategies for computing the unknown content preferences in an online social network based on a small set of nodes in the corresponding social graph for wh...
Jacob Chakareski
CORR
2010
Springer
180views Education» more  CORR 2010»
13 years 8 months ago
A Network Coding Approach to Loss Tomography
Network tomography aims at inferring internal network characteristics based on measurements at the edge of the network. In loss tomography, in particular, the characteristic of in...
Athina Markopoulou, Christina Fragouli, Minas Gjok...