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SDM
2009
SIAM
167views Data Mining» more  SDM 2009»
16 years 4 months ago
Detecting Communities in Social Networks Using Max-Min Modularity.
Many datasets can be described in the form of graphs or networks where nodes in the graph represent entities and edges represent relationships between pairs of entities. A common ...
Jiyang Chen, Osmar R. Zaïane, Randy Goebel
SDM
2009
SIAM
114views Data Mining» more  SDM 2009»
16 years 4 months ago
Top-k Correlative Graph Mining.
Correlation mining has been widely studied due to its ability for discovering the underlying occurrence dependency between objects. However, correlation mining in graph databases ...
Yiping Ke, James Cheng, Jeffrey Xu Yu
SDM
2009
SIAM
220views Data Mining» more  SDM 2009»
16 years 4 months ago
Bayesian Cluster Ensembles.
Cluster ensembles provide a framework for combining multiple base clusterings of a dataset to generate a stable and robust consensus clustering. There are important variants of th...
Hongjun Wang, Hanhuai Shan, Arindam Banerjee
SDM
2009
SIAM
217views Data Mining» more  SDM 2009»
16 years 4 months ago
A Framework for Exploring Categorical Data.
In this paper, we present a framework for categorical data analysis which allows such data sets to be explored using a rich set of techniques that are only applicable to continuou...
Shyam Boriah, Varun Chandola, Vipin Kumar
SDM
2009
SIAM
118views Data Mining» more  SDM 2009»
16 years 4 months ago
Finding Links and Initiators: A Graph-Reconstruction Problem.
Consider a 0–1 observation matrix M, where rows correspond to entities and columns correspond to signals; a value of 1 (or 0) in cell (i, j) of M indicates that signal j has bee...
Evimaria Terzi, Heikki Mannila
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