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» On Modularity Clustering
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WEA
2010
Springer
316views Algorithms» more  WEA 2010»
14 years 2 months ago
Modularity-Driven Clustering of Dynamic Graphs
Maximizing the quality index modularity has become one of the primary methods for identifying the clustering structure within a graph. As contemporary networks are not static but e...
Robert Görke, Pascal Maillard, Christian Stau...
ACMSE
2007
ACM
14 years 1 months ago
Verifying design modularity, hierarchy, and interaction locality using data clustering techniques
Modularity, hierarchy, and interaction locality are general approaches to reducing the complexity of any large system. A widely used principle in achieving these goals in designin...
Liguo Yu, Srini Ramaswamy
NAACL
2003
13 years 11 months ago
QCS: A Tool for Querying, Clustering, and Summarizing Documents
The QCS information retrieval (IR) system is presented as a tool for querying, clustering, and summarizing document sets. QCS has been developed as a modular development framework...
Daniel M. Dunlavy, John M. Conroy, Dianne P. O'Lea...
ISDA
2006
IEEE
14 years 3 months ago
Modular Neural Network Task Decomposition Via Entropic Clustering
The use of monolithic neural networks (such as a multilayer perceptron) has some drawbacks: e.g. slow learning, weight coupling, the black box effect. These can be alleviated by t...
Jorge M. Santos, Luís A. Alexandre, Joaquim...
IDEAL
2000
Springer
14 years 1 months ago
Observational Learning with Modular Networks
Observational learning algorithm is an ensemble algorithm where each network is initially trained with a bootstrapped data set and virtual data are generated from the ensemble for ...
Hyunjung Shin, Hyoungjoo Lee, Sungzoon Cho