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» Experiments on Graph Clustering Algorithms
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125
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ISDA
2006
IEEE
15 years 8 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...
PKDD
2009
Springer
175views Data Mining» more  PKDD 2009»
15 years 9 months ago
Latent Dirichlet Bayesian Co-Clustering
Co-clustering has emerged as an important technique for mining contingency data matrices. However, almost all existing coclustering algorithms are hard partitioning, assigning each...
Pu Wang, Carlotta Domeniconi, Kathryn B. Laskey
143
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COLOGNETWENTE
2010
14 years 11 months ago
A Branch-and-price Approach to the k-Clustering Minimum Biclique Completion Problem
Given a bipartite graph G = (S, T, E), we consider the problem of finding k bipartite subgraphs, called "clusters", such that each vertex i of S appears in exactly one o...
Stefano Gualandi, Francesco Maffioli, Claudio Magn...
119
Voted
EWCBR
2004
Springer
15 years 7 months ago
Investigating Graphs in Textual Case-Based Reasoning
Textual case-based reasoning (TCBR) provides the ability to reason with domain-specific knowledge when experiences exist in text. Ideally, we would like to find an inexpensive way ...
Colleen Cunningham, Rosina Weber, Jason M. Proctor...
ESWS
2008
Springer
15 years 4 months ago
Instance Based Clustering of Semantic Web Resources
Abstract. The original Semantic Web vision was explicit in the need for intelligent autonomous agents that would represent users and help them navigate the Semantic Web. We argue t...
Gunnar Aastrand Grimnes, Peter Edwards, Alun D. Pr...