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» On Clusterings - Good, Bad and Spectral
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SODA
2010
ACM
189views Algorithms» more  SODA 2010»
14 years 5 months ago
Correlation Clustering with Noisy Input
Correlation clustering is a type of clustering that uses a basic form of input data: For every pair of data items, the input specifies whether they are similar (belonging to the s...
Claire Mathieu, Warren Schudy
ICML
2005
IEEE
14 years 9 months ago
Semi-supervised graph clustering: a kernel approach
Semi-supervised clustering algorithms aim to improve clustering results using limited supervision. The supervision is generally given as pairwise constraints; such constraints are...
Brian Kulis, Sugato Basu, Inderjit S. Dhillon, Ray...
WACV
2005
IEEE
14 years 2 months ago
Ensemble Methods in the Clustering of String Patterns
We address the problem of clustering of contour images from hardware tools based on string descriptions, in a comparative study of cluster combination techniques. Several clusteri...
André Lourenço, Ana L. N. Fred
WAW
2009
Springer
138views Algorithms» more  WAW 2009»
14 years 3 months ago
Information Theoretic Comparison of Stochastic Graph Models: Some Experiments
The Modularity-Q measure of community structure is known to falsely ascribe community structure to random graphs, at least when it is naively applied. Although Q is motivated by a ...
Kevin J. Lang
SEMWEB
2009
Springer
14 years 3 months ago
Scalable Distributed Reasoning Using MapReduce
We address the problem of scalable distributed reasoning, proposing a technique for materialising the closure of an RDF graph based on MapReduce. We have implemented our approach o...
Jacopo Urbani, Spyros Kotoulas, Eyal Oren, Frank v...