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» On Clusterings - Good, Bad and Spectral
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SODA
2010
ACM
189views Algorithms» more  SODA 2010»
15 years 8 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
90
Voted
ICML
2005
IEEE
15 years 12 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
15 years 4 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»
15 years 5 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
15 years 5 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...