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» Supervised Graph Inference
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EDBT
2009
ACM
277views Database» more  EDBT 2009»
14 years 7 days ago
G-hash: towards fast kernel-based similarity search in large graph databases
Structured data including sets, sequences, trees and graphs, pose significant challenges to fundamental aspects of data management such as efficient storage, indexing, and simila...
Xiaohong Wang, Aaron M. Smalter, Jun Huan, Gerald ...
ICML
2005
IEEE
14 years 8 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...
SEMWEB
2005
Springer
14 years 1 months ago
Representing Probabilistic Relations in RDF
Probabilistic inference will be of special importance when one needs to know how much we can say with what all we know given new observations. Bayesian Network is a graphical prob...
Yoshio Fukushige
ACL
2008
13 years 9 months ago
Semantic Class Learning from the Web with Hyponym Pattern Linkage Graphs
We present a novel approach to weakly supervised semantic class learning from the web, using a single powerful hyponym pattern combined with graph structures, which capture two pr...
Zornitsa Kozareva, Ellen Riloff, Eduard H. Hovy
BMCBI
2010
143views more  BMCBI 2010»
13 years 7 months ago
Learning gene regulatory networks from only positive and unlabeled data
Background: Recently, supervised learning methods have been exploited to reconstruct gene regulatory networks from gene expression data. The reconstruction of a network is modeled...
Luigi Cerulo, Charles Elkan, Michele Ceccarelli