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» Modeling Relational Data by the Adjacency Model
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GEOINFORMATICA
1998
125views more  GEOINFORMATICA 1998»
13 years 10 months ago
Computational Perspectives on Map Generalization
ally related entity types, or classes, into higher level, more abstract types, as part of a hierarchical classi®cation scheme. graphy, generalization retains the notion of abstrac...
Robert Weibel, Christopher B. Jones
PVLDB
2010
112views more  PVLDB 2010»
13 years 9 months ago
Querying Probabilistic Information Extraction
Recently, there has been increasing interest in extending relational query processing to include data obtained from unstructured sources. A common approach is to use stand-alone I...
Daisy Zhe Wang, Michael J. Franklin, Minos N. Garo...
BMCBI
2011
13 years 2 months ago
MINE: Module Identification in NEtworks
Background: Graphical models of network associations are useful for both visualizing and integrating multiple types of association data. Identifying modules, or groups of function...
Kahn Rhrissorrakrai, Kristin C. Gunsalus
CVPR
2009
IEEE
15 years 5 months ago
Co-training with Noisy Perceptual Observations
Many perception and multimedia indexing problems involve datasets that are naturally comprised of multiple streams or modalities for which supervised training data is only sparsely...
Ashish Kapoor, Chris Mario Christoudias, Raquel Ur...
ICML
2007
IEEE
14 years 11 months ago
Bottom-up learning of Markov logic network structure
Markov logic networks (MLNs) are a statistical relational model that consists of weighted firstorder clauses and generalizes first-order logic and Markov networks. The current sta...
Lilyana Mihalkova, Raymond J. Mooney