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» A Formal Model of Learning Object Metadata
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ICMLA
2009
13 years 5 months ago
Learning Parameters for Relational Probabilistic Models with Noisy-Or Combining Rule
Languages that combine predicate logic with probabilities are needed to succinctly represent knowledge in many real-world domains. We consider a formalism based on universally qua...
Sriraam Natarajan, Prasad Tadepalli, Gautam Kunapu...
ECAI
2010
Springer
13 years 4 months ago
Adaptive Markov Logic Networks: Learning Statistical Relational Models with Dynamic Parameters
Abstract. Statistical relational models, such as Markov logic networks, seek to compactly describe properties of relational domains by representing general principles about objects...
Dominik Jain, Andreas Barthels, Michael Beetz
GECCO
2008
Springer
145views Optimization» more  GECCO 2008»
13 years 8 months ago
An evolutionary approach for competency-based curriculum sequencing
The process of creating e-learning contents using reusable learning objects (LOs) can be broken down in two sub-processes: LOs finding and LO sequencing. Sequencing is usually per...
Luis de Marcos, José-Javier Martínez...
ISOLA
2010
Springer
13 years 6 months ago
LivingKnowledge: Kernel Methods for Relational Learning and Semantic Modeling
Latest results of statistical learning theory have provided techniques such us pattern analysis and relational learning, which help in modeling system behavior, e.g. the semantics ...
Alessandro Moschitti
SAC
2003
ACM
14 years 22 days ago
WebSOGO: A Global Ontology for Describing Web Sources
Based on the limitations raised by existing approaches in the context of the Semantic Web, we propose a formalism, Web Sources Global Ontology (WebSOGO), a data meta-model for the...
Edna Ruckhaus, Maria-Esther Vidal