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ML
2008
ACM
150views Machine Learning» more  ML 2008»
14 years 11 months ago
Learning probabilistic logic models from probabilistic examples
Abstract. We revisit an application developed originally using Inductive Logic Programming (ILP) by replacing the underlying Logic Program (LP) description with Stochastic Logic Pr...
Jianzhong Chen, Stephen Muggleton, José Car...
SEMWEB
2004
Springer
15 years 5 months ago
Learning Meta-descriptions of the FOAF Network
We argue that in a distributed context, such as the Semantic Web, ontology engineers and data creators often cannot control (or even imagine) the possible uses their data or ontolo...
Gunnar Aastrand Grimnes, Peter Edwards, Alun D. Pr...
AAAI
1996
15 years 1 months ago
Learning to Parse Database Queries Using Inductive Logic Programming
This paper presents recent work using the Chill parser acquisition system to automate the construction of a natural-language interface for database queries. Chill treats parser ac...
John M. Zelle, Raymond J. Mooney
MDAI
2005
Springer
15 years 5 months ago
Meta-data: Characterization of Input Features for Meta-learning
Abstract. Common inductive learning strategies offer the tools for knowledge acquisition, but possess some inherent limitations due to the use of fixed bias during the learning p...
Ciro Castiello, Giovanna Castellano, Anna Maria Fa...
GECCO
2007
Springer
177views Optimization» more  GECCO 2007»
15 years 5 months ago
Evolving problem heuristics with on-line ACGP
Genetic Programming uses trees to represent chromosomes. The user defines the representation space by defining the set of functions and terminals to label the nodes in the trees. ...
Cezary Z. Janikow