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» Learning Stochastic Logic Programs
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ILP
2003
Springer
14 years 26 days ago
Hybrid Abductive Inductive Learning: A Generalisation of Progol
The learning system Progol5 and the underlying inference method of Bottom Generalisation are firmly established within Inductive Logic Programming (ILP). But despite their success...
Oliver Ray, Krysia Broda, Alessandra Russo
JASIS
2000
143views more  JASIS 2000»
13 years 7 months ago
Discovering knowledge from noisy databases using genetic programming
s In data mining, we emphasize the need for learning from huge, incomplete and imperfect data sets (Fayyad et al. 1996, Frawley et al. 1991, Piatetsky-Shapiro and Frawley, 1991). T...
Man Leung Wong, Kwong-Sak Leung, Jack C. Y. Cheng
SWAP
2008
13 years 9 months ago
Learning SHIQ+log Rules for Ontology Evolution
The definition of new concepts or roles for which extensional knowledge become available can turn out to be necessary to make a DL ontology evolve. In this paper we reformulate thi...
Francesca A. Lisi, Floriana Esposito
ACL
2001
13 years 9 months ago
Extending Lambek Grammars: a Logical Account of Minimalist Grammars
We provide a logical definition of Minimalist grammars, that are Stabler's formalization of Chomsky's minimalist program. Our logical definition leads to a neat relation...
Alain Lecomte, Christian Retoré
ICLP
2009
Springer
14 years 8 months ago
Generative Modeling by PRISM
PRISM is a probabilistic extension of Prolog. It is a high level language for probabilistic modeling capable of learning statistical parameters from observed data. After reviewing ...
Taisuke Sato