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» Condensed Representations for Inductive Logic Programming
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ML
2006
ACM
131views Machine Learning» more  ML 2006»
13 years 7 months ago
Markov logic networks
We propose a simple approach to combining first-order logic and probabilistic graphical models in a single representation. A Markov logic network (MLN) is a first-order knowledge b...
Matthew Richardson, Pedro Domingos
SWAP
2008
13 years 8 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
PKDD
2007
Springer
146views Data Mining» more  PKDD 2007»
14 years 1 months ago
A Method for Multi-relational Classification Using Single and Multi-feature Aggregation Functions
This paper presents a novel method for multi-relational classification via an aggregation-based Inductive Logic Programming (ILP) approach. We extend the classical ILP representati...
Richard Frank, Flavia Moser, Martin Ester
FUIN
2008
142views more  FUIN 2008»
13 years 7 months ago
Relational Transformation-based Tagging for Activity Recognition
Abstract. The ability to recognize human activities from sensory information is essential for developing the next generation of smart devices. Many human activity recognition tasks...
Niels Landwehr, Bernd Gutmann, Ingo Thon, Luc De R...
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