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Canonical Horn representations and query learning

Autor
Arias, M.; Balcazar, J. L.
Tipus d'activitat
Document cientificotècnic
Data
2009-05
Codi
LSI-09-18-R
Repositori
http://hdl.handle.net/2117/87970 Obrir en finestra nova
Resum
We describe an alternative construction of an existing canonical representation for definite Horn theories, the emph{Guigues-Duquenne} basis (or GD basis), which minimizes a natural notion of implicational size. We extend the canonical representation to general Horn, by providing a reduction from definite to general Horn CNF. We show how this representation relates to two topics in query learning theory: first, we show that a well-known algorithm by Angluin, Frazier and Pitt that learns Horn CNF...
Citació
Arias, M., Balcázar, J. L. "Canonical Horn representations and query learning". 2009.
Paraules clau
Horn Logic, Minimal Representation, Query Learning
Grup de recerca
LARCA - Laboratori d'Algorísmia Relacional, Complexitat i Aprenentatge

Participants

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