Information Processing Letters
Foundations of logic programming; (2nd extended ed.)
Foundations of logic programming; (2nd extended ed.)
Learning from good and bad data
Learning from good and bad data
Implication of clauses is undecidable
Theoretical Computer Science
Removing redundancy from a clause
Artificial Intelligence
A Machine-Oriented Logic Based on the Resolution Principle
Journal of the ACM (JACM)
Multistrategy Theory Revision: Induction and Abductionin INTHELEX
Machine Learning - Special issue on multistrategy learning
Reasoning with Logic Programming
Reasoning with Logic Programming
Foundations of Inductive Logic Programming
Foundations of Inductive Logic Programming
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
Ideal Theory Refinement under Object Identity
ICML '00 Proceedings of the Seventeenth International Conference on Machine Learning
Locally Finite, Proper and Complete Operators for Refining Datalog Programs
ISMIS '96 Proceedings of the 9th International Symposium on Foundations of Intelligent Systems
Minimal Generalizations under OI-Implication
ISMIS '02 Proceedings of the 13th International Symposium on Foundations of Intelligent Systems
A General Similarity Framework for Horn Clause Logic
Fundamenta Informaticae
Spaces of theories with ideal refinement operators
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
Plugging Taxonomic Similarity in First-Order Logic Horn Clauses Comparison
AI*IA '09: Proceedings of the XIth International Conference of the Italian Association for Artificial Intelligence Reggio Emilia on Emergent Perspectives in Artificial Intelligence
Generalization-based similarity for conceptual clustering
MCD'07 Proceedings of the 3rd ECML/PKDD international conference on Mining complex data
Plugging numeric similarity in first-order logic horn clauses comparison
AI*IA'11 Proceedings of the 12th international conference on Artificial intelligence around man and beyond
A General Similarity Framework for Horn Clause Logic
Fundamenta Informaticae
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A framework for theory refinement is presented pursuing the efficiency and effectiveness of learning regarded as a search process. A refinement operator satisfying these requirements is formally defined as ideal. Past results have demonstrated the impossibility of specifying ideal operators in search spaces where standard generalization models, like logical implication or &thetas;-subsumption, are adopted. By assuming the object identity bias over a space defined by a clausal language ordered by logical implication, a novel generalization model, named OI-implication, is derived and we prove that ideal operators can be defined for the resulting search space.