Generalized subsumption and its applications to induction and redundancy
Artificial Intelligence
Handbook of theoretical computer science (vol. A)
Handbook of theoretical computer science (vol. B)
Flattening and Saturation: Two Representation Changes for Generalization
Machine Learning - Special issue on evaluating and changing representation
Interactive theory revision: an inductive logic programming approach
Interactive theory revision: an inductive logic programming approach
Machine Learning - special issue on inductive logic programming
Machine Learning for Intelligent Processing of Printed Documents
Journal of Intelligent Information Systems - Special issue on methodologies for intelligent information systems
Advances in Inductive Logic Programming
Advances in Inductive Logic Programming
Machine Learning
What You Always Wanted to Know About Datalog (And Never Dared to Ask)
IEEE Transactions on Knowledge and Data Engineering
Learning Logical Definitions from Relations
Machine Learning
Specialization of Recursive Predicates
ECML '95 Proceedings of the 8th European Conference on Machine Learning
The Many Faces of Inductive Logic Programming
ISMIS '93 Proceedings of the 7th International Symposium on Methodologies for Intelligent Systems
Learning Simple Recursive Theories
ISMIS '93 Proceedings of the 7th International Symposium on Methodologies for Intelligent Systems
Adaptive Layout Analysis of Document Images
ISMIS '02 Proceedings of the 13th International Symposium on Foundations of Intelligent Systems
Correcting the Document Layout: A Machine Learning Approach
ICDAR '03 Proceedings of the Seventh International Conference on Document Analysis and Recognition - Volume 1
Inductive Synthesis of Recursive Functional Programs
KI '07 Proceedings of the 30th annual German conference on Advances in Artificial Intelligence
Learning Recursive Theories in the Normal ILP Setting
Fundamenta Informaticae
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Induction of recursive theories in the normal ILP setting is a complex task because of the non-monotonicity of the consistency property. In this paper we propose computational solutions to some relevant issues raised by the multiple predicate learning problem. A separate-and-parallel-conquer search strategy is adopted to interleave the learning of clauses supplying predicates with mutually recursive definitions. A novel generality order to be imposed to the search space of clauses is investigated in order to cope with recursion in a more suitable way. The consistency recovery is performed by reformulating the current theory and by applying a layering technique based on the collapsed dependency graph. The proposed approach has been implemented in the ILP system ATRE and tested in the specific context of the document understanding problem within the WISDOM project. Experimental results are discussed and future directions are drawn.