Machine Learning - special issue on inductive logic programming
Separate-and-Conquer Rule Learning
Artificial Intelligence Review
Resource-bounded Relational Reasoning: Induction and Deduction Through Stochastic Matching
Machine Learning - Special issue on multistrategy learning
Corpus-based learning of semantic relations by the ILP system, Asium
Learning language in logic
An extended transformation approach to inductive logic programming
ACM Transactions on Computational Logic (TOCL) - Special issue devoted to Robert A. Kowalski
Relational learning and boosting
Relational Data Mining
First-Order Rule Induction for the Recognition of Morphological Patterns in Topographic Maps
MLDM '01 Proceedings of the Second International Workshop on Machine Learning and Data Mining in Pattern Recognition
Discovering Geographic Knowledge: The INGENS System
ISMIS '00 Proceedings of the 12th International Symposium on Foundations of Intelligent Systems
A Rough Set Approach to Inductive Logic Programming
RSCTC '00 Revised Papers from the Second International Conference on Rough Sets and Current Trends in Computing
Knowledge Representation for Inductive Learning
ECSQARU '95 Proceedings of the European Conference on Symbolic and Quantitative Approaches to Reasoning and Uncertainty
Induction of Recursive Theories in the Normal ILP Setting: Issues and Solutions
ILP '00 Proceedings of the 10th International Conference on Inductive Logic Programming
Intelligent data analysis
Naive Bayesian Classification of Structured Data
Machine Learning
Learning Recursive Theories in the Normal ILP Setting
Fundamenta Informaticae
Inductive learning from numerical and symbolic data: An integrated framework
Intelligent Data Analysis
Inductive Logic Programming
Partial Functions and Equality in Answer Set Programming
ICLP '08 Proceedings of the 24th International Conference on Logic Programming
The difficulties of learning logic programs with cut
Journal of Artificial Intelligence Research
Learning first-order definitions of functions
Journal of Artificial Intelligence Research
Learning first-order definitions of functions
Journal of Artificial Intelligence Research
Pac-learning recursive logic programs: efficient algorithms
Journal of Artificial Intelligence Research
Pac-learning recursive logic programs: negative results
Journal of Artificial Intelligence Research
Functional answer set programming
Theory and Practice of Logic Programming
ECML'05 Proceedings of the 16th European conference on Machine Learning
ILP meets knowledge engineering: a case study
ILP'05 Proceedings of the 15th international conference on Inductive Logic Programming
Smart testing of functional programs in isabelle
LPAR'12 Proceedings of the 18th international conference on Logic for Programming, Artificial Intelligence, and Reasoning
Logical approximation for program analysis
Higher-Order and Symbolic Computation
Efficient operations in feature terms using constraint programming
ILP'11 Proceedings of the 21st international conference on Inductive Logic Programming
Learning Recursive Theories in the Normal ILP Setting
Fundamenta Informaticae
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Two representation changes are presented: the first one, called flattening, transforms a first-order logic program with function symbols into an equivalent logic program without function symbols; the second one, called saturation, completes an example description with relevant information with respect to both the example and available background knowledge. The properties of these two represenlation changes are analyzed as well as their influence on a generalization algorithm that takes a single example as input.