Communications of the ACM
Rule induction with CN2: some recent improvements
EWSL-91 Proceedings of the European working session on learning on Machine learning
Conceptual clustering in a first order logic representation
ECAI '92 Proceedings of the 10th European conference on Artificial intelligence
Learning Conjunctions of Horn Clauses
Machine Learning - Computational learning theory
C4.5: programs for machine learning
C4.5: programs for machine learning
Mining association rules between sets of items in large databases
SIGMOD '93 Proceedings of the 1993 ACM SIGMOD international conference on Management of data
Using the m-estimate in rule induction
Journal of Computing and Information Technology
First-order jk-clausal theories are PAC-learnable
Artificial Intelligence
Applications of inductive logic programming
Communications of the ACM
A maximum entropy approach to natural language processing
Computational Linguistics
Theories for mutagenicity: a study in first-order and feature-based induction
Artificial Intelligence - Special volume on empirical methods
Machine Learning - special issue on inductive logic programming
Fast discovery of association rules
Advances in knowledge discovery and data mining
Logical settings for concept-learning
Artificial Intelligence
Top-down induction of first-order logical decision trees
Artificial Intelligence
An interference matching technique for inducing abstractions
Communications of the ACM
Advances in Inductive Logic Programming
Advances in Inductive Logic Programming
Foundations of Inductive Logic Programming
Foundations of Inductive Logic Programming
Learning Logical Definitions from Relations
Machine Learning
Machine Learning
Machine Learning
ILP Experiments in Detecting Traffic Problems
ECML '98 Proceedings of the 10th European Conference on Machine Learning
A Process-Oriented Heuristic for Model Selection
ICML '98 Proceedings of the Fifteenth International Conference on Machine Learning
On Multi-class Problems and Discretization in Inductive Logic Programming
ISMIS '97 Proceedings of the 10th International Symposium on Foundations of Intelligent Systems
ALT '95 Proceedings of the 6th International Conference on Algorithmic Learning Theory
Probabilistic First-Order Classification
ILP '97 Proceedings of the 7th International Workshop on Inductive Logic Programming
Mining Association Rules in Multiple Relations
ILP '97 Proceedings of the 7th International Workshop on Inductive Logic Programming
Attribute-Value Learning Versus Inductive Logic Programming: The Missing Links (Extended Abstract)
ILP '98 Proceedings of the 8th International Workshop on Inductive Logic Programming
Relational Distance-Based Clustering
ILP '98 Proceedings of the 8th International Workshop on Inductive Logic Programming
Learning First-Order Acyclic Horn Programs from Entailment
ILP '98 Proceedings of the 8th International Workshop on Inductive Logic Programming
Strongly Typed Inductive Concept Learning
ILP '98 Proceedings of the 8th International Workshop on Inductive Logic Programming
Maximum Entropy Modeling with Clausal Constraints
ILP '97 Proceedings of the 7th International Workshop on Inductive Logic Programming
Learning first-order definitions of functions
Journal of Artificial Intelligence Research
Learning first-order definitions of functions
Journal of Artificial Intelligence Research
The predictive toxicology evaluation challenge
IJCAI'97 Proceedings of the 15th international joint conference on Artifical intelligence - Volume 1
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 1
Multi-relational Data Mining: a perspective
EPIA '01 Proceedings of the10th Portuguese Conference on Artificial Intelligence on Progress in Artificial Intelligence, Knowledge Extraction, Multi-agent Systems, Logic Programming and Constraint Solving
Statistical Relational Learning for Document Mining
ICDM '03 Proceedings of the Third IEEE International Conference on Data Mining
Multi-relational data mining: an introduction
ACM SIGKDD Explorations Newsletter
Integrating Guidance into Relational Reinforcement Learning
Machine Learning
Bottom-up learning of Markov logic network structure
Proceedings of the 24th international conference on Machine learning
An Inductive Logic Programming Approach to Statistical Relational Learning
Proceedings of the 2005 conference on An Inductive Logic Programming Approach to Statistical Relational Learning
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We describe a methodology for upgrading existing attribute-value learners towards first-order logic. This method has several advantages: one can profit from existing research on propositional learners (and inherit its efficiency and effectiveness), relational learners (and inherit its expressiveness) and PAC-learning (and inherit its theoretical basis). Moreover there is a clear relationship between the new relational system and its propositional counterpart. This makes the ILP system easy to use and understand by users familiar with the propositional counterpart. We demonstrate the methodology on the ICL system which is an upgrade of the propositional learner CN2.