Foundations of logic programming; (2nd extended ed.)
Foundations of logic programming; (2nd extended ed.)
Experimental comparison of human and machine learning formalisms
Proceedings of the sixth international workshop on Machine learning
Existence and nonexistence of complete refinement operators
ECML-94 Proceedings of the European conference on machine learning on Machine Learning
Resource-bounded Relational Reasoning: Induction and Deduction Through Stochastic Matching
Machine Learning - Special issue on multistrategy learning
Propositionalization approaches to relational data mining
Relational Data Mining
Learning Logical Definitions from Relations
Machine Learning
Efficient Specialization of Relational Concepts
Machine Learning
Learning Conjunctive Concepts in Structural Domains
Machine Learning
Machine Learning
Some Lower Bounds for the Computational Complexity of Inductive Logic Programming
ECML '93 Proceedings of the European Conference on Machine Learning
Analyzing Relational Learning in the Phase Transition Framework
ICML '00 Proceedings of the Seventeenth International Conference on Machine Learning
On the Stability of Example-Driven Learning Systems: A Case Study in Multirelational Learning
MICAI '02 Proceedings of the Second Mexican International Conference on Artificial Intelligence: Advances in Artificial Intelligence
Learning from Inconsistent and Noisy Data: The AQ18 Approach
ISMIS '99 Proceedings of the 11th International Symposium on Foundations of Intelligent Systems
Efficient Theta-Subsumption Based on Graph Algorithms
ILP '96 Selected Papers from the 6th International Workshop on Inductive Logic Programming
A Logical Framework for Graph Theoretical Decision Tree Learning
ILP '97 Proceedings of the 7th International Workshop on Inductive Logic Programming
Unbiased assessment of learning algorithms
IJCAI'97 Proceedings of the Fifteenth international joint conference on Artifical intelligence - Volume 2
Subsumption and connection graphs
IJCAI'81 Proceedings of the 7th international joint conference on Artificial intelligence - Volume 1
Existential arc consistency: getting closer to full arc consistency in weighted CSPs
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Top-down induction of first-order logical decision trees
Artificial Intelligence
On the Connection Between the Phase Transition of the Covering Test and the Learning Success Rate
Inductive Logic Programming
A Model to Study Phase Transition and Plateaus in Relational Learning
ILP '08 Proceedings of the 18th international conference on Inductive Logic Programming
Empirical Study of Relational Learning Algorithms in the Phase Transition Framework
ECML PKDD '09 Proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases: Part I
Learning discriminant rules as a minimal saturation search
ILP'10 Proceedings of the 20th international conference on Inductive logic programming
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Several upgrades of Attribute-Value learning to Inductive Logic Programming have been proposed and used successfully. However, the Top-Down Data-Driven strategy, popularised by the AQfamily, has not yet been transferred to ILP: if the idea of reducing the hypothesis space by covering a seed example is utilised with systems like PROGOL, Aleph or MIO, these systems do not benefit from the associated data-driven specialisation operator. This operator is given an incorrect hypothesis hand a covered negative example eand outputs a set of hypotheses more specific than hand correct wrt e. This refinement operator is very valuable considering heuristic search problems ILP systems may encounter when crossing plateaus in relational search spaces. In this paper, we present the data-driven strategy of AQ, in terms of a lgg-based change of representation of negative examples given a positive seedexample, and show how it can be extended to ILP. We evaluate a basic implementation of AQin the system Propalon a number of benchmark ILP datasets.