Foundations of logic programming; (2nd extended ed.)
Foundations of logic programming; (2nd extended ed.)
Abstract interpretation and application to logic programs
Journal of Logic Programming
Static analysis of logic programs for independent and parallelism
Journal of Logic Programming
Inductive logic programming: derivations, successes and shortcomings
ACM SIGART Bulletin
Effectiveness of global analysis in strict independence-based automatic parallelization
ILPS '94 Proceedings of the 1994 International Symposium on Logic programming
Theories for mutagenicity: a study in first-order and feature-based induction
Artificial Intelligence - Special volume on empirical methods
Program Improvement by Source-to-Source Transformation
Journal of the ACM (JACM)
Foundations of Inductive Logic Programming
Foundations of Inductive Logic Programming
Discovery of frequent DATALOG patterns
Data Mining and Knowledge Discovery
A Study of Two Sampling Methods for Analyzing Large Datasets with ILP
Data Mining and Knowledge Discovery
Learning Logical Definitions from Relations
Machine Learning
ALT '95 Proceedings of the 6th International Conference on Algorithmic Learning Theory
Efficient Theta-Subsumption Based on Graph Algorithms
ILP '96 Selected Papers from the 6th International Workshop on Inductive Logic Programming
Part-of-Speech Tagging Using Progol
ILP '97 Proceedings of the 7th International Workshop on Inductive Logic Programming
Induction in first order logic from noisy training examples and fixed example set sizes
Induction in first order logic from noisy training examples and fixed example set sizes
Tractable induction and classification in first order logic via stochastic matching
IJCAI'97 Proceedings of the Fifteenth international joint conference on Artifical intelligence - Volume 2
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 1
Scalability and efficiency in multi-relational data mining
ACM SIGKDD Explorations Newsletter
Fast Theta-Subsumption with Constraint Satisfaction Algorithms
Machine Learning
Analyzing & debugging ILP data mining query execution
Proceedings of the sixth international symposium on Automated analysis-driven debugging
Learning Horn Expressions with LOGAN-H
The Journal of Machine Learning Research
Efficient and Scalable Induction of Logic Programs Using a Deductive Database System
Inductive Logic Programming
Compile the Hypothesis Space: Do it Once, Use it Often
Fundamenta Informaticae - Progress on Multi-Relational Data Mining
Parallel ILP for distributed-memory architectures
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
ILP'07 Proceedings of the 17th international conference on Inductive logic programming
Intelligent Data Analysis - Ubiquitous Knowledge Discovery
When does it pay off to use sophisticated entailment engines in ILP?
ILP'10 Proceedings of the 20th international conference on Inductive logic programming
April: an inductive logic programming system
JELIA'06 Proceedings of the 10th European conference on Logics in Artificial Intelligence
Guiding the search in the NO region of the phase transition problem with a partial subsumption test
ECML'06 Proceedings of the 17th European conference on Machine Learning
On applying tabling to inductive logic programming
ECML'05 Proceedings of the 16th European conference on Machine Learning
ILP'05 Proceedings of the 15th international conference on Inductive Logic Programming
Strategies to parallelize ILP systems
ILP'05 Proceedings of the 15th international conference on Inductive Logic Programming
A study of applying dimensionality reduction to restrict the size of a hypothesis space
ILP'05 Proceedings of the 15th international conference on Inductive Logic Programming
Efficient sampling in relational feature spaces
ILP'05 Proceedings of the 15th international conference on Inductive Logic Programming
Prolog performance on larger datasets
PADL'07 Proceedings of the 9th international conference on Practical Aspects of Declarative Languages
Compile the Hypothesis Space: Do it Once, Use it Often
Fundamenta Informaticae - Progress on Multi-Relational Data Mining
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Relatively simple transformations can speed up the execution of queries for data mining considerably. While some ILP systems use such transformations, relatively little is known about them or how they relate to each other. This paper describes a number of such transformations. Not all of them are novel, but there have been no studies comparing their efficacy. The main contributions of the paper are: (a) it clarifies the relationship between the transformations; (b) it contains an empirical study of what can be gained by applying the transformations; and (c) it provides some guidance on the kinds of problems that are likely to benefit from the transformations.