Foundations of logic programming; (2nd extended ed.)
Foundations of logic programming; (2nd extended ed.)
Principles of database and knowledge-base systems, Vol. I
Principles of database and knowledge-base systems, Vol. I
KARDIO: a study in deep and qualitative knowledge for expert systems
KARDIO: a study in deep and qualitative knowledge for expert systems
Boolean Feature Discovery in Empirical Learning
Machine Learning
Rule induction with CN2: some recent improvements
EWSL-91 Proceedings of the European working session on learning on Machine learning
Learning nonrecursive definitions of relations with LINUS
EWSL-91 Proceedings of the European working session on learning on Machine learning
PAC-learnability of determinate logic programs
COLT '92 Proceedings of the fifth annual workshop on Computational learning theory
Constructive induction using a non-greedy strategy for feature selection
ML92 Proceedings of the ninth international workshop on Machine learning
Flattening and Saturation: Two Representation Changes for Generalization
Machine Learning - Special issue on evaluating and changing representation
Solving the multiple instance problem with axis-parallel rectangles
Artificial Intelligence
Advances in knowledge discovery and data mining
Advances in knowledge discovery and data mining
Explora: a multipattern and multistrategy discovery assistant
Advances in knowledge discovery and data mining
Fast discovery of association rules
Advances in knowledge discovery and data mining
Data mining: practical machine learning tools and techniques with Java implementations
Data mining: practical machine learning tools and techniques with Java implementations
Confirmation-guided discovery of first-order rules with tertius
Machine Learning
Inductive Logic Programming: From Machine Learning to Software Engineering
Inductive Logic Programming: From Machine Learning to Software Engineering
Foundations of Inductive Logic Programming
Foundations of Inductive Logic Programming
Inductive Logic Programming: Techniques and Applications
Inductive Logic Programming: Techniques and Applications
Discovery of frequent DATALOG patterns
Data Mining and Knowledge Discovery
A Relevancy Filter for Constructive Induction
IEEE Intelligent Systems
Learning Logical Definitions from Relations
Machine Learning
Machine Learning
A Minimization Approach to Propositional Inductive Learning
ECML '95 Proceedings of the 8th European Conference on Machine Learning
An Algorithm for Multi-relational Discovery of Subgroups
PKDD '97 Proceedings of the First European Symposium on Principles of Data Mining and Knowledge Discovery
Background Knowledge and Declarative Bias in Inductive Concept Learning
AII '92 Proceedings of the International Workshop on Analogical and Inductive Inference
Learning Rules That Classify Ocular Fundus Images for Glaucoma Diagnosis
ILP '96 Selected Papers from the 6th International Workshop on Inductive Logic Programming
ILP '96 Selected Papers from the 6th International Workshop on Inductive Logic Programming
ILP '97 Proceedings of the 7th International Workshop on Inductive Logic Programming
Learning Structurally Indeterminate Clauses
ILP '98 Proceedings of the 8th International Workshop on Inductive Logic Programming
Stochastic Propositionalization of Non-determinate Background Knowledge
ILP '98 Proceedings of the 8th 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
Repeat Learning Using Predicate Invention
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
Data Mining using MLC++, A Machine Learning Library in C++
ICTAI '96 Proceedings of the 8th International Conference on Tools with Artificial Intelligence
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
Learning trees and rules with set-valued features
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
Learning in Clausal Logic: A Perspective on Inductive Logic Programming
Computational Logic: Logic Programming and Beyond, Essays in Honour of Robert A. Kowalski, Part I
Feature Selection for Propositionalization
DS '02 Proceedings of the 5th International Conference on Discovery Science
Intelligent data analysis
ICML '04 Proceedings of the twenty-first international conference on Machine learning
Naive Bayesian Classification of Structured Data
Machine Learning
Propositionalization-based relational subgroup discovery with RSD
Machine Learning
Maximally informative k-itemsets and their efficient discovery
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Summarizing gene-expression-based classifiers by meta-mining comprehensible relational patterns
BioMed'06 Proceedings of the 24th IASTED international conference on Biomedical engineering
Compositional mining of multirelational biological datasets
ACM Transactions on Knowledge Discovery from Data (TKDD)
A Mining Algorithm Using Property Items Extracted from Sampled Examples
Inductive Logic Programming
ILP Through Propositionalization and Stochastic k-Term DNF Learning
Inductive Logic Programming
A Genetic-Based Feature Construction Method for Data Summarisation
ADMA '08 Proceedings of the 4th international conference on Advanced Data Mining and Applications
Dynamic Aggregation of Relational Attributes Based on Feature Construction
ADBIS '08 Proceedings of the 12th East European conference on Advances in Databases and Information Systems
Description and classification of complex structured objects by applying similarity measures
International Journal of Approximate Reasoning
ICML '09 Proceedings of the 26th Annual International Conference on Machine Learning
Combining Multiple Interrelated Streams for Incremental Clustering
SSDBM 2009 Proceedings of the 21st International Conference on Scientific and Statistical Database Management
Propositionalization for clustering symbolic relational descriptions
ILP'02 Proceedings of the 12th international conference on Inductive logic programming
RSD: relational subgroup discovery through first-order feature construction
ILP'02 Proceedings of the 12th international conference on Inductive logic programming
Relational pattern mining based on equivalent classes of properties extracted from samples
PAKDD'08 Proceedings of the 12th Pacific-Asia conference on Advances in knowledge discovery and data mining
G3P-MI: A genetic programming algorithm for multiple instance learning
Information Sciences: an International Journal
On enumerating frequent closed patterns with key in multi-relational data
DS'10 Proceedings of the 13th international conference on Discovery science
Prediction of DNA-binding propensity of proteins by the ball-histogram method
ISBRA'11 Proceedings of the 7th international conference on Bioinformatics research and applications
Local patterns: theory and practice of constraint-based relational subgroup discovery
LPD'04 Proceedings of the 2004 international conference on Local Pattern Detection
Efficient sampling in relational feature spaces
ILP'05 Proceedings of the 15th international conference on Inductive Logic Programming
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Inductive logic programming (ILP) is concerned with learning relational descriptions that typically have the form of logic programs. In a transformation approach, an ILP task is transformed into an equivalent learning task in a different representation formalism. Propositionalization is a particular transformation method, in which the ILP task is compiled to an attribute-value learning task. The main restriction of propositionalization methods such as LINUS is that they are unable to deal with nondeterminate local variables in the body of hypothesis clauses. In this paper we show how this limitation can be overcome., by systematic first-order feature construction using a particular individual-centered feature bias. The approach can be applied in any domain where there is a clear notion of individual. We also show how to improve upon exhaustive first-order feature construction by using a relevancy filter. The proposed approach is illustrated on the “trains” and “mutagenesis” ILP domains.