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
Constructive induction using a non-greedy strategy for feature selection
ML92 Proceedings of the ninth international workshop on Machine learning
C4.5: programs for machine learning
C4.5: programs for machine learning
Pac-learning nondeterminate clauses
AAAI '94 Proceedings of the twelfth national conference on Artificial intelligence (vol. 1)
The nature of statistical learning theory
The nature of statistical learning theory
Theories for mutagenicity: a study in first-order and feature-based induction
Artificial Intelligence - Special volume on empirical methods
Solving the multiple instance problem with axis-parallel rectangles
Artificial Intelligence
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
Logical settings for concept-learning
Artificial Intelligence
Confirmation-guided discovery of first-order rules with tertius
Machine Learning
Advances in Inductive Logic Programming
Advances in Inductive Logic Programming
Inductive Logic Programming: Techniques and Applications
Inductive Logic Programming: Techniques and Applications
Levelwise Search and Borders of Theories in KnowledgeDiscovery
Data Mining and Knowledge Discovery
A Tutorial on Support Vector Machines for Pattern Recognition
Data Mining and Knowledge Discovery
Discovery of frequent DATALOG patterns
Data Mining and Knowledge Discovery
Data Mining and Knowledge Discovery
A Relevancy Filter for Constructive Induction
IEEE Intelligent Systems
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
An assessment of submissions made to the Predictive Toxicology Evaluation Challenge
IJCAI '99 Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence
Learning Rules That Classify Ocular Fundus Images for Glaucoma Diagnosis
ILP '96 Selected Papers from the 6th 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
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
Estimation of Dependences Based on Empirical Data: Springer Series in Statistics (Springer Series in Statistics)
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
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
Feature Selection for Propositionalization
DS '02 Proceedings of the 5th International Conference on Discovery Science
Demand-Driven Construction of Structural Features in ILP
ILP '01 Proceedings of the 11th International Conference on Inductive Logic Programming
ICDM '03 Proceedings of the Third IEEE International Conference on Data Mining
Statistical Relational Learning for Document Mining
ICDM '03 Proceedings of the Third IEEE International Conference on Data Mining
Aggregation-based feature invention and relational concept classes
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
Multi-relational data mining: an introduction
ACM SIGKDD Explorations Newsletter
Scalability and efficiency in multi-relational data mining
ACM SIGKDD Explorations Newsletter
A survey of kernels for structured data
ACM SIGKDD Explorations Newsletter
Link mining: a new data mining challenge
ACM SIGKDD Explorations Newsletter
Fast Theta-Subsumption with Constraint Satisfaction Algorithms
Machine Learning
Cluster-based concept invention for statistical relational learning
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Naive Bayesian Classification of Structured Data
Machine Learning
An efficient multi-relational Naïve Bayesian classifier based on semantic relationship graph
MRDM '05 Proceedings of the 4th international workshop on Multi-relational mining
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
Spatial associative classification: propositional vs structural approach
Journal of Intelligent Information Systems
Multistrategy Operators for Relational Learning and Their Cooperation
Fundamenta Informaticae
Classification in Networked Data: A Toolkit and a Univariate Case Study
The Journal of Machine Learning Research
Margin-based first-order rule learning
Machine Learning
Extension of the Top-Down Data-Driven Strategy to ILP
Inductive Logic Programming
The Study of Dynamic Aggregation of Relational Attributes on Relational Data Mining
ADMA '07 Proceedings of the 3rd international conference on Advanced Data Mining and Applications
Logic and the Automatic Acquisition of Scientific Knowledge: An Application to Functional Genomics
Computational Discovery of Scientific Knowledge
Description and classification of complex structured objects by applying similarity measures
International Journal of Approximate Reasoning
Towards Machine Learning on the Semantic Web
Uncertainty Reasoning for the Semantic Web I
AAAI'06 proceedings of the 21st national conference on Artificial intelligence - Volume 2
Discovering Knowledge from Multi-relational Data Based on Information Retrieval Theory
ADMA '09 Proceedings of the 5th International Conference on Advanced Data Mining and Applications
Fuzzy Clustering for Categorical Spaces
ISMIS '09 Proceedings of the 18th International Symposium on Foundations of Intelligent Systems
Relational random forests based on random relational rules
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
Learning first-order Bayesian networks
AI'03 Proceedings of the 16th Canadian society for computational studies of intelligence conference on Advances in artificial intelligence
Upgrading ILP rules to first-order Bayesian networks
PAKDD'03 Proceedings of the 7th Pacific-Asia conference on Advances in knowledge discovery and data mining
Learning with feature description logics
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
Discretization numbers for multiple-instances problem in relational database
ADBIS'07 Proceedings of the 11th East European conference on Advances in databases and information systems
Exploiting propositionalization based on random relational rules for semi-supervised learning
PAKDD'08 Proceedings of the 12th Pacific-Asia conference on Advances in knowledge discovery and data mining
Clustering relational data based on randomized propositionalization
ILP'07 Proceedings of the 17th international conference on Inductive logic programming
A phase transition-based perspective on multiple instance kernels
ILP'07 Proceedings of the 17th international conference on Inductive logic programming
Learning with kernels and logical representations
Probabilistic inductive logic programming
Fuzzy Clustering for Semantic Knowledge Bases
Fundamenta Informaticae - Methodologies for Intelligent Systems
Guest Editorial: Global modeling using local patterns
Data Mining and Knowledge Discovery
Optimizing probabilistic models for relational sequence learning
ISMIS'11 Proceedings of the 19th international conference on Foundations of intelligent systems
Informative variables selection for multi-relational supervised learning
MLDM'11 Proceedings of the 7th international conference on Machine learning and data mining in pattern recognition
Label-dependent node classification in the network
Neurocomputing
Good and bad practices in propositionalisation
AI*IA'05 Proceedings of the 9th conference on Advances in Artificial Intelligence
(Agnostic) PAC learning concepts in higher-order logic
ECML'06 Proceedings of the 17th European conference on Machine Learning
Tractable feature generation through description logics with value and number restrictions
IEA/AIE'06 Proceedings of the 19th international conference on Advances in Applied Artificial Intelligence: industrial, Engineering and Other Applications of Applied Intelligent Systems
ADMA'06 Proceedings of the Second international conference on Advanced Data Mining 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
Support vector inductive logic programming
DS'05 Proceedings of the 8th international conference on Discovery Science
MapReduce approach to collective classification for networks
ICAISC'12 Proceedings of the 11th international conference on Artificial Intelligence and Soft Computing - Volume Part I
Conceptual clustering of multi-relational data
ILP'11 Proceedings of the 21st international conference on Inductive Logic Programming
Multistrategy Operators for Relational Learning and Their Cooperation
Fundamenta Informaticae
AI'12 Proceedings of the 25th Australasian joint conference on Advances in Artificial Intelligence
Simple decision forests for multi-relational classification
Decision Support Systems
Annals of Mathematics and Artificial Intelligence
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This chapter surveys methods that transform a relational representation of a learning problem into a propositional (feature-based, attribute-value) representation. This kind of representation change is known as propositionalization. Taking such an approach, feature construction can be decoupled from model construction. It has been shown that in many relational data mining applications this can be done without loss of predictive performance. After reviewing both general-purpose and domain-dependent propositionalization approaches from the literature, an extension to the LINUS propositionalization method that overcomes the system's earlier inability to deal with non-determinate local variables is described.