Applications of inductive logic programming
Communications of the ACM
Theories for mutagenicity: a study in first-order and feature-based induction
Artificial Intelligence - Special volume on empirical methods
Wrappers for feature subset selection
Artificial Intelligence - Special issue on relevance
Distance based approaches to relational learning and clustering
Relational Data Mining
Learning Logical Definitions from Relations
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A Framework for Defining Distances Between First-Order Logic Objects
ILP '98 Proceedings of the 8th International Workshop on Inductive Logic Programming
Overfitting in making comparisons between variable selection methods
The Journal of Machine Learning Research
Statistical Relational Learning for Document Mining
ICDM '03 Proceedings of the Third IEEE International Conference on Data Mining
A survey of kernels for structured data
ACM SIGKDD Explorations Newsletter
Learning the Kernel Matrix with Semidefinite Programming
The Journal of Machine Learning Research
Kernels and Distances for Structured Data
Machine Learning
Learning the Kernel Function via Regularization
The Journal of Machine Learning Research
Kernels on Prolog Proof Trees: Statistical Learning in the ILP Setting
The Journal of Machine Learning Research
nFOIL: integrating Naïve Bayes and FOIL
AAAI'05 Proceedings of the 20th national conference on Artificial intelligence - Volume 2
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 1
An integrated approach to learning bayesian networks of rules
ECML'05 Proceedings of the 16th European conference on Machine Learning
Support vector inductive logic programming
DS'05 Proceedings of the 8th international conference on Discovery Science
An integrated approach to feature invention and model construction for drug activity prediction
Proceedings of the 24th international conference on Machine learning
Learning from interpretations: a rooted kernel for ordered hypergraphs
Proceedings of the 24th international conference on Machine learning
Margin-based first-order rule learning
Machine Learning
k-RNN: k-relational nearest neighbour algorithm
Proceedings of the 2008 ACM symposium on Applied computing
Discriminative structure and parameter learning for Markov logic networks
Proceedings of the 25th international conference on Machine learning
Optimizing Feature Sets for Structured Data
ECML '07 Proceedings of the 18th European conference on Machine Learning
Discriminative Structure Learning of Markov Logic Networks
ILP '08 Proceedings of the 18th international conference on Inductive Logic Programming
Feature Construction Using Theory-Guided Sampling and Randomised Search
ILP '08 Proceedings of the 18th international conference on Inductive Logic Programming
Towards Machine Learning on the Semantic Web
Uncertainty Reasoning for the Semantic Web I
Compile the Hypothesis Space: Do it Once, Use it Often
Fundamenta Informaticae - Progress on Multi-Relational Data Mining
Multi-class protein fold recognition using large margin logic based divide and conquer learning
Proceedings of the KDD-09 Workshop on Statistical and Relational Learning in Bioinformatics
An l 1 Regularization Framework for Optimal Rule Combination
ECML PKDD '09 Proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases: Part I
Relational random forests based on random relational rules
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
Learning Large Margin First Order Decision Lists for Multi-Class Classification
DS '09 Proceedings of the 12th International Conference on Discovery Science
Learning with kernels and logical representations
ILP'07 Proceedings of the 17th international conference on Inductive logic programming
Induction of optimal semantic semi-distances for clausal knowledge bases
ILP'07 Proceedings of the 17th international conference on Inductive logic programming
Combining clauses with various precisions and recalls to produce accurate probabilistic estimates
ILP'07 Proceedings of the 17th international conference on Inductive logic programming
An overview of AI research in Italy
Artificial intelligence
Learning with kernels and logical representations
Probabilistic inductive logic programming
Trading expressivity for efficiency in statistical relational learning: Ph.D. thesis abstract
ACM SIGKDD Explorations Newsletter
Multi-Class protein fold recognition using large margin logic based divide and conquer learning
ACM SIGKDD Explorations Newsletter
Parameter Screening and Optimisation for ILP using Designed Experiments
The Journal of Machine Learning Research
Boosting learning and inference in Markov logic through metaheuristics
Applied Intelligence
Relational kernel machines for learning from graph-structured RDF data
ESWC'11 Proceedings of the 8th extended semantic web conference on The semantic web: research and applications - Volume Part I
Learning with semantic kernels for clausal knowledge bases
ISMIS'11 Proceedings of the 19th international conference on Foundations of intelligent systems
Enhancing activity recognition in smart homes using feature induction
DaWaK'11 Proceedings of the 13th international conference on Data warehousing and knowledge discovery
Fisher kernels for relational data
ECML'06 Proceedings of the 17th European conference on Machine Learning
Relational Feature Mining with Hierarchical Multitask kFOIL
Fundamenta Informaticae - Machine Learning in Bioinformatics
Subgroup discovery using bump hunting on multi-relational histograms
ILP'11 Proceedings of the 21st international conference on Inductive Logic Programming
Conceptual clustering of multi-relational data
ILP'11 Proceedings of the 21st international conference on Inductive Logic Programming
Compile the Hypothesis Space: Do it Once, Use it Often
Fundamenta Informaticae - Progress on Multi-Relational Data Mining
A new relational Tri-training system with adaptive data editing for inductive logic programming
Knowledge-Based Systems
Scalable relation prediction exploiting both intrarelational correlation and contextual information
ECML PKDD'12 Proceedings of the 2012 European conference on Machine Learning and Knowledge Discovery in Databases - Volume Part I
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A novel and simple combination of inductive logic programming with kernel methods is presented. The kFOIL algorithm integrates the well-known inductive logic programming system FOIL with kernel methods. The feature space is constructed by leveraging FOIL search for a set of relevant clauses. The search is driven by the performance obtained by a support vector machine based on the resulting kernel. In this way, kFOIL implements a dynamic propositionalization approach. Both classification and regression tasks can be naturally handled. Experiments in applying kFOIL to well-known benchmarks in chemoinformatics show the promise of the approach.