Logic programming and databases
Logic programming and databases
Distance Induction in First Order Logic
ILP '97 Proceedings of the 7th International Workshop on Inductive Logic Programming
A Framework for Defining Distances Between First-Order Logic Objects
ILP '98 Proceedings of the 8th International Workshop on Inductive Logic Programming
Relational Distance-Based Clustering
ILP '98 Proceedings of the 8th International Workshop on Inductive Logic Programming
Distances and Limits on Herbrand Interpretations
ILP '98 Proceedings of the 8th International Workshop on Inductive Logic Programming
Kernel Methods for Pattern Analysis
Kernel Methods for Pattern Analysis
Kernels and Distances for Structured Data
Machine Learning
Kernels on Prolog Proof Trees: Statistical Learning in the ILP Setting
The Journal of Machine Learning Research
Learning with Kernels in Description Logics
ILP '08 Proceedings of the 18th international conference on Inductive Logic Programming
Statistical Learning for Inductive Query Answering on OWL Ontologies
ISWC '08 Proceedings of the 7th International Conference on The Semantic Web
kFOIL: learning simple relational kernels
AAAI'06 Proceedings of the 21st national conference on Artificial intelligence - Volume 1
Induction of optimal semantic semi-distances for clausal knowledge bases
ILP'07 Proceedings of the 17th international conference on Inductive logic programming
Support vector inductive logic programming
DS'05 Proceedings of the 8th international conference on Discovery Science
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Many applicative domains require complex multi-relational representations. We propose a family of kernels for relational representations to produce statistical classifiers that can be effectively employed in a variety of such tasks. The kernel functions are defined over the set of objects in a knowledge base parameterized on a notion of context, represented by a committee of concepts expressed through logic clauses. A preliminary feature construction phase based on genetic programming allows for the selection of optimized contexts. An experimental session on the task of similarity search proves the practical effectiveness of the method.