Fuzzy sets and fuzzy logic: theory and applications
Fuzzy sets and fuzzy logic: theory and applications
On the relative expressiveness of description logics and predicate logics
Artificial Intelligence
Equality and Domain Closure in First-Order Databases
Journal of the ACM (JACM)
Foundations of Inductive Logic Programming
Foundations of Inductive Logic Programming
Possibility Theory, Probability Theory and Multiple-Valued Logics: A Clarification
Annals of Mathematics and Artificial Intelligence
Learning Logical Definitions from Relations
Machine Learning
An Induction Algorithm Based on Fuzzy Logic Programming
PAKDD '99 Proceedings of the Third Pacific-Asia Conference on Methodologies for Knowledge Discovery and Data Mining
Improving Expressivity of Inductive Logic Programming by Learning Different Kinds of Fuzzy Rules
Soft Computing - A Fusion of Foundations, Methodologies and Applications - Special issue on soft computing for information mining
The Description Logic Handbook
The Description Logic Handbook
Induction of Fuzzy and Annotated Logic Programs
Inductive Logic Programming
DL-FOIL Concept Learning in Description Logics
ILP '08 Proceedings of the 18th international conference on Inductive Logic Programming
Managing uncertainty and vagueness in description logics for the Semantic Web
Web Semantics: Science, Services and Agents on the World Wide Web
Data Integration through ${\textit{DL-Lite}_{\mathcal A}}$ Ontologies
Semantics in Data and Knowledge Bases
Reasoning within fuzzy description logics
Journal of Artificial Intelligence Research
A faithful integration of description logics with logic programming
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Journal on data semantics X
ILP'10 Proceedings of the 20th international conference on Inductive logic programming
Towards learning fuzzy DL inclusion axioms
WILF'11 Proceedings of the 9th international conference on Fuzzy logic and applications
Top-k retrieval for ontology mediated access to relational databases
Information Sciences: an International Journal
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Fuzzy Description Logics DLs are logics that allow to deal with structured vague knowledge. Although a relatively important amount of work has been carried out in the last years concerning the use of fuzzy DLs as ontology languages, the problem of automatically managing the evolution of fuzzy ontologies has received very little attention so far. We describe here a logic-based computational method for the automated induction of fuzzy ontology axioms which follows the machine learning approach of Inductive Logic Programming. The potential usefulness of the method is illustrated by means of an example taken from the tourism application domain.