Generalized subsumption and its applications to induction and redundancy
Artificial Intelligence
Logic programming and databases
Logic programming and databases
Attributive concept descriptions with complements
Artificial Intelligence
Thoughts and afterthoughts on the 1988 Workshop on Principles of Hybrid Reasoning
AI Magazine - Reports from three of the 1990 Spring symposia and eight workshops held over the past two years
A translation approach to portable ontology specifications
Knowledge Acquisition - Special issue: Current issues in knowledge modeling
First-order jk-clausal theories are PAC-learnable
Artificial Intelligence
On the relative expressiveness of description logics and predicate logics
Artificial Intelligence
Machine Learning - special issue on inductive logic programming
ACM Transactions on Database Systems (TODS)
Combining Horn rules and description logics in CARIN
Artificial Intelligence
{\cal A}{\cal L}-log: Integrating Datalog and Description Logics
Journal of Intelligent Information Systems
Equality and Domain Closure in First-Order Databases
Journal of the ACM (JACM)
Foundations of Inductive Logic Programming
Foundations of Inductive Logic Programming
Relational Data Mining
Scaling Up Inductive Logic Programming by Learning from Interpretations
Data Mining and Knowledge Discovery
What You Always Wanted to Know About Datalog (And Never Dared to Ask)
IEEE Transactions on Knowledge and Data Engineering
Learning Logical Definitions from Relations
Machine Learning
Predicate Invention in Inductive Data Engineering
ECML '93 Proceedings of the European Conference on Machine Learning
Nonmonotonic Inductive Logic Programming
LPNMR '01 Proceedings of the 6th International Conference on Logic Programming and Nonmonotonic Reasoning
ILPS '97 International Seminar on Logic Databases and the Meaning of Change, Transactions and Change in Logic Databases
ILP '00 Proceedings of the 10th International Conference on Inductive Logic Programming
Ontological Engineering
Inducing Multi-Level Association Rules from Multiple Relations
Machine Learning
The Description Logic Handbook
The Description Logic Handbook
Tractable Reasoning and Efficient Query Answering in Description Logics: The DL-Lite Family
Journal of Automated Reasoning
Discovery of multivalued dependencies from relations
Intelligent Data Analysis
Conjunctive query containment and answering under description logic constraints
ACM Transactions on Computational Logic (TOCL)
Building rules on top of ontologies for the semantic web with inductive logic programming
Theory and Practice of Logic Programming
Foundations of Onto-Relational Learning
ILP '08 Proceedings of the 18th international conference on Inductive Logic Programming
Conjunctive query answering for the description logic SHIQ
Journal of Artificial Intelligence Research
Query Answering for OWL-DL with rules
Web Semantics: Science, Services and Agents on the World Wide Web
On the decidability and complexity of integrating ontologies and rules
Web Semantics: Science, Services and Agents on the World Wide Web
Learnability of description logic programs
ILP'02 Proceedings of the 12th international conference on Inductive logic programming
Semantic and computational advantages of the safe integration of ontologies and rules
PPSWR'05 Proceedings of the Third international conference on Principles and Practice of Semantic Web Reasoning
DC proposal: ontology learning from noisy linked data
ISWC'11 Proceedings of the 10th international conference on The semantic web - Volume Part II
AL-QuIn: An Onto-Relational Learning System for Semantic Web Mining
International Journal on Semantic Web & Information Systems
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In this paper we address an issue that has been brought to the attention of the database community with the advent of the Semantic Web, i.e., the issue of how ontologies (and semantics conveyed by them) can help solving typical database problems, through a better understanding of Knowledge Representation (KR) aspects related to databases. In particular, we investigate this issue from the ILP perspective by considering two database problems, (i) the definition of views and (ii) the definition of constraints, for a database whose schema is represented also by means of an ontology. Both can be reformulated as ILP problems and can benefit from the expressive and deductive power of the KR framework $\mathcal{DL}+log}^{\neg\vee}$. We illustrate the application scenarios by means of examples.