Part2 chapter2

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Learning Onto-Relational Rules with Inductive Logic Programming
Authors Francesca A. LISI
Part Logical Learning
Topics ILP, Concept Learning
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Learning Onto-Relational Rules with Inductive Logic Programming

The chapter "Learning Onto-Relational Rules with Inductive Logic Programming" was written by Francesca A. LISI.

Abstract

Rules complement and extend ontologies on the Semantic Web. We refer to these rules as onto-relational since they combine DL-based ontology languages and Knowledge Representation formalisms supporting the relational data model within the tradition of Logic Programming and Deductive Databases. Rule authoring is a very demanding Knowledge Engineering task which can be automated though partially by applying Machine Learning algorithms. In this chapter we show how Inductive Logic Programming (ILP), born at the intersection of Machine Learning and Logic Programming and considered as a major approach to Relational Learning, can be adapted to Onto-Relational Learning. For the sake of illustration, we provide details of a specific Onto-Relational Learning solution to the problem of learning rule-based definitions of DL concepts and roles with ILP.

Topics / Key Words

ILP, Concept Learning


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Facts about Part2 chapter2RDF feed
AbstractRules complement and extend ontologies on Rules complement and extend ontologies on the Semantic Web. We refer to these rules as onto-relational since they combine DL-based ontology languages

and Knowledge Representation formalisms supporting the relational data model within the tradition of Logic Programming and Deductive Databases. Rule authoring is a very demanding Knowledge Engineering task which can be automated though partially by applying Machine Learning algorithms. In this chapter we show how Inductive Logic Programming (ILP), born at the intersection of Machine Learning and Logic Programming and considered as a major approach to Relational Learning, can be adapted to Onto-Relational Learning. For the sake of illustration, we provide details of a specific Onto-Relational Learning solution to

the problem of learning rule-based definitions of DL concepts and roles with ILP.
nitions of DL concepts and roles with ILP.
AuthorFrancesca A. LISI  +
Book part titleLogical Learning  +
Chapter titleLearning Onto-Relational Rules with Inductive Logic Programming  +
TopicsILP  +, and Concept Learning  +
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