Inductive Learning for Rule Generation from Ontology

TL;DR

This paper explores the potential of inductive learning techniques to generate rules from ontologies, aiming to enhance the knowledge base of Semantic Web Expert Systems and address a gap in existing research.

Contribution

It evaluates the feasibility of using inductive learning for rule generation from ontologies and proposes methods to implement this process.

Findings

Inductive learning can be applied to generate rules from ontologies.

The approach can supplement existing knowledge bases in Semantic Web systems.

The research addresses a previously underexplored area in rule generation.

Abstract

This paper presents an idea of inductive learning use for rule generation from ontologies. The main purpose of the paper is to evaluate the possibility of inductive learning use in rule generation from ontologies and to develop the way how this can be done. Generated rules are necessary to supplement or even to develop the Semantic Web Expert System (SWES) knowledge base. The SWES emerges as the result of evolution of expert system concept toward the Web, and the SWES is based on the Semantic Web technologies. Available publications show that the problem of rule generation from ontologies based on inductive learning is not investigated deeply enough.