This article presents an innovative knowledge management approach for the validation and transfer of knowledge between semantic networks or ontologies and a target ontology represented in web ontology language (OWL) format. This process has been designed for addressing the quality improvement of ontologies automatically created by learning techniques. The knowledge transfer process is a semi-automatic computer aided method to assist the domain expert to improve the target ontology. To validate our proposal, we have used an automatically generated target ontology. We used knowledge transfer from the well-known Babelnet semantic graph and a manually generated ontology to improve the quality of the target ontology. Finally, to show the suitability of our proposal in the ontology-fixing process, we compare the improved target ontology resulting from the application of the proposed validation and knowledge transfer techniques with its original version. We developed an example of our proposal in our OntologyFixer tool, which is available on a GitHub repository (https://github.com/gabyluna/OntologyFixer/tree/ontofixer_v2).

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Automatic knowledge exchange,Ontology,Ontology fixing,Ontology quality,Semantic graph

• Computer and Information Sciences - Natural Sciences
• Media and Communications - Social Sciences
• Other Social Sciences - Social Sciences

This publication is an output of the following project(s):

• Alternative Shaper
• Image and Video Data Analytics
• Impact of Blockchains and Decentralised Ledger Technologies