A Prototype for Automating Ontology Learning and Ontology Evolution

Gerhard Wohlgenannt, Stefan Belk, Matthias Schett

Abstract

Ontology learning supports ontology engineers in the complex task of creating an ontology. Updating ontologies at regular intervals greatly increases the need for expensive expert contribution. This naturally leads to endeavors to automate the process wherever applicable. This paper presents a model for automated ontology learning and a prototype which demonstrates the feasibility of the proposed approach in learning lightweight domain ontologies. The system learns ontologies from heterogeneous sources periodically and delegates all evaluation processes, eg. the verification of new concept candidates, to a crowdsourcing framework which currently relies on Games with a Purpose. Furthermore, we sketch ontology evolution experiments to trace trends and patterns facilitated by the system.

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Paper Citation


in Harvard Style

Wohlgenannt G., Belk S. and Schett M. (2013). A Prototype for Automating Ontology Learning and Ontology Evolution . In Proceedings of the International Conference on Knowledge Engineering and Ontology Development - Volume 1: KEOD, (IC3K 2013) ISBN 978-989-8565-81-5, pages 407-412. DOI: 10.5220/0004630504070412


in Bibtex Style

@conference{keod13,
author={Gerhard Wohlgenannt and Stefan Belk and Matthias Schett},
title={A Prototype for Automating Ontology Learning and Ontology Evolution},
booktitle={Proceedings of the International Conference on Knowledge Engineering and Ontology Development - Volume 1: KEOD, (IC3K 2013)},
year={2013},
pages={407-412},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004630504070412},
isbn={978-989-8565-81-5},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Knowledge Engineering and Ontology Development - Volume 1: KEOD, (IC3K 2013)
TI - A Prototype for Automating Ontology Learning and Ontology Evolution
SN - 978-989-8565-81-5
AU - Wohlgenannt G.
AU - Belk S.
AU - Schett M.
PY - 2013
SP - 407
EP - 412
DO - 10.5220/0004630504070412