A Prototype for Automating Ontology Learning and Ontology Evolution

Gerhard Wohlgenannt; Stefan Belk; Matthias Schett

A Prototype for Automating Ontology Learning and Ontology Evolution

Gerhard Wohlgenannt, Stefan Belk, Matthias Schett

Publication: Chapter in book/Conference proceeding › Contribution to conference proceedings

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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.(authors' abstract)

Original language	English
Title of host publication	5th International Conference on Knowledge Engineering and Ontology Development (KEOD-2013)
Editors	Joaquim Filipe and Jan Dietz
Place of Publication	Vilamoura, Portugal
Publisher	SciTePress
Pages	407 - 412
ISBN (Print)	978-989-8565-81-5
Publication status	Published - 1 Oct 2013

Austrian Classification of Fields of Science and Technology (ÖFOS)

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University Library Catalogue

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@inproceedings{2a43ad72184c4785bca0f4c3d4f2fbec,

title = "A Prototype for Automating Ontology Learning and Ontology Evolution",

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.(authors' abstract)",

author = "Gerhard Wohlgenannt and Stefan Belk and Matthias Schett",

year = "2013",

month = oct,

day = "1",

language = "English",

isbn = "978-989-8565-81-5",

pages = "407 -- 412",

editor = "{Joaquim Filipe and Jan Dietz}",

booktitle = "5th International Conference on Knowledge Engineering and Ontology Development (KEOD-2013)",

publisher = "SciTePress",

}

A Prototype for Automating Ontology Learning and Ontology Evolution. / Wohlgenannt, Gerhard; Belk, Stefan; Schett, Matthias.
5th International Conference on Knowledge Engineering and Ontology Development (KEOD-2013). ed. / Joaquim Filipe and Jan Dietz. Vilamoura, Portugal: SciTePress, 2013. p. 407 - 412.

Publication: Chapter in book/Conference proceeding › Contribution to conference proceedings

TY - GEN

T1 - A Prototype for Automating Ontology Learning and Ontology Evolution

AU - Wohlgenannt, Gerhard

AU - Belk, Stefan

AU - Schett, Matthias

PY - 2013/10/1

Y1 - 2013/10/1

N2 - 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.(authors' abstract)

AB - 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.(authors' abstract)

UR - http://www.keod.ic3k.org

M3 - Contribution to conference proceedings

SN - 978-989-8565-81-5

SP - 407

EP - 412

BT - 5th International Conference on Knowledge Engineering and Ontology Development (KEOD-2013)

A2 - Joaquim Filipe and Jan Dietz, null

PB - SciTePress

CY - Vilamoura, Portugal

ER -

A Prototype for Automating Ontology Learning and Ontology Evolution

Abstract

Austrian Classification of Fields of Science and Technology (ÖFOS)

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uComp (Embedded Human Computation for Knowledge Extraction and Evaluation)

Dynamic Integration and Visualization of Information from Multiple Evidence Sources

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A Prototype for Automating Ontology Learning and Ontology Evolution

Abstract

Austrian Classification of Fields of Science and Technology (ÖFOS)

Access to Document

Check availability

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Projects

uComp (Embedded Human Computation for Knowledge Extraction and Evaluation)

Dynamic Integration and Visualization of Information from Multiple Evidence Sources

Cite this