Concepts and Relations Acquisition within Ontology Learning Process for Automotive

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21730%2F18%3A00330526" target="_blank" >RIV/68407700:21730/18:00330526 - isvavai.cz</a>

Výsledek na webu

<a href="http://daz2018.fit.vutbr.cz/" target="_blank" >http://daz2018.fit.vutbr.cz/</a>

DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Concepts and Relations Acquisition within Ontology Learning Process for Automotive

Popis výsledku v původním jazyce

Flexible manufacturing as the key target of Industry 4.0 depends on precise knowledge of available human as well as machine resources and a capability to exibly manage them. Integration of the various resources is a very complex task and represents a signi_cant obstacle for a perfect understanding of the required knowledge. An ontology may facilitate the integration, but the problem occurs when the ontology does not comprise required concepts or relations. External data sources may be exploited for the ontology extensions. Such tasks may be hard to achieve purely by human given the volume of data involved in industrial applications. In this paper, we investigate an approach of acquiring the necessary information for ontology learning using a web mining method. The proposed approach was experimentally veri_ed on the integration of Excel document containing spare parts and Ford Supply Chain Ontology.

Název v anglickém jazyce

Concepts and Relations Acquisition within Ontology Learning Process for Automotive

Popis výsledku anglicky

Flexible manufacturing as the key target of Industry 4.0 depends on precise knowledge of available human as well as machine resources and a capability to exibly manage them. Integration of the various resources is a very complex task and represents a signi_cant obstacle for a perfect understanding of the required knowledge. An ontology may facilitate the integration, but the problem occurs when the ontology does not comprise required concepts or relations. External data sources may be exploited for the ontology extensions. Such tasks may be hard to achieve purely by human given the volume of data involved in industrial applications. In this paper, we investigate an approach of acquiring the necessary information for ontology learning using a web mining method. The proposed approach was experimentally veri_ed on the integration of Excel document containing spare parts and Ford Supply Chain Ontology.

Druh

D - Stať ve sborníku

CEP obor

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OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

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Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2018

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Data a znalosti & WIKT

ISBN

978-80-214-5679-2

ISSN

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e-ISSN

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Počet stran výsledku

5

Strana od-do

115-119

Název nakladatele

Fakulta informačních technologií

Místo vydání

Brno

Místo konání akce

Brno

Datum konání akce

11. 10. 2018

Typ akce podle státní příslušnosti

EUR - Evropská akce

Kód UT WoS článku

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