Concepts and Relations Acquisition within Ontology Learning Process for Automotive
The result's identifiers
Result code in 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>
Result on the web
<a href="http://daz2018.fit.vutbr.cz/" target="_blank" >http://daz2018.fit.vutbr.cz/</a>
DOI - Digital Object Identifier
—
Alternative languages
Result language
angličtina
Original language name
Concepts and Relations Acquisition within Ontology Learning Process for Automotive
Original language description
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.
Czech name
—
Czech description
—
Classification
Type
D - Article in proceedings
CEP classification
—
OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
—
Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2018
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Data a znalosti & WIKT
ISBN
978-80-214-5679-2
ISSN
—
e-ISSN
—
Number of pages
5
Pages from-to
115-119
Publisher name
Fakulta informačních technologií
Place of publication
Brno
Event location
Brno
Event date
Oct 11, 2018
Type of event by nationality
EUR - Evropská akce
UT code for WoS article
—