Full metadata record
| DC pole | Hodnota | Jazyk |
|---|---|---|
| dc.contributor.author | Šebek, Ondrej | |
| dc.contributor.author | Jirkovský, Václav | |
| dc.contributor.author | Rychtyckyj, Nestor | |
| dc.contributor.author | Kadera, Petr | |
| dc.contributor.editor | Steinberger, Josef | |
| dc.contributor.editor | Zíma, Martin | |
| dc.contributor.editor | Fiala, Dalibor | |
| dc.contributor.editor | Dostal, Martin | |
| dc.contributor.editor | Nykl, Michal | |
| dc.date.accessioned | 2017-10-09T08:32:37Z | |
| dc.date.available | 2017-10-09T08:32:37Z | |
| dc.date.issued | 2017 | |
| dc.identifier.citation | STEINBERGER, Josef ed.; ZÍMA, Martin ed.; FIALA, Dalibor ed.; DOSTAL, Martin ed.; NYKL, Michal ed. Data a znalosti 2017: sborník konference, Plzeň, Hotel Angelo 5. - 6. října 2017. 1. vyd. Plzeň: Západočeská univerzita v Plzni, 2017, s. 31-34. ISBN 978-80-261-0720-0. | cs |
| dc.identifier.isbn | 978-80-261-0720-0 | |
| dc.identifier.uri | https://www.zcu.cz/export/sites/zcu/pracoviste/vyd/online/DataAZnalosti2017.pdf | |
| dc.identifier.uri | http://hdl.handle.net/11025/26331 | |
| dc.format | 4 s. | cs |
| dc.format.mimetype | application/pdf | |
| dc.language.iso | cs | cs |
| dc.publisher | Západočeská univerzita v Plzni | cs |
| dc.rights | © Západočeská univerzita v Plzni | cs |
| dc.subject | ontologie | cs |
| dc.subject | heterogenita | cs |
| dc.subject | matching | cs |
| dc.title | Ontology learning for facilitating ontology matching in automotive | en |
| dc.type | konferenční příspěvek | cs |
| dc.type | conferenceObject | en |
| dc.rights.access | openAccess | en |
| dc.type.version | publishedVersion | en |
| dc.description.abstract-translated | All manufacturing companies need to monitor a large number of de-vices and from which critical data must be captured and analyzed. The increas-ing complexity of these ecosystems emphasizes the requirement for a flexible and versatile data model architecture. Ontologies may facilitate a proper under-standing of the problem domain as well as the interoperability with surrounding systems using ontology matching approach. However, data models of surround-ing systems are not always ontologies. Thus, concepts and relations among them have to be extracted from the models to enable their integration with the ontology. The definition of concepts, their hierarchy, relations between con-cepts, and properties from a general architecture is a complex task and has to be tailored to an application’s needs. In this paper, we propose an involvement of the ontology learning approach to the process of ontology matching in the au-tomotive. | en |
| dc.subject.translated | ontology | en |
| dc.subject.translated | heterogeneity | en |
| dc.subject.translated | matching | en |
| dc.type.status | Peer-reviewed | en |
| Vyskytuje se v kolekcích: | Data a znalosti 2017 Data a znalosti 2017 | |
Soubory připojené k záznamu:
| Soubor | Popis | Velikost | Formát | |
|---|---|---|---|---|
| Sebek.pdf | Plný text | 414,57 kB | Adobe PDF | Zobrazit/otevřít |
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