Semi-automatic Tool for Ontology Learning Tasks
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21730%2F19%3A00337262" target="_blank" >RIV/68407700:21730/19:00337262 - isvavai.cz</a>
Result on the web
<a href="https://doi.org/10.1007/978-3-030-27878-6_10" target="_blank" >https://doi.org/10.1007/978-3-030-27878-6_10</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-030-27878-6_10" target="_blank" >10.1007/978-3-030-27878-6_10</a>
Alternative languages
Result language
angličtina
Original language name
Semi-automatic Tool for Ontology Learning Tasks
Original language description
The (semi-)automated integration of new information into a data model is a functionality which is required in cases when input documents are extensive and therefore a manual integration difficult or even impossible. We proposed an ontology learning procedure combining information acquisition from structured resources, such as WordNet or DBpedia, and unstructured resources using text mining techniques based on an evaluation of lexico-syntactic patterns. This approach offers a robust way, how to integrate even previously unknown information disregarding target application or domain. The proposed solution was implemented in the form of semi-automatic ontology learning tool used for integration of Excel document containing spare part records and Ford Supply Chain Ontology.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2019
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Industrial Applications of Holonic and Multi-Agent Systems
ISBN
978-3-030-27877-9
ISSN
0302-9743
e-ISSN
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Number of pages
11
Pages from-to
119-129
Publisher name
Springer
Place of publication
Wien
Event location
Linz
Event date
Aug 26, 2019
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
000611680100010