Text-to-Ontology Mapping via Natural Language Processing with Application to Search for Relevant Ontologies in Catalysis

Text-to-Ontology Mapping via Natural Language Processing with Application to Search for Relevant Ontologies in Catalysis

The paper presents a machine-learning based approach to text-to-ontology mapping. We explore a possibility of matching texts to the relevant ontologies using a combination of artificial neural networks and classifiers. Ontologies are formal specifications of the shared conceptualizations of applicat...

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Bibliographic Details
Main Authors: Lukáš Korel, Uladzislau Yorsh, Alexander S. Behr, Norbert Kockmann, Martin Holeňa
Format: Article
Language:English
Published: MDPI AG 2023-01-01
Series:Computers
Subjects:
text representation learning
text classification
text preprocessing
text data
ontology
Online Access:https://www.mdpi.com/2073-431X/12/1/14

Internet

https://www.mdpi.com/2073-431X/12/1/14

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