Ontology extension with NLP-based concept extraction for domain experts in catalytic sciences

Ontologies store semantic knowledge in a machine-readable way and represent domain knowledge in controlled vocabulary. In this work, a workflow is set up to derive classes from a text dataset using natural language processing (NLP) methods. Furthermore, ontologies and thesauri are browsed for those...

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Bibliographic Details
Published in:Knowledge and information systems 2023-12, Vol.65 (12), p.5503-5522
Main Authors: Behr, Alexander S., Völkenrath, Marc, Kockmann, Norbert
Format: Article
Language:English
Subjects:
Catalysis
Computer Science
Data Mining and Knowledge Discovery
Database Management
Datasets
Extraction
Information Storage and Retrieval
Information Systems and Communication Service
Information Systems Applications (incl.Internet)
IT in Business
Methanation
Natural language processing
Ontology
Regular Paper
Semantics
Subject specialists
Workflow
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Summary:Ontologies store semantic knowledge in a machine-readable way and represent domain knowledge in controlled vocabulary. In this work, a workflow is set up to derive classes from a text dataset using natural language processing (NLP) methods. Furthermore, ontologies and thesauri are browsed for those classes and corresponding existing textual definitions are extracted. A base ontology is selected to be extended with knowledge from catalysis science, while word similarity is used to introduce new classes to the ontology based on the class candidates. Relations are introduced to automatically reference them to already existing classes in the selected ontology. The workflow is conducted for a text dataset related to catalysis research on methanation of CO 2 and seven semantic artifacts assisting ontology extension by domain experts. Undefined concepts and unstructured relations can be more easily introduced automatically into existing ontologies. Domain experts can then revise the resulting extended ontology by choosing the best fitting definition of a class and specifying suggested relations between concepts of catalyst research. A structured extension of ontologies supported by NLP methods is made possible to facilitate a Findable, Accessible, Interoperable, Reusable (FAIR) data management workflow.
ISSN:0219-1377
0219-3116
DOI:10.1007/s10115-023-01919-1