Using Artificial Neural Networks to Determine Ontologies Most Relevant to Scientific Texts

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SYSNO	0565961
Title	Using Artificial Neural Networks to Determine Ontologies Most Relevant to Scientific Texts
Author(s)	Korel, L. (CZ) Behr, A. S. (DE) Kockmann, N. (DE) Holeňa, Martin (UIVT-O)_{SAI, RID}
Source Title	Proceedings of the 22st Conference Information Technologies – Applications and Theory (ITAT 2022). S. 44-54. - Aachen : Technical University & CreateSpace Independent Publishing, 2022 / Ciencialová L. ; Holeňa M. ; Jajcay R. ; Jajcayová R. ; Mráz F. ; Pardubská D. ; Plátek M.
Conference	ITAT 2022: Conference Information Technologies - Applications and Theory /22./, 23.09.2022 - 27.09.2022, Zuberec
Document Type	Konferenční příspěvek (zahraniční konf.)
Institutional support	UIVT-O - RVO:67985807
Language	eng
Country	DE
Keywords	ontology * text data * text preprocessing * text representation learning * text classification
Cooperating institutions	Fakulta informačních technologií ČVUT (Czech Republic) Technische Universität Dortmund (Germany) Leibniz Institute for Catalysis, Rostock (Germany)
URL	https://ceur-ws.org/Vol-3226/paper5.pdf
Permanent Link	https://hdl.handle.net/11104/0337426

Number of the records: 1