0565961 - ÚI 2023 RIV DE eng C - Conference Paper (international conference)
Korel, L. - Behr, A. S. - Kockmann, N. - Holeňa, MartinUsing Artificial Neural Networks to Determine Ontologies Most Relevant to Scientific Texts.
Proceedings of the 22st Conference Information Technologies – Applications and Theory (ITAT 2022). Aachen: Technical University & CreateSpace Independent Publishing, 2022 - (Ciencialová, L.; Holeňa, M.; Jajcay, R.; Jajcayová, R.; Mráz, F.; Pardubská, D.; Plátek, M.), s. 44-54. ISSN 1613-0073.
[ITAT 2022: Conference Information Technologies - Applications and Theory /22./. Zuberec (SK), 23.09.2022-27.09.2022]
Institutional support: RVO:67985807
Keywords : ontology * text data * text preprocessing * text representation learning * text classification
OECD category: Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
https://ceur-ws.org/Vol-3226/paper5.pdf
Permanent Link: https://hdl.handle.net/11104/0337426
