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Textual embeddings with word-type-weighted word2vec and graph neural networks

LADIN, T., KOREL, L., HOLEŇA, Martin. Textual embeddings with word-type-weighted word2vec and graph neural networks. In: CIENCIALOVÁ, L., ČECHOVÁ, M., DENTI, L., HOLEŇA, M., MRÁZ, F., OSTERTÁG, R., PARDUBSKÁ, D., PLÁTEK, M., STANEK, M., eds. <em>Proceedings of the 25th Conference Information Technologies – Applications and Theory (ITAT 2025)</em>. Aachen: Technical University & CreateSpace Independent Publishing, 2025, S. 105-113. CEUR Workshop Proceedings, 4092. ISSN 1613-0073. Dostupné z: https://ceur-ws.org/Vol-4092/paper8.pdf

Autoři: T. Ladin , L. Korel , Martin Holeňa

Using machine learning on multiple true-false item texts to predict the difficulty of best singleanswer items: Identifying domain-specific text features beyond readability

ŠTĚPÁNEK, Lubomír, ŠTUKA, Č., VEJRAŽKA, M., MARTINKOVÁ, Patrícia. Using machine learning on multiple true-false item texts to predict the difficulty of best singleanswer items: Identifying domain-specific text features beyond readability. In: <em>XI Conference –European Congress of Methodology. Book of Abstracts</em>. San Cristobal de La Laguna: University of La Laguna, 2025, S. 281-281. Dostupné z: https://congress.eam2025.eu/event/2/book-of-abstracts.pdf

Autoři: Lubomír Štěpánek , Č. Štuka , M. Vejražka , Patrícia Martinková