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Using Artificial Neural Networks to Determine Ontologies Most Relevant to Scientific Texts
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$1 001 cav_un_epca*0565959 $1 011 $a 1613-0073 $1 200 1 $a Proceedings of the 22st Conference Information Technologies – Applications and Theory (ITAT 2022) $v S. 44-54 $1 210 $a Aachen $c Technical University & CreateSpace Independent Publishing $d 2022 $1 702 1 $a Ciencialová $b L. $4 340 $1 702 1 $a Holeňa $b M. $4 340 $1 702 1 $a Jajcay $b R. $4 340 $1 702 1 $a Jajcayová $b R. $4 340 $1 702 1 $a Mráz $b F. $4 340 $1 702 1 $a Pardubská $b D. $4 340 $1 702 1 $a Plátek $b M. $4 340 610 $a ontology 610 $a text data 610 $a text preprocessing 610 $a text representation learning 610 $a text classification 700 -1
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$3 cav_un_auth*0100761 $a Holeňa $b Martin $p UIVT-O $i Oddělení strojového učení $j Department of Machine Learning $w Department of Machine Learning $T Ústav informatiky AV ČR, v. v. i. 856 $u https://ceur-ws.org/Vol-3226/paper5.pdf $9 RIV
Number of the records: 1