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@inproceedings{1643878,
author = {Medveď, Marek and Horák, Aleš and Sabol, Radoslav},
address = {Portugal},
booktitle = {Proceedings of the 12th International Conference on Agents and Artificial Intelligence},
doi = {http://dx.doi.org/10.5220/0008979206440651},
editor = {Ana Rocha, Luc Steels, Jaap van den Herik},
keywords = {Question Answering; Question Classification; Answer Classification; Czech; Simple Question Answering Database; SQAD},
howpublished = {elektronická verze "online"},
language = {eng},
location = {Portugal},
isbn = {978-989-758-395-7},
pages = {644-651},
publisher = {SCITEPRESS},
title = {Improving RNN-based Answer Selection for Morphologically Rich Languages},
year = {2020}
}
TY - JOUR
ID - 1643878
AU - Medveď, Marek - Horák, Aleš - Sabol, Radoslav
PY - 2020
TI - Improving RNN-based Answer Selection for Morphologically Rich Languages
PB - SCITEPRESS
CY - Portugal
SN - 9789897583957
KW - Question Answering
KW - Question Classification
KW - Answer Classification
KW - Czech
KW - Simple Question Answering Database
KW - SQAD
N2 - Question answering systems have improved greatly during the last five years by employing architectures of deep neural networks such as attentive recurrent networks or transformer-based networks with pretrained con- textual information. In this paper, we present the results and detailed analysis of experiments with the largest question answering benchmark dataset for the Czech language. The best results evaluated in the text reach the accuracy of 72 %, which is a 4 % improvement to the previous best result. We also introduce the newest version of the Czech Question Answering benchmark dataset SQAD 3.0, which was substantially extended to more than 13,000 question-answer pairs, and we report the first answer selection results on this dataset which indicate that the size of the training data is important for the task.
ER -
MEDVEĎ, Marek, Aleš HORÁK and Radoslav SABOL. Improving RNN-based Answer Selection for Morphologically Rich Languages. Online. In Ana Rocha, Luc Steels, Jaap van den Herik. \textit{Proceedings of the 12th International Conference on Agents and Artificial Intelligence}. Portugal: SCITEPRESS, 2020, p.~644-651. ISBN~978-989-758-395-7. Available from: https://dx.doi.org/10.5220/0008979206440651.
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