| MIKUŠEK, Ota. Automatic Identification of Speakers and Parties in Steno Protocols of the Czech Parliament. In Aleš Horák, Pavel Rychlý, Adam Rambousek. Proceedings of the Sixteenth Workshop on Recent Advances in Slavonic Natural Languages Processing, RASLAN 2022. Brno: Tribun EU, 2022, s. 15-23. ISBN 978-80-263-1752-4. |
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@inproceedings{2240126,
author = {Mikušek, Ota},
address = {Brno},
booktitle = {Proceedings of the Sixteenth Workshop on Recent Advances in Slavonic Natural Languages Processing, RASLAN 2022.},
editor = {Aleš Horák, Pavel Rychlý, Adam Rambousek},
keywords = {scikit-learn; embedding; SVM; random forest; naive Bayes; ngram; CountVectorizer; classification},
howpublished = {tištěná verze "print"},
language = {eng},
location = {Brno},
isbn = {978-80-263-1752-4},
pages = {15-23},
publisher = {Tribun EU},
title = {Automatic Identification of Speakers and Parties in Steno Protocols of the Czech Parliament},
url = {https://raslan2022.nlp-consulting.net/},
year = {2022}
}
TY - JOUR
ID - 2240126
AU - Mikušek, Ota
PY - 2022
TI - Automatic Identification of Speakers and Parties in Steno Protocols of the Czech Parliament
PB - Tribun EU
CY - Brno
SN - 9788026317524
KW - scikit-learn
KW - embedding
KW - SVM
KW - random forest
KW - naive Bayes
KW - ngram
KW - CountVectorizer
KW - classification
UR - https://raslan2022.nlp-consulting.net/
N2 - There are many methods of machine learning. This paper shows an application of basic machine learning methods like bag of words, random forest and naive Bayes on classification task of assigning sentences to members and parties of the Czech Parliament.
ER -
MIKUŠEK, Ota. Automatic Identification of Speakers and Parties in Steno Protocols of the Czech Parliament. In Aleš Horák, Pavel Rychlý, Adam Rambousek. \textit{Proceedings of the Sixteenth Workshop on Recent Advances in Slavonic Natural Languages Processing, RASLAN 2022.}. Brno: Tribun EU, 2022, s.~15-23. ISBN~978-80-263-1752-4.
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