Automatic Identification of Speakers and Parties in Steno Protocols of the Czech Parliament
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F22%3A00127477" target="_blank" >RIV/00216224:14330/22:00127477 - isvavai.cz</a>
Result on the web
<a href="https://nlp.fi.muni.cz/raslan/2022/paper10.pdf" target="_blank" >https://nlp.fi.muni.cz/raslan/2022/paper10.pdf</a>
DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Automatic Identification of Speakers and Parties in Steno Protocols of the Czech Parliament
Original language description
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.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2022
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Proceedings of the Sixteenth Workshop on Recent Advances in Slavonic Natural Languages Processing, RASLAN 2022.
ISBN
9788026317524
ISSN
2336-4289
e-ISSN
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Number of pages
9
Pages from-to
15-23
Publisher name
Tribun EU
Place of publication
Brno
Event location
Brno
Event date
Jan 1, 2022
Type of event by nationality
CST - Celostátní akce
UT code for WoS article
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