Towards Perfection of Machine Learning of Competing Patterns:
The Use Case of Czechoslovak Patterns Development

D 2023

Towards Perfection of Machine Learning of Competing Patterns: The Use Case of Czechoslovak Patterns Development

SOJKA, Ondřej a Petr SOJKA

Základní údaje

Originální název

Towards Perfection of Machine Learning of Competing Patterns: The Use Case of Czechoslovak Patterns Development

Autoři

SOJKA, Ondřej (203 Česká republika, garant, domácí) a Petr SOJKA (203 Česká republika, domácí)

Vydání

Recent Advances in Slavonic. Brno, Recent Advances in Slavonic Natural Language Processing (RASLAN 2023), od s. 113-120, 8 s. 2023

Nakladatel

Tribun EU

Další údaje

Jazyk

angličtina

Typ výsledku

Stať ve sborníku

Obor

10201 Computer sciences, information science, bioinformatics

Stát vydavatele

Česká republika

Utajení

není předmětem státního či obchodního tajemství

Forma vydání

tištěná verze "print"

Odkazy

fulltext PDF

Kód RIV

RIV/00216224:14330/23:00132397

Organizační jednotka

Fakulta informatiky

ISBN

978-80-263-1793-7

ISSN

Klíčová slova anglicky

dictionary problem; effectiveness; hyphenation patterns; patgen; syllabification; Czech; Slovak; Czechoslovak patterns; machine learning

Příznaky

Mezinárodní význam

Změněno: 7. 4. 2024 23:37, RNDr. Pavel Šmerk, Ph.D.

Anotace

V originále

Finding space- and time-effective even perfect solution to the dictionary problem is an important practical and research problem, which solving may lead to a breakthrough in computation. Competing pattern technology from TeX is a special case, where for a given dictionary a word segmentation is stored in the competing patterns yet with very good generalization quality. Recently, the unreasonable effectiveness of pattern generation has been shown---it is possible to use hyphenation patterns to solve the dictionary problem jointly even for several languages without compromise.

In this article, we study the effectiveness of patgen for the supervised machine learning of the generation of the Czechoslovak hyphenation patterns. We show the machine learning techniques to develop competing patterns that are close to being perfect. We evaluate the new approach by improvements and space savings we gained during the development and finetuning of Czechoslovak hyphenation patterns.

Návaznosti

LM2023062, projekt VaV

Název: Digitální výzkumná infrastruktura pro jazykové technologie, umění a humanitní vědy

Investor: Ministerstvo školství, mládeže a tělovýchovy ČR, LINDAT/CLARIAH-CZ - Digitální výzkumná infrastruktura pro jazykové technologie, umění a humanitní vědy

Citovat

SOJKA, Ondřej a Petr SOJKA. Towards Perfection of Machine Learning of Competing Patterns: The Use Case of Czechoslovak Patterns Development. In Recent Advances in Slavonic Natural Language Processing (RASLAN 2023). Recent Advances in Slavonic. Brno: Tribun EU, 2023, s. 113-120. ISBN 978-80-263-1793-7.

@inproceedings{2345338,
   author = {Sojka, Ondřej and Sojka, Petr},
   address = {Brno},
   booktitle = {Recent Advances in Slavonic Natural Language Processing (RASLAN 2023)},
   edition = {Recent Advances in Slavonic},
   keywords = {dictionary problem; effectiveness; hyphenation patterns; patgen; syllabification; Czech; Slovak; Czechoslovak patterns; machine learning},
   howpublished = {tištěná verze "print"},
   language = {eng},
   location = {Brno},
   isbn = {978-80-263-1793-7},
   pages = {113-120},
   publisher = {Tribun EU},
   title = {Towards Perfection of Machine Learning of Competing Patterns: The Use Case of Czechoslovak Patterns Development},
   url = {https://www.fi.muni.cz/usr/sojka/papers/sojka-sojka-raslan-2023.pdf},
   year = {2023}
}

TY  - JOUR
ID  - 2345338
AU  - Sojka, Ondřej - Sojka, Petr
PY  - 2023
TI  - Towards Perfection of Machine Learning of Competing Patterns: The Use Case of Czechoslovak Patterns Development
PB  - Tribun EU
CY  - Brno
SN  - 9788026317937
KW  - dictionary problem
KW  - effectiveness
KW  - hyphenation patterns
KW  - patgen
KW  - syllabification
KW  - Czech
KW  - Slovak
KW  - Czechoslovak patterns
KW  - machine learning
UR  - https://www.fi.muni.cz/usr/sojka/papers/sojka-sojka-raslan-2023.pdf
N2  - Finding space- and time-effective even perfect solution to the dictionary problem is an important practical and research problem, which solving may lead to a breakthrough in computation. Competing pattern technology from TeX is a special case, where for a given dictionary a word segmentation is stored in the competing patterns yet with very good generalization quality. Recently, the unreasonable effectiveness of pattern generation has been shown---it is possible to use hyphenation patterns to solve the dictionary problem jointly even for several languages without compromise.

ER -

SOJKA, Ondřej a Petr SOJKA. Towards Perfection of Machine Learning of Competing Patterns: The Use Case of Czechoslovak Patterns Development. In \textit{Recent Advances in Slavonic Natural Language Processing (RASLAN 2023)}. Recent Advances in Slavonic. Brno: Tribun EU, 2023, s.~113-120. ISBN~978-80-263-1793-7.

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