SOJKA, Ondřej and 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, p. 113-120. ISBN 978-80-263-1793-7.
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Basic information
Original name Towards Perfection of Machine Learning of Competing Patterns: The Use Case of Czechoslovak Patterns Development
Authors SOJKA, Ondřej (203 Czech Republic, guarantor, belonging to the institution) and Petr SOJKA (203 Czech Republic, belonging to the institution).
Edition Recent Advances in Slavonic. Brno, Recent Advances in Slavonic Natural Language Processing (RASLAN 2023), p. 113-120, 8 pp. 2023.
Publisher Tribun EU
Other information
Original language English
Type of outcome Proceedings paper
Field of Study 10201 Computer sciences, information science, bioinformatics
Country of publisher Czech Republic
Confidentiality degree is not subject to a state or trade secret
Publication form printed version "print"
WWW fulltext PDF
RIV identification code RIV/00216224:14330/23:00132397
Organization unit Faculty of Informatics
ISBN 978-80-263-1793-7
ISSN 2336-4289
Keywords in English dictionary problem; effectiveness; hyphenation patterns; patgen; syllabification; Czech; Slovak; Czechoslovak patterns; machine learning
Tags International impact
Changed by Changed by: RNDr. Pavel Šmerk, Ph.D., učo 3880. Changed: 7/4/2024 23:37.
Abstract
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.
Links
LM2023062, research and development projectName: Digitální výzkumná infrastruktura pro jazykové technologie, umění a humanitní vědy
Investor: Ministry of Education, Youth and Sports of the CR
PrintDisplayed: 25/8/2024 16:00