Automatic Genre Classification of Czech Texts Based on Syntactic Functions

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F26%3ANUZA74QN" target="_blank" >RIV/00216208:11320/26:NUZA74QN - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.1007/978-3-031-55917-4_13" target="_blank" >http://dx.doi.org/10.1007/978-3-031-55917-4_13</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-031-55917-4_13" target="_blank" >10.1007/978-3-031-55917-4_13</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Automatic Genre Classification of Czech Texts Based on Syntactic Functions

Popis výsledku v původním jazyce

Although there has been research conducted on text classification based on syntactic features for decades, the recent development of accurate automatic syntactic taggers has enabled scholars to apply the methods to much larger and more diverse datasets than before. This study aims to classify various text types in Czech language using relative frequencies of syntactic functions (as they are defined in the Prague Dependency Treebank (PDT)). A large balanced corpus of contemporary written Czech SYN2020 is used as the language material. The distances between texts are calculated by the Cosine Delta method and then hierarchical cluster analysis is performed. The results indicate that syntactic functions can contribute to automatic genre classification based on large empirical language data. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

Název v anglickém jazyce

Automatic Genre Classification of Czech Texts Based on Syntactic Functions

Popis výsledku anglicky

Although there has been research conducted on text classification based on syntactic features for decades, the recent development of accurate automatic syntactic taggers has enabled scholars to apply the methods to much larger and more diverse datasets than before. This study aims to classify various text types in Czech language using relative frequencies of syntactic functions (as they are defined in the Prague Dependency Treebank (PDT)). A large balanced corpus of contemporary written Czech SYN2020 is used as the language material. The distances between texts are calculated by the Cosine Delta method and then hierarchical cluster analysis is performed. The results indicate that syntactic functions can contribute to automatic genre classification based on large empirical language data. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

Druh

D - Stať ve sborníku

CEP obor

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OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

—

Návaznosti

—

Rok uplatnění

2024

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

Stud. Classif., Data Anal., Knowl. Organ.

ISBN

978-3-031-55916-7

ISSN

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e-ISSN

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Počet stran výsledku

10

Strana od-do

163-172

Název nakladatele

Springer Science and Business Media Deutschland GmbH

Místo vydání

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Místo konání akce

Naples, Italy

Datum konání akce

1. 1. 2026

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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