A systematic survey of natural language processing for the Greek language

Kód výsledku v IS VaVaI

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

Výsledek na webu

<a href="http://dx.doi.org/10.1016/j.patter.2025.101313" target="_blank" >http://dx.doi.org/10.1016/j.patter.2025.101313</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.patter.2025.101313" target="_blank" >10.1016/j.patter.2025.101313</a>

Jazyk výsledku

angličtina

Název v původním jazyce

A systematic survey of natural language processing for the Greek language

Popis výsledku v původním jazyce

Comprehensive monolingual natural language processing (NLP) surveys are essential for assessing language-specific challenges, resource availability, and research gaps. However, existing surveys often lack standardized methodologies, leading to selection bias and fragmented coverage of NLP tasks and resources. This study introduces a generalizable framework for systematic monolingual NLP surveys. Our approach integrates a structured search protocol to minimize bias, an NLP task taxonomy for classification, and language resource taxonomies to identify potential benchmarks and highlight opportunities for improving resource availability. We apply this framework to Greek NLP (2012–2023), providing an in-depth analysis of its current state, task-specific progress, and resource gaps. The survey results are publicly available and are regularly updated to provide an evergreen resource. This systematic survey of Greek NLP serves as a case study, demonstrating the effectiveness of our framework and its potential for broader application to other not-so-well-resourced languages as regards NLP. © 2025 The Authors

Název v anglickém jazyce

A systematic survey of natural language processing for the Greek language

Popis výsledku anglicky

Comprehensive monolingual natural language processing (NLP) surveys are essential for assessing language-specific challenges, resource availability, and research gaps. However, existing surveys often lack standardized methodologies, leading to selection bias and fragmented coverage of NLP tasks and resources. This study introduces a generalizable framework for systematic monolingual NLP surveys. Our approach integrates a structured search protocol to minimize bias, an NLP task taxonomy for classification, and language resource taxonomies to identify potential benchmarks and highlight opportunities for improving resource availability. We apply this framework to Greek NLP (2012–2023), providing an in-depth analysis of its current state, task-specific progress, and resource gaps. The survey results are publicly available and are regularly updated to provide an evergreen resource. This systematic survey of Greek NLP serves as a case study, demonstrating the effectiveness of our framework and its potential for broader application to other not-so-well-resourced languages as regards NLP. © 2025 The Authors

Druh

J_SC - Článek v periodiku v databázi SCOPUS

CEP obor

—

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

2025

Kód důvěrnosti údajů

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

Název periodika

Patterns

ISSN

2666-3899

e-ISSN

—

Svazek periodika

2025

Číslo periodika v rámci svazku

2025

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

14

Strana od-do

101313

Kód UT WoS článku

—

EID výsledku v databázi Scopus

2-s2.0-105011258794