Resources and components for gujarati NLP systems: a survey

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F22%3AW5WIZTGT" target="_blank" >RIV/00216208:11320/22:W5WIZTGT - isvavai.cz</a>

Result on the web

<a href="https://doi.org/10.1007/s10462-021-10120-1" target="_blank" >https://doi.org/10.1007/s10462-021-10120-1</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/s10462-021-10120-1" target="_blank" >10.1007/s10462-021-10120-1</a>

Result language

angličtina

Original language name

Resources and components for gujarati NLP systems: a survey

Original language description

Natural Language Processing (NLP) represents the task of automatic handling of natural human language by machines. There is a large spectrum of possible NLP applications which aid in automating tasks like text translation amongst languages, retrieving and summarizing data from very huge and complex repositories, spam email filtering, identifying fake news in digital media, finding political opinions, views and sentiments of people on various government policies, providing effective medical assistance based on past history records of patients etc. Gujarati language is an Indian language with more than sixty million users worldwide. At present, many efforts are laid for developing NLP applications and resources for Indian languages. This survey gives a taxonomy and comprehensive report regarding component and resource development for Gujarati NLP systems. Also, few prominent tools available in open domain are tested, and their posterior analysis is presented. Possible measures to handle the issues in resource and component development of Gujarati NLP system are also discussed. This report might be useful for industry, researchers and academicians to have a clear picture of the research gaps, challenges and opportunities in Gujarati NLP systems.

Czech name

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Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

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)

Project

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Continuities

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Publication year

2022

Confidentiality

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

Name of the periodical

Artificial Intelligence Review [online]

ISSN

1573-7462

e-ISSN

1573-7462

Volume of the periodical

55

Issue of the periodical within the volume

7

Country of publishing house

JP - JAPAN

Number of pages

19

Pages from-to

1-19

UT code for WoS article

000743000400001

EID of the result in the Scopus database

2-s2.0-85124138738