Unveiling the Effectiveness of NLP-based DL Methods for Urdu Text Analysis

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F49777513%3A23520%2F24%3A43972891" target="_blank" >RIV/49777513:23520/24:43972891 - isvavai.cz</a>

Result on the web

<a href="https://link.springer.com/chapter/10.1007/978-3-031-75329-9_12" target="_blank" >https://link.springer.com/chapter/10.1007/978-3-031-75329-9_12</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-031-75329-9_12" target="_blank" >10.1007/978-3-031-75329-9_12</a>

Result language

angličtina

Original language name

Unveiling the Effectiveness of NLP-based DL Methods for Urdu Text Analysis

Original language description

The analysis of text data has become a significant challenge while its size is gradually increasing in massive amounts. Various textual analysis methods exist, dealing with different processing styles due to multiple data types, mainly for English. Therefore, the other low-resource languages are difficult to process due to the unavailability of intelligent methods. Similarly, Urdu, as a low-resource language, requires effective methods based on machine learning or deep learning mechanisms. Our study has identified the rarely used pure Urdu text dataset, an effective combination of embeddings, and the best combination of hyperparameters for DL methods trained on that dataset. According to the evaluation results, our study has also determined the best methods regarding embeddings, hyperparameters, and overall performance. Moreover, combining pre-trained BERT embeddings with the fine-tuned BiLSTM and BERT was the best method to cope with Urdu as a low-resource language. As per the findings, our study recommends the pre-trained embedding models and hyperparameters settings for Urdu text classification analysis.

Czech name

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Czech description

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Type

D - Article in proceedings

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

<a href="/en/project/LM2018140" target="_blank" >LM2018140: e-Infrastructure CZ</a><br>

Continuities

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Publication year

2024

Confidentiality

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

Article name in the collection

Information Systems and Technological Advances for Sustainable Development. Lecture Notes in Information Systems and Organisation

ISBN

978-3-031-75328-2

ISSN

2195-4968

e-ISSN

2195-4976

Number of pages

12

Pages from-to

102-113

Publisher name

Springer Cham

Place of publication

Cham

Event location

Košice

Event date

May 27, 2024

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

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