Optimized Identification of Sentence-Level Multiclass Events on Urdu-Language-Text Using Machine Learning Techniques
In today’s digital world, social media platforms generate a plethora of unstructured information. However, for low-resource languages like Urdu, there is a scarcity of well-structured data for specific tasks such as event classification. Urdu, a language prominent in South Asia, has boast...
Saved in:
| Main Authors: | Somia Ali, Uzma Jamil, Muhammad Younas, Bushra Zafar, Muhammad Kashif Hanif |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2025-01-01
|
| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10816408/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
A dataset of Roman Urdu text with spelling variations for sentence level sentiment analysisMendeley Data
by: Mudasar Ahmed Soomro, et al.
Published: (2024-12-01) -
Urdu Toxic Comment Classification With PURUTT Corpus Development
by: Hafiz Hassaan Saeed, et al.
Published: (2025-01-01) -
UEF-HOCUrdu: Unified Embeddings Ensemble Framework for Hate and Offensive Text Classification in Urdu
by: Kifayat Ullah, et al.
Published: (2025-01-01) -
UMEDNet: a multimodal approach for emotion detection in the Urdu language
by: Adil Majeed, et al.
Published: (2025-05-01) -
Roman urdu hate speech detection using hybrid machine learning models and hyperparameter optimization
by: Waqar Ashiq, et al.
Published: (2024-11-01)