ICCK

Aftab Ahmad Khan

Department of Computer Science, University of Science and Technology Bannu, Bannu 28100, Pakistan

Section 01

Academic Profile

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Section 02

Editorial Roles

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Section 03

ICCK Publications

Open Access | Research Article | 30 June 2025 | Cited: Scopus 1
Comparison of Machine Learning and Deep Learning Models for Part-of-Speech Tagging
ICCK Transactions on Advanced Computing and Systems | Volume 1, Issue 2: 106-116, 2025 | DOI: 10.62762/TACS.2025.493945
Abstract
Part-of-speech (POS) tagging—the automatic assignment of grammatical categories to every token in a text corpus—is a foundational preprocessing step for AI-driven language applications such as machine translation, sentiment analysis, and information retrieval. For morphologically complex, low-resource languages such as Pashto, the scarcity of annotated data and standardised tools makes this task particularly challenging. This paper presents a systematic comparative evaluation of six machine learning (ML) and deep learning (DL) algorithms—Support Vector Machine (SVM), Decision Tree (DT), Random Forest (RF), K-Nearest Neighbor (KNN), Multi-Layer Perceptron (MLP), and Naïve Bayes (NB)—... More >

Graphical Abstract
Comparison of Machine Learning and Deep Learning Models for Part-of-Speech Tagging