POS Tagging: A Review of Recent Techniques
Abstract
Part-of-Speech (POS) tagging is a fundamental task in Natural Language Pro-cessing (NLP) that involves assigning grammatical categories such as noun, verb, adjective, and adverb to words in a text. Accurate POS tagging serves as a critical preprocessing step for higher-level NLP applications, including syntactic parsing, machine translation, information retrieval, and sentiment analysis. Over the past decades, a wide range of POS tagging techniques has been proposed, by different research scholars from rule-based systems to da-ta-driven and neural approaches. This review provides a systematic examination of recent techniques, highlighting their core methodologies, strengths, limitations, and applicability to different languages.
Fields of Study & Subjects
Natural Language Processing Techniques
Topic Modeling
Speech and dialogue systems
Publication details
- Journal / source
- International Journal on Advanced Computer Theory and Engineering
- Volume
- 15
- Issue
- 1S
- Pages
- 238–246
- Publication date
- 18 January 2026
- Language
- EN