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In various NLP (Natural Language Processing) applications uses the POS tagging as a necessary component for a particular language. The precision of tagging on variety of certain language as a result is important analysis parameter. The author proposes a methodology to find the best machine algorithm in terms of performance for POS tagging of Hindi language. On this basis of result analysis, sequential minimum optimization and K nearest neighbors’ algorithm gives good accuracy 80.15% and 80.49%, respectively.

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A Comparative Performance Analysis of Machine-Learning Algorithms for Hindi Part-of-Speech Tagging

  • 会议论文

  • 发表日期：

    2025年

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  • Yashika Mathur,
  • Prashant Sharma,
  • Sunil Sharma

摘要

In various NLP (Natural Language Processing) applications uses the POS tagging as a necessary component for a particular language. The precision of tagging on variety of certain language as a result is important analysis parameter. The author proposes a methodology to find the best machine algorithm in terms of performance for POS tagging of Hindi language. On this basis of result analysis, sequential minimum optimization and K nearest neighbors’ algorithm gives good accuracy 80.15% and 80.49%, respectively.