A comparison of features for POS tagging in Kannada

Shriya Atmakuri, Bhavya Shahi, B. Ashwath Rao, S. N. Muralikrishna

Research output: Contribution to journalArticlepeer-review

7 Citations (Scopus)


This paper proposes a system of part of speech tagging for the South Indian language Kannada using supervised machine learning. POS tagging is an important step in Natural Language Processing and has varied applications such as word sense disambiguation, natural language understanding etc. Based on extensive research into methods used for POS tagging, Conditional Random fields have been chosen as our algorithm. CRFs are used for sequence modeling in POS tagging, named entity recognition and as an alternative to Hidden Markov Models. Three very large corpora are used and their results are compared. The feature sets for all three corpora are also varied. The best method for the task is determined using these results.

Original languageEnglish
Pages (from-to)2418-2421
Number of pages4
JournalInternational Journal of Engineering and Technology(UAE)
Issue number4
Publication statusPublished - 2018

All Science Journal Classification (ASJC) codes

  • Biotechnology
  • Computer Science (miscellaneous)
  • Environmental Engineering
  • General Chemical Engineering
  • General Engineering
  • Hardware and Architecture


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