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Genetic and Evolutionary Computing pp 175–185Cite as

Machine Learning Techniques for Myanmar Word-Sense Disambiguation

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 387))

Abstract

Word Sense Disambiguation (WSD) is the vital of Natural Language processing such as machine translation, grammatical analysis, content analysis and information retrieval. WSD process is useful for automatically identifying the correct meaning of an ambiguous word in the sentence or the query when it has multiple meanings. In this paper, the supervised, semi-supervised, unsupervised and knowledge-based approaches for WSD are discussed. This work aim to explore the machine learning techniques for word sense disambiguation of Myanmar Nouns.

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References

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Author information

Authors and Affiliations

  1. University of Computer Studies, Mandalay, Myanmar

    Phyu Phyu Khaing & Than Nwe Aung

Authors
  1. Phyu Phyu Khaing
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  2. Than Nwe Aung
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Corresponding author

Correspondence to Phyu Phyu Khaing .

Editor information

Editors and Affiliations

  1. Faculty of Engineering, University of Miyazaki, Miyazaki, Japan

    Thi Thi Zin

  2. School of Computer Science and Tech..., Harbin Institute of Technology Shenzhen Graduate School, Shenzhen, China

    Jerry Chun-Wei Lin

  3. College of Information Science and Engg, Fujian University of Technology, Fuzhou, China

    Jeng-Shyang Pan

  4. Faculty of Engineering, University of Miyazaki, Miyazaki, Japan

    Pyke Tin

  5. Faculty of Engineering, University of Miyazaki, Miyazaki, Japan

    Mitsuhiro Yokota

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© 2016 Springer International Publishing Switzerland

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Cite this paper

Khaing, P.P., Aung, T.N. (2016). Machine Learning Techniques for Myanmar Word-Sense Disambiguation. In: Zin, T., Lin, JW., Pan, JS., Tin, P., Yokota, M. (eds) Genetic and Evolutionary Computing. Advances in Intelligent Systems and Computing, vol 387. Springer, Cham. https://doi.org/10.1007/978-3-319-23204-1_18

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  • DOI: https://doi.org/10.1007/978-3-319-23204-1_18

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-23203-4

  • Online ISBN: 978-3-319-23204-1

  • eBook Packages: EngineeringEngineering (R0)

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