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Enhanced Rules Application Order to Stem Affixation, Reduplication and Compounding Words in Malay Texts

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Knowledge Management and Acquisition for Intelligent Systems (PKAW 2016)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9806))

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Abstract

Word stemmer is an automated program to remove affixes, clitics and particles from derived words based on morphological structures of specific natural languages. It has been widely used for text preprocessing in many artificial intelligence applications. Furthermore, the performance of word stemmer to correctly stem derived words has an influence to the performance of information retrieval, text mining and text categorization applications. Despite of various stemming approaches were proposed in the past research, the existing word stemmers for Malay language still suffer from stemming errors. Moreover, the existing word stemmers partially consider morphological structures of Malay language in which only focused on affixation words instead of affixation, reduplication and compounding words, simultaneously. Therefore, this paper proposes an enhanced word stemmer using rule-based affixes removal and dictionary lookup methods called enhanced rule application order that is able to stem affixation, reduplication and compounding words and at the same time, is able to address possible stemming errors. This paper also examines possible root causes of affixation, reduplication and compounding stemming errors that could happen during word stemming process. The experimental results indicate that the proposed word stemmer is able to stem affixation, reduplication and compounding words with better stemming accuracy by using enhanced rule application order.

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Acknowledgments

The authors would like to thank the Editor-in-Chief and the anonymous reviewers of the manuscript for their valuable comments and suggestions. This research was funded by Universiti Teknologi Malaysia’s Research University Grant PY/2014/02479.

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Authors and Affiliations

  1. Strategic Research, CyberSecurity Malaysia, The Mines Resort City, 43300, Seri Kembangan, Malaysia

    Mohamad Nizam Kassim & Amirudin Abdul Wahab

  2. Faculty of Computing, Universiti Teknologi Malaysia, 81310, Skudai, Johore, Malaysia

    Mohamad Nizam Kassim, Mohd Aizaini Maarof & Anazida Zainal

Authors
  1. Mohamad Nizam Kassim
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  2. Mohd Aizaini Maarof
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  3. Anazida Zainal
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  4. Amirudin Abdul Wahab
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Corresponding author

Correspondence to Mohamad Nizam Kassim .

Editor information

Editors and Affiliations

  1. Tokyo University of Science , Noda, Japan

    Hayato Ohwada

  2. University of Tsukuba, Tokyo, Japan

    Kenichi Yoshida

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Kassim, M.N., Maarof, M.A., Zainal, A., Abdul Wahab, A. (2016). Enhanced Rules Application Order to Stem Affixation, Reduplication and Compounding Words in Malay Texts. In: Ohwada, H., Yoshida, K. (eds) Knowledge Management and Acquisition for Intelligent Systems . PKAW 2016. Lecture Notes in Computer Science(), vol 9806. Springer, Cham. https://doi.org/10.1007/978-3-319-42706-5_6

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  • DOI: https://doi.org/10.1007/978-3-319-42706-5_6

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-42705-8

  • Online ISBN: 978-3-319-42706-5

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