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Impact of Stemmer on Arabic Text Retrieval

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Information Retrieval Technology (AIRS 2014)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 8870))

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Abstract

Stemming is a process of reducing inflected words to their stem, stem or root from a generally written word form. One of the high inflected words in the languages world is Arabic Language. Stemming improve the retrieval performance by reducing words variants, and in lcrease the similarity between related words. However, an Arabic Information Retrieval (AIR) can use stemming algorithms to retrieve a greater number of documents related to the users’ query. Therefore, the aim of this paper is to evaluate the impact of three different Arabic stemmers (i.e. ‘Information Science Research Institute” (ISRI), morphological and syntax based lemmatization “Educated Text Stemmer” (ETS), and Light10 stemmer) on the Arabic Information Retrieval performance for Arabic language, we used the Linguistic Data Consortium (LDC) Arabic Newswire data set as benchmark dataset. The evaluation of the three different stemmers ranked the best performance was achieved by light10 stemmer in term of mean average precision.

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Author information

Authors and Affiliations

  1. Faculity of Information Science and Technology, Universiti Kebangsaan Malaysia, Malaysia, Bangi

    Jaffar Atwan & Qusay Bsoul

  2. School of Information Science, Japan Advanced Institute of Science and Technology, Japan

    Masnizah Mohd

  3. Faculty of Computer Science and Informatics, Amman Arab University, Amman, Jordan

    Ghassan Kanaan

Authors
  1. Jaffar Atwan
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  2. Masnizah Mohd
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  3. Ghassan Kanaan
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  4. Qusay Bsoul
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Editor information

Editors and Affiliations

  1. Institute of Visual Informatic, Universiti Kebangsaan Malaysia, 43600, Bangi, Selangor, Malaysia

    Azizah Jaafar

  2. Institute of Visual Informatics, Universiti Kebangsaan Malaysia, 43600, Bangi, Selangor, Malaysia

    Nazlena Mohamad Ali

  3. Faculty of Information Science and Technology, Universiti Kebangsaan Malaysia, 43600, Bangi, Selangor, Malaysia

    Shahrul Azman Mohd Noah

  4. Insight Centre for Data Analytics, Dublin City University, Glasnevin, 9, Dublin, Ireland

    Alan F. Smeaton

  5. Information Systems, Queensland University of Technology, 4001, Brisbane, QLD, Australia

    Peter Bruza

  6. Faculty of Computer and Mathematical Sciences, Universiti Teknologi MARA, 40450, Shah Alam, Selangor, Malaysia

    Zainab Abu Bakar  & Nursuriati Jamil  & 

  7. Cyber Security Center, Universiti Pertahanan Nasional Malaysia, Kem Sungai Besi, 57000, Kuala Lumpur, Malaysia

    Tengku Mohd Tengku Sembok

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© 2014 Springer International Publishing Switzerland

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Atwan, J., Mohd, M., Kanaan, G., Bsoul, Q. (2014). Impact of Stemmer on Arabic Text Retrieval. In: Jaafar, A., et al. Information Retrieval Technology. AIRS 2014. Lecture Notes in Computer Science, vol 8870. Springer, Cham. https://doi.org/10.1007/978-3-319-12844-3_27

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  • DOI: https://doi.org/10.1007/978-3-319-12844-3_27

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-12843-6

  • Online ISBN: 978-3-319-12844-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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