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Arabic Stemmer Based Big Data

Author

Listed:
  • Youness Madani

    (Sultan Moulay Slimane University, Beni Mellal, Morocco)

  • Mohammed Erritali

    (Sultan Moulay Slimane University, Beni Mellal, Morocco)

  • Jamaa Bengourram

    (Sultan Moulay Slimane University, Beni Mellal, Morocco)

Abstract

By its morphological and syntactic richness, the Arabic language is considered among the most difficult languages to deal with it in the field of information search. This is due; in particular, to the various difficulties encountered in its Stemming, which has not yet experienced a standard approach. The Stemming algorithm for Arabic words has been an important topic in Arabic information retrieval. The intention of this article is to parallelize a stemming algorithm for Arabic by proposing a distributed stemming algorithm in a big data system. This is by using the Hadoop framework, the MapReduce programming model for the development of the algorithm, and the distributed file system HDFS for the Storage of stemming result.

Suggested Citation

  • Youness Madani & Mohammed Erritali & Jamaa Bengourram, 2018. "Arabic Stemmer Based Big Data," Journal of Electronic Commerce in Organizations (JECO), IGI Global, vol. 16(1), pages 17-28, January.
    • Handle: RePEc:igg:jeco00:v:16:y:2018:i:1:p:17-28
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    File URL: http://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/JECO.2018010102
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