Arabic part of speech disambiguation: A survey

Research output: Contribution to journalArticle

11 Citations (Scopus)

Abstract

After several decades of heavy research activities in part of speech tagging of rich-resources languages, various supervised and unsupervised machine learning approaches have been proposed to solve this problem. In contrast, a few researches have been investigated in Arabic part of speech tagging with modest effort. Thus, the aim of this paper is to summarize and organize the information available in the literature to motivate researchers to look into these techniques, adopt them for other languages and to develop more advanced ones. The paper also surveys Arabic part of speech tagging and discuss their limitation. In addition, open areas and future work directions are discussed.

Original languageEnglish
Pages (from-to)517-532
Number of pages16
JournalInternational Review on Computers and Software
Volume4
Issue number5
Publication statusPublished - Sep 2009

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Learning systems

Keywords

  • Part of speech tagging
  • Supervised and unsupervised machine learning

ASJC Scopus subject areas

  • Computer Science(all)

Cite this

Arabic part of speech disambiguation : A survey. / Albared, Mohammed; Omar, Nazlia; Ab Aziz, Mohd Juzaiddin.

In: International Review on Computers and Software, Vol. 4, No. 5, 09.2009, p. 517-532.

Research output: Contribution to journalArticle

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