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Al-Serhan, H. and Ayesh, A. (2006) A Triliteral Word Roots Extraction Using Neural Network for Arabic. International Conference on Computer Engineering and Systems, Cairo, 5-7 November 2006, 436-440.
https://doi.org/10.1109/ICCES.2006.320487

has been cited by the following article:

• TITLE: Developing Two Different Novel Techniques for Arabic Text Stemming

  AUTHORS: Mohammad Mustafa, Afag Salah Aldeen, Mohammed E. Zidan, Rihab E. Ahmed, Yasir Eltigani

  KEYWORDS: Arabic Language, Arabic Information Retrieval, Light Stemming, Light 10, Extended Light-Stemmer, Linguistic-Based Stemmer

  JOURNAL NAME: Intelligent Information Management, Vol.11 No.1, January 3, 2019

  ABSTRACT: Stemming is used to produce stem or root of words. The process is vital to different research fields such as text mining, sentiment analysis, and text categorization, etc. Several techniques have been proposed to stemming Arabic text and among them, Khoja and light-10 stemmers are the most widely used. In this paper, we propose and evaluate two different stemming techniques to Arabic that are based on light stemming techniques. The new stemmers are compared to best reported light stemmer, which is light-10. Results and experiments, which were conducted using standard collections, reveal that The proposed stemmers yield 5.13% and 13.1% improvement in retrieval performance over light 10 with 0.369 average precision and 0.397, respectively and the improvement is statistically significant.