A triliteral word roots extraction using neural network for Arabic

Hasan Al-Serhan*, Aladdin Ayesh

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingPublished conference contribution

11 Citations (Scopus)

Abstract

Many of existing Arabic stemming algorithms use a large set of rules. In many cases, they refer to a lookup table of patterns and roots. This requires a large storage space, and time to access the information. A novel neural network based approach for stemming Arabic words is proposed in this paper. This approach attempts to exploit numerical relations between characters by using Backpropagation Neural Network (BPNN). No such system in literature can be found that uses neural network to extract the stemming of Arabic words.

Original languageEnglish
Title of host publication2006 International Conference on Computer Engineering and Systems, ICCES'06
Pages436-440
Number of pages5
DOIs
Publication statusPublished - 2006
Externally publishedYes
Event2006 International Conference on Computer Engineering and Systems, ICCES'06 - Cairo, Egypt
Duration: 5 Nov 20067 Nov 2006

Conference

Conference2006 International Conference on Computer Engineering and Systems, ICCES'06
Country/TerritoryEgypt
CityCairo
Period5/11/067/11/06

Keywords

  • Arabic language
  • Backpropagation
  • Natural language processing
  • Neural networks
  • Stemming

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