Unsupervised Stemmer for Arabic Tweets

Research output: Contribution to conferencePaper

  • Authors:
  • Allan Ramsay
  • Fahad Albogamy

Abstract

Stemming is an essential processing step in a wide range of high level text processing applications such as information extraction, machine translation and sentiment analysis. It is used to reduce words to their stems. Many stemming algorithms have been developed for Modern Standard Arabic (MSA). Although Arabic tweets and MSA are closely related and share many characteristics, there are substantial differences between them in lexicon and syntax. In this paper, we introduce a light Arabic stemmer for Arabic tweets. Our results show improvements over the performance of a number of well-known stemmers for Arabic.

Bibliographical metadata

Original languageEnglish
Pages78-84
Number of pages7
Publication statusPublished - Dec 2016