Arabic Retrieval Revisited: Morphological Hole Filling

Due to Arabic’s morphological complexity, Arabic retrieval benefits greatly from morphological analysis – particularly stemming. However, the best known stemming does not handle linguistic phenomena such as broken plurals and malformed stems. In this paper we propose a model of character-level morphological transformation that is trained using Wikipedia hypertext to page title links. The use of our model yields statistically significant improvements in Arabic retrieval over the use of the best statistical stemming technique. The technique can potentially be applied to other languages.

• Type: Journal
• Year: 2012
• Where: ACL
• Authors: Kareem Darwish, Ahmed Ali
• Keywords: ACL 2012, Computational Linguistics, Linguistic Phenomena, Morphological Complexity, Significant Improvements