@article {10.3844/jcssp.2006.245.248,
article_type = {journal},
title = {Hybrid Method for Tagging Arabic Text},
author = {Tlili-Guiassa, Yamina},
volume = {2},
number = {3},
year = {2006},
month = {Mar},
pages = {245-248},
doi = {10.3844/jcssp.2006.245.248},
url = {https://thescipub.com/abstract/jcssp.2006.245.248},
abstract = {Many natural language expressions are ambiguous and need to draw on other sources of information to be interpreted. Interpretation of the word ﺗﻌﺎون to be considered as a noun or a verb depends on the presence of contextual cues. This study proposes a hybrid method of based- rules and a machine learning method for tagging Arabic words. So this method is based firstly on rules (that considered the post-position, ending of a word and patterns) and then the anomaly is corrected by adopting a memory-based learning method (MBL). The memory based learning is an efficient method to integrate various sources of information and handling exceptional data in natural language processing tasks. Secondly checking the exceptional cases of rules and more information is made available to the learner for treating those exceptional cases. To evaluate the proposed method a number of experiments has been run and in order, to improve the importance of the various information in learning.},
journal = {Journal of Computer Science},
publisher = {Science Publications}
}