期刊名称：Journal of Software Engineering and Applications
印刷版ISSN：1945-3116
电子版ISSN：1945-3124
出版年度：2011
卷号：4
期号：9
页码：522-526
DOI：10.4236/jsea.2011.49060
出版社：Scientific Research Publishing
摘要：Word stemming is one of the most important factors that affect the performance of many natural language processing applications such as part of speech tagging, syntactic parsing, machine translation system and information retrieval systems. Computational stemming is an urgent problem for Arabic Natural Language Processing, because Arabic is a highly inflected language. The existing stemmers have ignored the handling of multi-word expressions and identification of Arabic names. We used the enhanced stemming for extracting the stem of Arabic words that is based on light stemming and dictionary-based stemming approach. The enhanced stemmer includes the handling of multiword expressions and the named entity recognition. We have used Arabic corpus that consists of ten documents in order to evaluate the enhanced stemmer. We reported the accuracy values for the enhanced stemmer, light stemmer, and dictionary-based stemmer in each document. The results obtain shows that the average of accuracy in enhanced stemmer on the corpus is 96.29%. The experimental results showed that the enhanced stemmer is better than the light stemmer and dictionary-based stemmer that achieved highest accuracy values.
关键词：Dictionary-Based Stemmer; Arabic Morphological Analyzer; Named Entity Recognition
