DocumentCode
3758097
Title
Stemming impact on Arabic text categorization performance: A survey
Author
Fawaz S. Al-Anzi;Dia AbuZeina
Author_Institution
Department of Computer Engineering, Kuwait University
fYear
2015
Firstpage
1
Lastpage
7
Abstract
The significant growth of online textual information has increased the demand for effective content-based Arabic text categorization methods. The categorization of Arabic texts has some challenges that need to be addressed specially when using stemming. In the literature, we found a debate among researchers about the benefits of using stemming in Arabic text categorization. Hence, we performed a study of this feature reduction method to clarify the impact of this widely used method in text mining and document classification. We also presented some Arabic text cases to deny the importance of stemming in Arabic text categorization.
Keywords
"Text categorization","Support vector machines","Niobium","Natural language processing","Information retrieval","Classification algorithms","Supervised learning"
Publisher
ieee
Conference_Titel
Information & Communication Technology and Accessibility (ICTA), 2015 5th International Conference on
Type
conf
DOI
10.1109/ICTA.2015.7426875
Filename
7426875
Link To Document