DocumentCode
2960205
Title
Arabic text categorization based on rough set classification
Author
Yahia, Moawia Elfaki
Author_Institution
Coll. of Comput. Sci. & Inf. Technol., King Faisal Univ., Alhasa, Saudi Arabia
fYear
2011
fDate
27-30 Dec. 2011
Firstpage
293
Lastpage
294
Abstract
The process of text categorization has been used in many applications and areas. Classifying of Arabic texts is different than classifying of English texts because Arabic is highly inflectional and derivational language which makes monophonical analysis a very complex task. This short paper has made a review of some researches in Arabic text categorization, and recent works for adopting rough sets theory in the field of text mining and text categorization, with investigation of use of its classification in Arabic text categorization.
Keywords
natural language processing; pattern classification; rough set theory; text analysis; Arabic text categorization; English texts; derivational language; inflectional language; monophonical analysis; rough set classification; text mining; Classification algorithms; Cognition; Computer science; Feature extraction; Rough sets; Support vector machines; Text categorization;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Systems and Applications (AICCSA), 2011 9th IEEE/ACS International Conference on
Conference_Location
Sharm El-Sheikh
ISSN
2161-5322
Print_ISBN
978-1-4577-0475-8
Electronic_ISBN
2161-5322
Type
conf
DOI
10.1109/AICCSA.2011.6126590
Filename
6126590
Link To Document