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
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;
Conference_Titel :
Computer Systems and Applications (AICCSA), 2011 9th IEEE/ACS International Conference on
Conference_Location :
Sharm El-Sheikh
Print_ISBN :
978-1-4577-0475-8
Electronic_ISBN :
2161-5322
DOI :
10.1109/AICCSA.2011.6126590