Classifying Arabic web pages toolkit

Authors:
Faten Al-Jaloud;Reem Bin Hezam;Mohamed Aoun-Allah
Affiliations:
Islamic University, Riyadh, Saudi Arabia;Rahman University, Riyadh, Saudi Arabia;Islamic University, Riyadh, Saudi Arabia
Venue:
Proceedings of the 2nd International Conference on Web Intelligence, Mining and Semantics
Year:
2012

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Abstract

Our research deals with classification of Arabic web pages. This field is challenging because limited research has been done in this field so far, and currently available tools do not support Arabic language. The fact remains that Arabic has various complex and discrete characteristics as compared to those of other languages: highly inflectional and derivational, the writing direction, the change of characters shapes based on their location, the absence of capitalization, etc. We have developed an environment that consist of two parts: The learning phase which facilitates the essential preprocessing tasks for Arabic web pages using several methods and tools. The second part classifies a web page by applying the best parameters setups.