Rouhia M.Sallam

Work place: Faculty of Applied Sciences, Taiz University, Yemen



Research Interests: Natural Language Processing


Rouhia M.Sallam is a master student at Menoufia University, Egypt. She works as a teaching assistant in Faculty of Sciences and Computer Sciences, Taiz University, Yemen. Her main research interest is in Natural Language Processing. She received BSc in Computer Science from Taiz University.

Author Articles
Arabic Text Categorization Using Mixed Words

By Mahmoud Hussein Hamdy M. Mousa Rouhia M.Sallam

DOI:, Pub. Date: 8 Nov. 2016

There is a tremendous number of Arabic text documents available online that is growing every day. Thus, categorizing these documents becomes very important. In this paper, an approach is proposed to enhance the accuracy of the Arabic text categorization. It is based on a new features representation technique that uses a mixture of a bag of words (BOW) and two adjacent words with different proportions. It also introduces a new features selection technique depends on Term Frequency (TF) and uses Frequency Ratio Accumulation Method (FRAM) as a classifier. Experiments are performed without both of normalization and stemming, with one of them, and with both of them. In addition, three data sets of different categories have been collected from online Arabic documents for evaluating the proposed approach. The highest accuracy obtained is 98.61% by the use of normalization.

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