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AARI: Automatic Arabic Readability Index IAJIT First Online Publication
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Abstract:
Abstract: Text readability refers to the ability of the reader to understand and comprehend a given text. In this research, we present our approach to develop an automatic readability index for the Arabic language: Automatic Arabic Readability Index (AARI), using factor analysis. Our results are based on more than 1196 Arabic texts extracted from the Jordanian curriculum in the subjects of: Arabic language, Islamic religion, natural sciences, and national and social education for the elementary classes (first grade through tenth grade). We conduct a comparison study to support our model using cluster analysis and Support Vector Machines (SVM). In order to facilitate the usage of our Arabic readability index, we developed two applications to compute the Arabic text readability: a standalone application and an add-on for Microsoft Word text processer. Through our presented research results and developed tools, we aim to improve the overall readability of Arabic texts, especially those targeted towards the younger generations.
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Keyword:
Arabic language; cluster analysis; factor analysis; Readability index; SVM; text mining
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URL: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.296.9723
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AARI: Automatic Arabic Readability Index
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In: http://www.ccis2k.org/iajit/PDF/vol.11,no.4/5200.pdf (2012)
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