The paper presents a rapid method of developing a shallow Arabic morphological analyzer. The analyzer will only be concerned with generating the possible roots of any given Arabic word. The analyzer is based on automatically derived rules and statistics. For evaluation, the analyzer is compared to a commercially available Arabic Morphological Analyzer.

Segmentation of clitics has been shown to improve accuracy on a variety of Arabic NLP tasks. However, state-of-the-art Arabic word segmenters are either limited to formal Modern Standard Arabic, performing poorly on Arabic text featuring dialectal vocabulary and grammar, or rely on linguistic knowledge that is hand-tuned for each dialect. We extend an existing MSA segmenter with a simple domain...

OBJECTIVE To determine whether the glycemic index (GI) and insulinemic index (II) of dates could be altered by Arabic coffee consumption. METHODS This randomized cross-over study was conducted at the Department of Nutritional Sciences, Faculty of Health and Medical Sciences, University of Surrey, Guildford, United Kingdom from November 2009 to February 2010. Healthy subjects (5 males, 5 femal...

Compared to other languages, there is still a limited body of research which has been conducted for the automated Arabic Text Categorization (TC) due to the complex and rich nature of the Arabic language. Most of such research includes supervised Machine Learning (ML) approaches such as Naïve Bayes (NB), K-Nearest Neighbour (KNN), Support Vector Machine and Decision Tree. Most of these techniqu...

In this paper, we present a generic Optical Character Recognition system for Arabic script languages called Nabocr. Nabocr uses OCR approaches specific for Arabic script recognition. Performing recognition on Arabic script text is relatively more difficult than Latin text due to the nature of Arabic script, which is cursive and context sensitive. Moreover, Arabic script has different writing st...

We demonstrate the feasibility of using unsupervised morphological segmentation for dialects of Arabic, which are poor in linguistics resources. Our experiments using a Qatari Arabic to English machine translation system show that unsupervised segmentation helps to improve the translation quality as compared to using no segmentation or to using ATB segmentation, which was especially designed fo...

The Japanese language represents numbers in kana digit words (a syllabic notation), kanji numbers and Arabic numbers (logographic notations). Kanji and Arabic numbers have previously shown similar patterns of numerical processing, and because of their shared logographic properties may exhibit similar brain areas of numerical representation. Kana digit words require a larger phonetic component, ...