Tunisian Arabic is a dialect of the Arabic language spoken in Tunisia. Tunisian Arabic is an under-resourced language. It has neither a standard orthography nor large collections of written text and dictionaries. Actually, there is no strict separation between Modern Standard Arabic, the official language of the government, media and education, and Tunisian Arabic; the two exist on a continuum ...

In this paper we describe the implementation of an Arabic error correction system developed for the EMNLP2014 shared task on automatic error correction for Arabic text. We proposed a novel algorithm, where we find some correction rules and calculate their probability based on the training data, they we rank the correction rules, then we apply them on the text to maximize the overall Fscore for ...

In the current study we aim at exploiting discourse structure of Arabic text to automatically finding answers to non-factoid questions ("Why" and "How to"). Our method is based on Rhetorical Structure Theory (RST) that many studies have shown to be a very effective approach for many computational linguistics applications such as (text generation, text summarization and machine translation). For...

In this paper, several new universal preprocessing techniques are described to improve Prediction by Partial Matching (PPM) compression of UTF-8 encoded natural language text. These methods essentially adjust the alphabet in some manner (for example, by expanding or reducing it) prior to the compression algorithm then being applied to the amended text. Firstly, a simple bigraphs (two-byte) subs...

Applications of statistical Arabic NLP in general, and text mining in specific, along with the tools underneath perform much better as the statistical processing operates on deeper language factorization(s) than on raw text. Lexical semantic factorization is very important in that aspect due to its feasibility, high level of abstraction, and the language independence of its output. In the core ...

In this paper we conduct a comparative study between two stemming algorithms: khoja stemmer and our new stemmer for Arabic text classification (categorization), using Chisquare statistics as feature selection and focusing on decision tree classifier. Evaluation used a corpus that consists of 5070 documents independently classified into six categories: sport, entertainment, business, middle east...

Text Segmentation is one of the critical and vital step in OCR system of any language because accuracy of OCR depends upon correctly segmented characters. Segmentation divide the text images into its constituent parts (i.e. lines, components or words and individual characters). As Urdu and Arabic are highly cursive and context sensitive in nature and have improper space between words therefore,...

OBJECTIVE The objective of this study was to establish basic reading performance that could lead to useful design recommendations for print display text formats and layouts for the improvement of reading and comprehension performance of print text, such as academic writings, books, and newspapers, of Arabic language. BACKGROUND Readability of English print text has been shown to be influenced...

Many Text Classification (TC) algorithms have been proposed for Arabic TC. Polynomial Neural Networks (PNNs) were used recently in English TC, and have proved to be competitive to the state of the art text classifiers in this field. Lately, they were proposed for classifying Arabic documents. In this research paper, an experimental study that directly compares PNNs against five famous classific...

This contribution describes a font family designed to meet the requirements of typesetting mathematical documents in an Arabic presentation. Thus, not only is the text written in an Arabic alphabet-based script, but specific symbols are used and mathematical expressions also spread out from right to left. Actually, this font family consists of two components: an Arabic mathematical font and a d...