In this paper, a novel Arabic text categorization system has been developed based on statistical learning. The system uses a new method for feature extraction. The system has been implemented and tested using an Arabic text corpus. Results prove that the efficiency of the proposed system in text categorization of Arabic documents. Moreover, the system proved powerfulness in grasping the semanti...

In this paper, we focus on a sub-problem of Arabic text error correction, namely Arabic Text Denormalization. Text Denormalization is considered an important post-processing step when performing machine translation into Arabic. We examine different approaches for denormalization via the use of language modeling, stemming, and sequence labeling. We show the effectiveness of different approaches ...

The paper presents a research in Arabic Information Retrieval (IR). It surveys the impact of statistical and morphological analysis of Arabic text in improving Arabic IR relevancy. We investigated the contributions of Stemming, Indexing, Query Expansion, Text Summarization (TS), Text Translation, and Named Entity Recognition (NER) in enhancing the relevancy of Arabic IR. Our survey emphasizing ...

Although, the fair amount of works in sentiment analysis (SA) and opinion mining (OM) systems in the last decade and with respect to the performance of these systems, but it still not desired performance, especially for morphologically-Rich Language (MRL) such as Arabic, due to the complexities and challenges exist in the nature of the languages itself. One of these challenges is the detection ...

Machine perception and recognition of handwritten text in any language is a difficult problem. Even for Latin script most solutions are restricted to specific domains like bank checks courtesy amount recognition. Arabic script presents additional challenges for handwriting recognition systems due to its highly connected nature, numerous forms of each letter, and other factors. In this paper we ...

Sentiment analysis research has predominantly been on English texts. Thus there exist many sentiment resources for English, but less so for other languages. Approaches to improve sentiment analysis in a resource-poor focus language include: (a) translate the focus language text into a resource-rich language such as English, and apply a powerful English sentiment analysis system on the text, and...

Computer information and retrieval is becoming increasingly sophisticated and is being exploited in more and more spheres of human activity. Many computer applications are developed as information distribution systems, of which the Internet is one of the best known and widely used. With enormous quantities of data in different languages available on the net, it is essential that more efficient ...

This paper presents a new method for the recognition of Arabic text using global fmtures and Fuzzy ARTMAP neural network The method is divided into three major steps. The first step is digitization and pre-processing to create connected component. The secondstep is concerned with fmture extraction, where global f w r e s of the input word are used to extract features such as number of suhvorch,...

Corresponding Author: Hamed Saad AL-Rubaiee Department of Computer Science and Technology, University of Bedfordshire, Bedfordshire, UK Email: [email protected] Abstract: In this study, we present the design and implementation of Arabic text classification in regard to university students’ opinions through different algorithms such as Support Vector Machine (SVM) and Naive Bayes (NB). Th...

The using of the internet with its technologies and applications have been increased rapidly. So, protecting the text from illegal use is too needed . Text watermarking is used for this purpose. Arabic text has many characteristics such existing of diacritics , kashida (extension character) and points above or under its letters .Each of Arabic letters can take different shapes with different Un...