This paper presents a comparative study of two machine learning techniques for recognizing handwritten Arabic words, where hidden Markov models (HMMs) and dynamic Bayesian networks (DBNs) were evaluated. The work proposed is divided into three stages, namely preprocessing, feature extraction and classification. Preprocessing includes baseline estimation and normalization as well as segmentation...

In this paper, we present a model based on the Neural Network (NN) for classifying Arabic texts. We propose the use of Singular Value Decomposition (SVD) as a preproces-sor of NN to reduce the data in terms of both size as well as dimensionality so that the input data become more classifiable and faster for the convergence of the training process used in the NN model. To test the effectiveness ...

Recognition of handwritten Arabic text awaits accurate recognition solutions. There are many difficulties facing a good handwritten Arabic recognition system such as unlimited variation in human handwriting, similarities of distinct character shapes, and their position in the word. The typical Optical Character Recognition (OCR) systems are based mainly on three stages, preprocessing, features ...

Arabic has some special syntax features which lead to complex syntax structures. We have developed a formal description of Arabic syntax in Definite Clause Grammar. This grarnrnar is characterized by its h igh descriptive power due to its dual formulat ion in terms of functions and in terms of grammatical categories. The developed g rammar has a high coverage of Arabic language and has context ...

Corresponding Author: Jehad Q. Odeh Alnihoud Department of Compute Science, Al al-Bayt University, Mafraq, Jordan Email: [email protected] Abstract: In this research, we propose a new approach to increase the capacity and enhance the reliability of hiding voice data in Arabic text. Using Kashida to hide bits in Arabic text is one of the most promising approaches in steganography. Unfortunately,...

Students and staff perspectives on language barriers in medical education in Egypt and their attitude towards Arabization of the medical curriculum were explored in a questionnaire survey of 400 medical students and 150 staff members. Many students (56.3%) did not consider learning medicine in English an obstacle, and 44.5% of staff considered it an obstacle only in the 1st year of medical scho...

In Information Retrieval System (IRS), the Automatic Relevance Feedback (ARF) is a query reformulation technique that modifies the initial one without the user intervention. It is applied mainly through the addition of terms coming from the external resources such as the ontologies and or the results of the current research. In this context we are mainly interested in the local analysis techniq...

Most Arabic Named Entity Recognition (NER) systems have been developed using either of two approaches: a rule-based or Machine Learning (ML) based approach, with their strengths and weaknesses. In this paper, the problem of Arabic NER is tackled through integrating the two approaches together in a pipelined process to create a hybrid system with the aim of enhancing the overall performance of N...

Existing steganography methods are still lacking in terms of capacity. Hence, a new steganography method for Arabic text is proposed. The method hides secret information bits within Arabic letters using two features, which are the moon and sun letters and the redundant Arabic extension character “-” known as Kashida. The Arabic alphabet contains 28 letters, which are classified into 14 sun lett...

Name identification has been worked on quite intensively for the past few years, and has been incorporated into several products. Many researchers have attacked this problem in a variety of languages but only a few limited researches have focused on Named Entity Recognition (NER) for Arabic text due to the lack of resources for Arabic named entities and the limited amount of progress made in Ar...