I am a PhD student at the computer science department in the University of Jordan. I received my B.S. and M.S. degrees in Computer Science from The University of Jordan. I am interested in machine learning, deep learning, data mining, natural language processing and software engineering.
My current research involves deep learning approaches and Arabic text processing. Specifically, I am working on developing an automatic approach for restoring diacritic marks for Arabic text in addition to other functionalities. The main goal of this research is to overcome some limitations that the other algorithms suffer, which include incorrectly diacritizing end of word and detecting the right diacritic mark.
Arabic is one of the six official languages of the United Nations , that belongs to Semitic languages used by Arabs and Muslims all over the world. With more than 200 million native speakers and 1 billion Muslims over the globe . The Arabic language alphabet consists of 28 letters in addition to the Hamza. The orientation of writing in Arabic is from right to left, there is no capitalization in Arabic as well as Arabic letters change shape according to their position in the word.
Faris, H., Abukhurma, R., Almanaseer, W., Saadeh, M., Mora, A. M., Castillo, P. A., & Aljarah, I. (2020). Improving financial bankruptcy prediction in a highly imbalanced class distribution using oversampling and ensemble learning: a case from the Spanish market. Progress in Artificial Intelligence, 9(1), 31-53
Allawi, H. M., Al Manaseer, W., & Al Shraideh, M. (2018). A greedy particle swarm optimization (GPSO) algorithm for testing real-world smart card applications. International Journal on Software Tools for Technology Transfer, 1-12.
Manaseer, S., Manasir, W., Alshraideh, M., Hashish, N. A., & Adwan, O. (2015). Automatic test data generation for java card applications using genetic algorithm. Journal of Software Engineering and Applications, 8(12), 603.