{"id":19402,"date":"2025-09-19T19:21:01","date_gmt":"2025-09-19T16:21:01","guid":{"rendered":"https:\/\/su.edu.ye\/voga\/?p=19402"},"modified":"2025-09-19T19:24:25","modified_gmt":"2025-09-19T16:24:25","slug":"phd-degree-awarded-to-mr-sameer-mohammed-qaid-yaseen","status":"publish","type":"post","link":"https:\/\/su.edu.ye\/voga\/en\/19402\/","title":{"rendered":"PhD Degree Awarded to Mr. Sameer Mohammed Qaid Yaseen"},"content":{"rendered":"

M<\/strong>r<\/strong>. <\/strong>Sameer Mohammed Qaid Yaseen <\/strong>was awarded a PhD degree in Computing and Information Technology for his dissertation titled \u201cA Novel Model for Enhancing Arabic Text Retrieval from Documents<\/strong>,\u201d<\/em> which was submitted to Department of Computer Science, Faculty of Computer and Information Technology – Sana\u2019a University. The PhD dissertation defense was held on Saturday, <\/strong>September 13<\/strong>, 2025<\/strong>, corresponding to Rabi’ al-Awwal <\/strong>21<\/strong>, 1447 <\/strong>Hijri.<\/p>\n

The PhD Viva-Voce Committee, which was formed based on a resolution issued by the Post-Graduate Studies and Scientific Research Council, consisted of the following members:<\/p>\n

 <\/p>\n\n\n\n\n\n\n
#<\/strong><\/td>\nCommittee Members<\/strong><\/td>\nDesignation<\/strong><\/td>\nUniversity<\/strong><\/td>\nPosition<\/strong><\/td>\n<\/tr>\n
1<\/td>\nAssoc. Prof. Malik Nasser Ali Al-Jabri<\/strong><\/td>\nInternal examiner<\/td>\nSana\u2019a University<\/td>\nMember<\/td>\n<\/tr>\n
2<\/td>\nProf. Abdulmajid Ahmed Ghalib Al-Khulaidi<\/strong><\/td>\nMain supervisor<\/td>\nSana\u2019a University<\/td>\nMember<\/td>\n<\/tr>\n
3<\/td>\nProf. Muneer Abdullah Saeed Hazaa Al-Mekhlafi<\/strong><\/td>\nExternal Examiner<\/td>\nThamar University<\/td>\nChair<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n

 <\/p>\n

The dissertation aimed to<\/strong> improve the retrieval of Arabic text from documents.<\/p>\n

The dissertation <\/strong>concluded with several key findings, including:<\/p>\n

– Inventing a method to generate a large database of Arabic words and their roots based on morphology.<\/p>\n

– Using the generated data to train a BiLSTM RNN model for recognizing Arabic word roots.<\/p>\n

– Testing the proposed model’s ability to recognize the true root and improve data classification against seven previous methods.<\/p>\n

The candidate also presented several recommendations and future research gaps, such as the potential use of the word generation method for other problems, including question answering.<\/p>\n

The PhD dissertation<\/strong> was examined and recommended by the Viva-Voce Committee for acceptance<\/strong> and approval<\/strong>. The PhD defense<\/strong> was attended<\/strong> by a number of academics, researchers, interested students, the candidate\u2019s colleagues, and family members.<\/p>\n

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