Visit of the Climate Change Assessment Committee at Assiut University

Visit of the Committee for Assessment of Climate Change at Assiut University to the Faculty 

Under the auspices of Prof. Dr. Tayseer Hassan, Dean of the Faculty

Prof. Dr. Khaled Fathy, Vice Dean for Student Affairs, and Dr. Mustafa Abu Bakr received

Prof. Maha Ghanem - Vice President for Community Service and Environmental Affairs

To evaluate the projects of college students to face the climate and its solutions

Where the college students presented their projects in showing climate change and providing solutions and proposals to preserve the environment

 

 

 

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Congratulations for the victory of the Assiut University student team in the NASA International Competition

Assiut University Student Team Wins NASA International Competition

Prof. Dr. Tayseer Hassan, Dean of the College

Prof. Dr. Khaled Fathy, Vice Dean for Education and Student Affairs

Heartfelt congratulations to the winning students of the NASA World Competition

Where the NASA International Competition took place on the land of Assiut University during the month of October, in which Assiut University students (Faculty of Computers and Information) participated and won third place in the competition held on the land of Assiut University

They qualified to compete globally as Global Nominee and the team performed wonderfully in the Global Judging stage and were evaluated by an expert committee from NASA with 600 other projects from around the world and Assiut University students were able to win the title of (Global Finalist) and be ranked among the top 30 projects in the world.

Sincere congratulations, thanks and appreciation to the students participating in the competition, who are:

- Mohamed Nasser Hassan, team leader and president of the Student Union of the Faculty of Computers and Information.

- Islam Yahya Ahmed.

- Amani Jamal Naji.

- Amira Ahmed Ibrahim.

- Habibullah Adnan Ahmed.

And the students supervising the establishment of the competition at Assiut University:

- Ahmed Fahmy.

- Ahmed Ramadan.

May be an image of 5 people, headscarf and text

 

Arabic aspect based sentiment analysis using bidirectional GRU based models

Research Abstract

Aspect-based Sentiment analysis (ABSA) accomplishes a fine-grained analysis that defines the aspects of a given document or sentence and the sentiments conveyed regarding each aspect. This level of analysis is the most detailed version that is capable of exploring the nuanced viewpoints of the reviews. The bulk of study in ABSA focuses on English with very little work available in Arabic. Most previous work in Arabic has been based on regular methods of machine learning that mainly depends on a group of rare resources and tools for analyzing and processing Arabic content such as lexicons, but the lack of those resources presents another challenge. In order to address these challenges, Deep Learning (DL)-based methods are proposed using two models based on Gated Recurrent Units (GRU) neural networks for ABSA. The first is a DL model that takes advantage of word and character representations by combining bidirectional GRU, Convolutional Neural Network (CNN), and Conditional Random Field (CRF) making up the (BGRU-CNN-CRF) model to extract the main opinionated aspects (OTE). The second is an interactive attention network based on bidirectional GRU (IAN-BGRU) to identify sentiment polarity toward extracted aspects. We evaluated our models using the benchmarked Arabic hotel reviews dataset. The results indicate that the proposed methods are better than baseline research on both tasks having 39.7% enhancement in F1-score for opinion target extraction (T2) and 7.58% in accuracy for aspect-based sentiment polarity classification (T3). Achieving F1 score of 70.67% for T2, and accuracy of 83.98% for T3.

Research Authors
Mohammed M.Abdelgwad, Taysir Hassan A Soliman , Ahmed I.Taloba, Mohamed Fawzy Farghaly
Research Date
Research Department
Information Systems Department
Research File
article_1.pdf (1.08 MB)
Research Journal
Journal of King Saud University - Computer and Information Sciences
Research Member
Mohammed Mustafa Abdel-Gawad
Taiseer Hassan Abdel-Hamid Sulaiman
Ahmed Ibrahim Taloba Mohamed
Mohammed Fawzi Seddik Farghally
Research Pages
6652-6662
Research Publisher
Elsevier
Research Rank
Q1
Research Vol
34
Research Website
https://doi.org/10.1016/j.jksuci.2021.08.030
Research Year
2021
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