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As seen in: Wiley Online Library, MDPI, ISG (Information Services Group), Pakistan Journal of Analytical and Environmental Chemistry

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Articles

[2501.17449] Cross-Language Approach for Quranic QA

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By Ali Hamdi, ammar mohammed, Mohamed Basem
| arXiv
arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.
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Enhancing Arabic Sentiment Analysis of Consumer Reviews: Machine Learning and Deep Learning Methods Based on NLP

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By Feng Zeng, ammar mohammed, Hani Almaqtari
| MDPI
1. Introduction Sentiment analysis is critical for understanding customer sentiments about products and services, providing companies with valuable insights that can enhance customer satisfaction, improve brand image, and boost profitability [1]. As more people express their opinions online, robust sentiment analysis tools become increasingly vital, particularly in the context of large volumes of user-generated content on platforms like Twitter, Facebook, and e-commerce websites.
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MRD‐GAN: Multi‐representation discrimination GAN for enhancing the diversity of the generated data

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By Mohammed Megahed, ammar mohammed
| Wiley Online Library Verified
CONFLICT OF INTEREST STATEMENT The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this article. REFERENCES 1, , , . A comprehensive survey and analysis of generative models in machine learning. Comput Sci Rev. 2020; 38:100285. https://www.sciencedirect.com/science/article/pii/S1574013720303853 2, . Deep generative models: survey.
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