Thèses en ligne de l'université 8 Mai 1945 Guelma

Sentiment Analysis for Arabic Language using Advanced Deep Learning Techniques

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dc.contributor.author LARAISSIA, LINA YASSAMINE
dc.date.accessioned 2024-12-02T12:56:38Z
dc.date.available 2024-12-02T12:56:38Z
dc.date.issued 2024
dc.identifier.uri http://dspace.univ-guelma.dz/jspui/handle/123456789/16478
dc.description.abstract This master’s thesis focuses on the Sentiment Analysis for Arabic languages using Advanced Deep Learning Techniques. The aim of this study is to develop an intelligent system that can automatically predict the sentiment from Arabic text based on Natural language processing . Traditional manual analysis methods are time-consuming, costly, and prone to human errors. By leveraging advancements in deep learning, Natural Language processing, an AI-based system can provide accurate and real-time information about the sentiment status of humans , enabling businesses to take preventive decision and optimize their products and services quality. The proposed system combines deep learning techniques with Natural language processing to assist businesses in maintaining their gains and reducing losses. This thesis presents the design, implementation, and evaluation of the system, demonstrating its effectiveness in Sentiment Analysis for Arabic Language. en_US
dc.language.iso en en_US
dc.publisher University of Guelma en_US
dc.subject Artificial Intelligence, Sentiment analysis, Arabic Language, Natural Language Processing, deep Learning, Product quality en_US
dc.title Sentiment Analysis for Arabic Language using Advanced Deep Learning Techniques en_US
dc.type Working Paper en_US


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