This book discovers groundbreaking advancements in artificial intelligence with innovative solutions for real-world challenges. This book showcases state-of-the-art methodologies like deep learning and transfer learning to tackle sentiment analysis, fake news detection, and multi-dialectal named entity recognition, with a special focus on Arabic language technologies. Bridging the gap between research and practice, it highlights topics such as knowledge extraction, AI ethics, and the societal impacts of big data. Targeted at researchers, educators, and professionals, it serves as a vital guide for beginners and a comprehensive reference for experts seeking to stay ahead in the rapidly evolving field of AI.
This book discovers groundbreaking advancements in artificial intelligence with innovative solutions for real-world challenges. This book showcases state-of-the-art methodologies like deep learning and transfer learning to tackle sentiment analysis, fake news detection, and multi-dialectal named entity recognition, with a special focus on Arabic language technologies. Bridging the gap between research and practice, it highlights topics such as knowledge extraction, AI ethics, and the societal impacts of big data. Targeted at researchers, educators, and professionals, it serves as a vital guide for beginners and a comprehensive reference for experts seeking to stay ahead in the rapidly evolving field of AI.
Lamia Hadrich Belguith
Computational Intelligence Machine Learning Natural Language Processing (NLP) Feature Selection Arabic Language Processing Sentiment Analysis Deep Learning Models Fake News Detection Opinion Mining Cyberbullying Detection Named Entity Recognition Ontology-driven Methods Business Process Modeling Big Data Analysis Rule-based Systems