Sentiment Analysis Unveiled

Techniques, Applications, and Innovations
Herausgeber: Nandal, Neha; Sapra, Varun; Tanwar, Rohit

• Gebundenes Buch

Produktbeschreibung

Sentiment Analysis Unveiled: Techniques, Applications, and Innovations is intended for professionals, researchers, and scientists in the field of Artificial Intelligence, and sentiments analysis. It will serve as a valuable resource for both beginners and experienced professionals in the field.

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Produktdetails

• Verlag: Taylor & Francis Ltd
• Seitenzahl: 184
• Erscheinungstermin: 2. April 2025
• Englisch
• Abmessung: 234mm x 156mm
• ISBN-13: 9781032824956
• ISBN-10: 1032824956
• Artikelnr.: 71706866

Autorenporträt

Neha Nandal has served as an Associate Professor in Computer Science and Engineering for over 8 years. Before that, she completed a PhD in Machine Learning. She is a lifetime member of IETA and of the IEEE Computer Society, Hyderabad Section. Her research interests are pattern recognition and machine learning. Rohit Tanwar received his bachelor's degree and PhD, in CSE, from Kurukshetra University. He received his master's degree from the YMCA University of Science and Technology. He has over 10 years of experience in teaching and is currently an Associate Professor in the School of Computer Science at UPES Dehradun. His areas of research include network security, optimization techniques, human computing, soft computing, cloud computing, and data mining. He also supervises PhD research scholars in the fields of network security, automatic target recognition, and healthcare. Varun Sapra is presently at the School of Computer Science at the University of Petroleum and Energy Studies. Dr. Sapra received his PhD in Computer Science & Engineering from Jagannath University. He has 17 years of combined experience in both industry and academia. Before joining academics, he was in the corporate sector and worked in companies like Cupid Software, WebOpac Applications, and CMA. His research areas include machine learning, decision support systems, case-based reasoning, and self-organizing maps.

Inhaltsangabe

0. Prelims. 1. Enhancing Sentiment Analysis through Supervised Machine
Learning Techniques. 2. A Multimodal Sentiment Analysis Framework for
Textual and Visual Cues. 3. Multimodal Sentiment Analysis Applications in
Healthcare: Enhancing Patient Care and Insights. 4. Sentiment
Analysis-Based Smart Support Assistant. 5. Leveraging LSTM Networks for
Predicting User Demand in the Fast-Moving Consumer Goods Market. 6.
Advancing Domain-Specific Adaptations of Large Language Models through
Transfer Learning and Fine-Tuning Techniques: An Analytical Study. 7.
Sentiment Analysis of Social-Media Content on COVID-19 Vaccine. 8. A Survey
on Detection of Deepfake Text using Machine Learning Models. 9. Exploring
emotions in textual data: Enhancing analysis through POS tagging and visual
representation. 10. A Comprehensive Review of Catastrophic Forgetting in
Text Processing: Challenges, Mitigation Strategies, and Future Directions.
11. The applications of the Metaverse stages in Language Teaching
strengthening learners' competencies to reflect promptly and sentiment
analysis implemented in the acquisition of foreign languages. 12. Knowledge
representation in Artificial Intelligence and structure of expert system
with inference rules. 13. Exploring Transfer Learning Paradigms in
Practical Contexts.