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Computational Intelligence Methods for Sentiment Analysis in Natural Language Processing Applications

Download or Read eBook Computational Intelligence Methods for Sentiment Analysis in Natural Language Processing Applications PDF written by D. Jude Hemanth and published by Elsevier. This book was released on 2024-01-19 with total page 296 pages. Available in PDF, EPUB and Kindle.
Computational Intelligence Methods for Sentiment Analysis in Natural Language Processing Applications
Author :
Publisher : Elsevier
Total Pages : 296
Release :
ISBN-10 : 9780443220104
ISBN-13 : 0443220107
Rating : 4/5 (04 Downloads)

Book Synopsis Computational Intelligence Methods for Sentiment Analysis in Natural Language Processing Applications by : D. Jude Hemanth

Book excerpt: Sentiment Analysis has become increasingly important in recent years for nearly all online applications. Sentiment Analysis depends heavily on Artificial Intelligence (AI) technology wherein computational intelligence approaches aid in deriving the opinions/emotions of human beings. With the vast increase in Big Data, computational intelligence approaches have become a necessity for Natural Language Processing and Sentiment Analysis in a wide range of decision-making application areas. The applications of Sentiment Analysis are enormous, ranging from business to biomedical and clinical applications. However, the combination of AI methods and Sentiment Analysis is one of the rarest commodities in the literature. The literatures either gives more importance to the application alone or to the AI/CI methodology.Computational Intelligence for Sentiment Analysis in Natural Language Processing Applications provides a solution to this problem through detailed technical coverage of AI-based Sentiment Analysis methods for various applications. The authors provide readers with an in-depth look at the challenges and solutions associated with the different types of Sentiment Analysis, including case studies and real-world scenarios from across the globe. Development of scientific and enterprise applications are covered, which will aid computer scientists in building practical/real-world AI-based Sentiment Analysis systems. - Includes basic concepts, technical explanations, and case studies for in-depth explanation of the Sentiment Analysis - Aids computer scientists in developing practical/real-world AI-based Sentiment Analysis systems - Provides readers with real-world development applications of AI-based Sentiment Analysis, including transfer learning for opinion mining from pandemic medical data, sarcasm detection using neural networks in human-computer interaction, and emotion detection using the random-forest algorithm


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