Sentiment Analysis: Hybrid Deep Learning Models for Sentiment Analysis: Leveraging Text and Emoji for Improved Sentiment Classification - Softcover
Inhaltsangabe
In today's digital world, emotions are conveyed not only through words but also through emojis that enrich and redefine human expression. Hybrid Deep Learning Models for Sentiment Analysis using Text and Emojis presents a groundbreaking approach to understanding sentiments by integrating textual and emoji-based data within advanced deep learning frameworks.This book introduces innovative hybrid architectures-ECSSO, EBERT, and HCGO-that combine the strengths of convolutional, recurrent, transformer, and graph-based neural networks. By fusing linguistic and visual-emotional cues, these models achieve remarkable accuracy in interpreting complex sentiments, sarcasm, and context-rich digital communication.Through comprehensive experiments and evaluations, the research demonstrates significant improvements over traditional text-only systems, highlighting the transformative role of emojis in emotion-aware artificial intelligence.Designed for researchers, scholars, and professionals in Natural Language Processing (NLP), Artificial Intelligence (AI), and Data Science, this book offers deep insights into multimodal sentiment analysis and the future of emotionally intelligent computing.
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Über die Autorin bzw. den Autor
Dr. Arjun Kuruva completed Ph.D in Computer Science and Engineering from YSR Engineering College of Yogi Vemana University, M.Tech degree in Computer Science & Engineering from St. John's College of Engineering & Technology, JNTUA, Anantapur. Since then, working as an Associate professor in the Department of Computer Science & Engineering.
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Paperback. Zustand: new. Paperback. In today's digital world, emotions are conveyed not only through words but also through emojis that enrich and redefine human expression. Hybrid Deep Learning Models for Sentiment Analysis using Text and Emojis presents a groundbreaking approach to understanding sentiments by integrating textual and emoji-based data within advanced deep learning frameworks.This book introduces innovative hybrid architectures-ECSSO, EBERT, and HCGO-that combine the strengths of convolutional, recurrent, transformer, and graph-based neural networks. By fusing linguistic and visual-emotional cues, these models achieve remarkable accuracy in interpreting complex sentiments, sarcasm, and context-rich digital communication.Through comprehensive experiments and evaluations, the research demonstrates significant improvements over traditional text-only systems, highlighting the transformative role of emojis in emotion-aware artificial intelligence.Designed for researchers, scholars, and professionals in Natural Language Processing (NLP), Artificial Intelligence (AI), and Data Science, this book offers deep insights into multimodal sentiment analysis and the future of emotionally intelligent computing. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Bestandsnummer des Verkäufers 9786209025587
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Paperback. Zustand: new. Paperback. In today's digital world, emotions are conveyed not only through words but also through emojis that enrich and redefine human expression. Hybrid Deep Learning Models for Sentiment Analysis using Text and Emojis presents a groundbreaking approach to understanding sentiments by integrating textual and emoji-based data within advanced deep learning frameworks.This book introduces innovative hybrid architectures-ECSSO, EBERT, and HCGO-that combine the strengths of convolutional, recurrent, transformer, and graph-based neural networks. By fusing linguistic and visual-emotional cues, these models achieve remarkable accuracy in interpreting complex sentiments, sarcasm, and context-rich digital communication.Through comprehensive experiments and evaluations, the research demonstrates significant improvements over traditional text-only systems, highlighting the transformative role of emojis in emotion-aware artificial intelligence.Designed for researchers, scholars, and professionals in Natural Language Processing (NLP), Artificial Intelligence (AI), and Data Science, this book offers deep insights into multimodal sentiment analysis and the future of emotionally intelligent computing. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Bestandsnummer des Verkäufers 9786209025587
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Paperback. Zustand: new. Paperback. In today's digital world, emotions are conveyed not only through words but also through emojis that enrich and redefine human expression. Hybrid Deep Learning Models for Sentiment Analysis using Text and Emojis presents a groundbreaking approach to understanding sentiments by integrating textual and emoji-based data within advanced deep learning frameworks.This book introduces innovative hybrid architectures-ECSSO, EBERT, and HCGO-that combine the strengths of convolutional, recurrent, transformer, and graph-based neural networks. By fusing linguistic and visual-emotional cues, these models achieve remarkable accuracy in interpreting complex sentiments, sarcasm, and context-rich digital communication.Through comprehensive experiments and evaluations, the research demonstrates significant improvements over traditional text-only systems, highlighting the transformative role of emojis in emotion-aware artificial intelligence.Designed for researchers, scholars, and professionals in Natural Language Processing (NLP), Artificial Intelligence (AI), and Data Science, this book offers deep insights into multimodal sentiment analysis and the future of emotionally intelligent computing. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability. Bestandsnummer des Verkäufers 9786209025587
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Sentiment Analysis | Hybrid Deep Learning Models for Sentiment Analysis: Leveraging Text and Emoji for Improved Sentiment Classification
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Taschenbuch. Zustand: Neu. Sentiment Analysis | Hybrid Deep Learning Models for Sentiment Analysis: Leveraging Text and Emoji for Improved Sentiment Classification | Arjun Kuruva (u. a.) | Taschenbuch | Englisch | 2025 | LAP LAMBERT Academic Publishing | EAN 9786209025587 | Verantwortliche Person für die EU: SIA OmniScriptum Publishing, Brivibas Gatve 197, 1039 RIGA, LETTLAND, customerservice[at]vdm-vsg[dot]de | Anbieter: preigu. Bestandsnummer des Verkäufers 134380629
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Sentiment Analysis
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Taschenbuch. Zustand: Neu. This item is printed on demand - Print on Demand Titel. Neuware -In today's digital world, emotions are conveyed not only through words but also through emojis that enrich and redefine human expression. Hybrid Deep Learning Models for Sentiment Analysis using Text and Emojis presents a groundbreaking approach to understanding sentiments by integrating textual and emoji-based data within advanced deep learning frameworks.This book introduces innovative hybrid architectures-ECSSO, EBERT, and HCGO-that combine the strengths of convolutional, recurrent, transformer, and graph-based neural networks. By fusing linguistic and visual-emotional cues, these models achieve remarkable accuracy in interpreting complex sentiments, sarcasm, and context-rich digital communication.Through comprehensive experiments and evaluations, the research demonstrates significant improvements over traditional text-only systems, highlighting the transformative role of emojis in emotion-aware artificial intelligence.Designed for researchers, scholars, and professionals in Natural Language Processing (NLP), Artificial Intelligence (AI), and Data Science, this book offers deep insights into multimodal sentiment analysis and the future of emotionally intelligent computing.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 164 pp. Englisch. Bestandsnummer des Verkäufers 9786209025587
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