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Table of Contents
Part I: Fundamentals
Chapter 1. Affective Computing
Chapter 2. Machine learning and pattern recognition in affective computing
Chapter 3. Affective Learning Environments
Part II: Sentiment Analysis for Learning Environments
Chapter 4. Building resources for sentiment detection
Chapter 5. Methods for data representation
Chapter 6. Designing and testing the classification models
Chapter 7. Model integration to a learning system
Part III: Multimodal Recognition of Learning-Oriented Emotions
Chapter 8. Building Resources for Emotion Detection
Chapter 9. Methods for Data Representation
Chapter 10. Multimodal recognition systems
Chapter 11. Multimodal emotion recognition in learning environments
Part IV: Automatic Personality Recognition
Chapter 12. Building resources for personality recognition
Chapter 13. Methods for data representation
Chapter 14. Personality recognition models
Chapter 15. Multimodal personality recognition for affective computing.
Chapter 1. Affective Computing
Chapter 2. Machine learning and pattern recognition in affective computing
Chapter 3. Affective Learning Environments
Part II: Sentiment Analysis for Learning Environments
Chapter 4. Building resources for sentiment detection
Chapter 5. Methods for data representation
Chapter 6. Designing and testing the classification models
Chapter 7. Model integration to a learning system
Part III: Multimodal Recognition of Learning-Oriented Emotions
Chapter 8. Building Resources for Emotion Detection
Chapter 9. Methods for Data Representation
Chapter 10. Multimodal recognition systems
Chapter 11. Multimodal emotion recognition in learning environments
Part IV: Automatic Personality Recognition
Chapter 12. Building resources for personality recognition
Chapter 13. Methods for data representation
Chapter 14. Personality recognition models
Chapter 15. Multimodal personality recognition for affective computing.