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.

About the Author

Ramon Zatarain Cabada. Professor and Researcher at the Instituto Tecnológico de Culiacán, Mexico. He is a regular member of the Mexican Academy of Computing (AMEXCOMP), the Mexican Society of Artificial Intelligence (SMIA), and the Mexican System of Researchers Level I (SNI). He has been a professor and Researcher at institutions such as Instituto Tecnológico de Toluca, the University of the State of México (UAEM), and the Instituto Tecnológico de Aguascalientes. He was a leader to create programs for Computer Science (Master and PhD). He has served as co-editor of a special issue of Educational Technology and Society and author of chapters in different Springer books such as Soft Computing for Recognition Based on Biometrics, Social Networking and Education, and Current Trends on Knowledge-Based Systems. As a researcher he has been a leader in more than 20 research projects and has more than 100 publications in different international journals and proceedings. His researchinterests are on Intelligent Learning Environments, Affective Computing, and Artificial Intelligence applied to Education.
Héctor Manuel Cárdenas López. Research assistant at the Instituto Tecnológico de Culiacán, Mexico. He is currently working towards a PhD degree in Engineering Sciences with the topic Multimodal Emotion and Personality Recognition. He is a member of the Thematic Network of Applied Computational Intelligence (RedICA). His main research interest includes Multimodal deep learning techniques, human behavior classification for emotion and personality recognition, affective tutoring systems, and cognitive oriented emotions.
Hugo Jair Escalante. Senior researcher scientist INAOE, Mexico and member of the board of directors of ChaLearn USA, Chair officer of the IAPR Technical Committee 12. He is a regular member of the Mexican Academy of Sciences (AMC), the Mexican Academy of Computing (AMEXCOMP) and Mexican System of Researchers Level II (SNI). He was editor of the Springer Series on Challenges in Machine Learning 2017-2023 and is Associate Editor of IEEE Transactions on Affective Computing. He has been involved in the organization of several challenges in machine learning and computer vision collocated with top venues. He has served as competition chair of NeurIPS2020, FG2020 and ICPR2020, NeurIPS2019, PAKDD2019-2018, IJCNN2019. His research interests are on machine learning, challenge organization, and its applications on language and vision.