Recommender Systems Handbook

This third edition handbook provides a comprehensive and convenient reference source to recommender systems for researchers and advanced-level students, covering classical methods, extensions, and novel approaches. It consists of five parts: general recommendation techniques, special recommendation techniques, value and impact of recommender systems, human computer interaction, and applications. The first part presents popular and fundamental techniques, while the second part introduces advanced techniques. The third part covers evaluation, fairness, diversity, and human computer interaction. The fourth part focuses on applications in various areas.

Format: Paperback / softback
Length: 1060 pages
Publication date: 23 April 2023
Publisher: Springer-Verlag New York Inc.

This comprehensive third edition handbook delves into the realm of recommender systems, encompassing both classical methods and innovative approaches that have emerged more recently. It is organized into five distinct parts:

General Recommendation Techniques: This section introduces the most widely employed techniques for building recommender systems, including collaborative filtering, semantic-based methods, recommender systems based on implicit feedback, neural networks, and context-aware methods. It provides a foundational understanding of the fundamental techniques used in this field.

Special Recommendation Techniques: The second part of the handbook explores advanced recommendation techniques, such as session-based recommender systems, adversarial machine learning for recommender systems, group recommendation techniques, reciprocal recommenders systems, natural language techniques for recommender systems, and cross-domain approaches to recommender systems. These techniques offer more sophisticated approaches to personalized recommendations.

Value and Impact of Recommender Systems: The third part of the handbook takes a broader perspective, examining the evaluation of recommender systems. It includes papers on methods for evaluating recommender systems, their value and impact, the multi-stakeholder perspective of recommender systems, the analysis of fairness, novelty, and diversity in recommender systems. This section provides insights into the practical applications and implications of recommender systems.

Human Computer Interaction: The fourth part focuses on the human computer dimension of recommender systems. It explores research on the role of explanation, user personality, and how to effectively support individual and group decision-making with recommender systems. This section emphasizes the importance of designing user-friendly interfaces and enhancing the user experience.

Applications: The last part of the handbook showcases real-world applications of recommender systems in various domains, including food, music, fashion, and multimedia recommendation. It provides practical examples and case studies demonstrating the effectiveness of recommender systems in different industries.

This third edition handbook serves as a valuable resource for researchers and advanced-level practitioners seeking to delve deeper into the world of recommender systems. It offers a comprehensive yet concise and convenient reference source that covers a wide range of topics, from foundational techniques to advanced algorithms, and from evaluation methodologies to practical applications. By providing a comprehensive overview of the field, this handbook equips readers with the knowledge and tools necessary to develop and implement effective recommender systems in a variety of domains.

Weight: 1588g
Dimension: 235 x 155 (mm)
ISBN-13: 9781071621998
Edition number: 3rd ed. 2022