This second edition of a well-received text, with 20 new chapters,
presents a coherent and unified repository of recommender systems'
major concepts, theories, methodologies, trends, and challenges. A
variety of real-world applications and detailed case studies are
included. In addition to wholesale revision of the existing
chapters, this edition includes new topics including: decision
making and recommender systems, reciprocal recommender systems,
recommender systems in social networks, mobile recommender systems,
explanations for recommender systems, music recommender systems,
cross-domain recommendations, privacy in recommender systems, and
semantic-based recommender systems. This multi-disciplinary
handbook involves world-wide experts from diverse fields such as
artificial intelligence, human-computer interaction, information
retrieval, data mining, mathematics, statistics, adaptive user
interfaces, decision support systems, psychology, marketing, and
consumer behavior. Theoreticians and practitioners from these
fields will find this reference to be an invaluable source of
ideas, methods and techniques for developing more efficient,
cost-effective and accurate recommender systems.
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