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This
book comprehensively covers the topic of recommender systems, which provide
personalized recommendations of products or services to users based on their
previous searches or purchases. Recommender system methods have been adapted to
diverse applications including query log mining, social networking, news
recommendations, and computational advertising. This book synthesizes both
fundamental and advanced topics of a research area that has now reached
maturity. The chapters of this book are organized into three categories:
- Algorithms and evaluation: These
chapters discuss the fundamental algorithms in recommender systems, including
collaborative filtering methods, content-based methods, knowledge-based
methods, ensemble-based methods, and evaluation.
- Recommendations in specific domains and contexts: the context of a recommendation
can be viewed as important side information that affects the recomme
