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Are you looking for place to read full E-Books without downloading? Here you can read Recommender Systems: The Textbook. You can also read and download new and old full E-Books. Enjoy and relax Reading full Recommender Systems: The Textbook Books online. . CLICK HERE TO DOWNLOAD THIS BOOK FOR FREE
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 recommendation goals. Different types of context such as temporal data, spatial da
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Are you looking for place to read full E-Books without downloading? Here you can read Recommender Systems: The Textbook. You can also read and download new and old full E-Books. Enjoy and relax Reading full Recommender Systems: The Textbook Books online. . CLICK HERE TO DOWNLOAD THIS BOOK FOR FREE
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 recommendation goals. Different types of context such as temporal data, spatial da
