| 书目名称 | Recommender Systems | | 副标题 | The Textbook | | 编辑 | Charu C. Aggarwal | | 视频video | | | 概述 | Includes exercises and assignments, with instructor access to a solutions manual.Illustrations throughout aid in comprehension.Provides many examples to simplify exposition and facilitate in learning. | | 图书封面 |  | | 描述 | .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 data, social data, tagging data, and trustworthiness are explored...Advanced topics and applications: Various robustness aspects of recommender systems, such as shilling systems, attack models, and their defe | | 出版日期 | Textbook 2016 | | 关键词 | Collaborative filtering; Data mining; Recommender systems; Social network analysis; Social tagging; Graph | | 版次 | 1 | | doi | https://doi.org/10.1007/978-3-319-29659-3 | | isbn_softcover | 978-3-319-80619-8 | | isbn_ebook | 978-3-319-29659-3 | | copyright | Springer Nature Switzerland AG 2016 |
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发表于 2025-3-21 19:30:36
