This third edition handbook describes in detail the classical methods as well as extensions and novel approaches that were more recently introduced within this field. 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 the m...(展开全部)

This third edition handbook describes in detail the classical methods as well as extensions and novel approaches that were more recently introduced within this field. 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 the m...(展开全部)

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: ...(展开全部)

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: ...(展开全部)

Practical Recommender Systems explains how recommender systems work and shows how to create and apply them for your site. After covering the basics, you'll see how to collect user data and produce personalized recommendations. You'll learn how to use the most popular recommendation algorithms and see examples of them in action on sites like Amazon and Netflix. Finally, the book...(展开全部)

Practical Recommender Systems explains how recommender systems work and shows how to create and apply them for your site. After covering the basics, you'll see how to collect user data and produce personalized recommendations. You'll learn how to use the most popular recommendation algorithms and see examples of them in action on sites like Amazon and Netflix. Finally, the book...(展开全部)

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...(展开全部)

Linear Systems and Signals, Third Edition, has been refined and streamlined to deliver unparalleled coverage and clarity. It emphasizes a physical appreciation of concepts through heuristic reasoning and the use of metaphors, analogies, and creative explanations. The text uses mathematics not only to prove axiomatic theory but also to enhance physical and intuitive understandin...(展开全部)

This book introduces higher-level study skills and allows students to develop a deeper understanding of the learning process itself, encouraging a reflective and well-informed approach to study.It is written by Stella Cottrell, the leader in the field with over 1/4 million book sales to date. "Bestselling - the Handbook" has topped the academic bestseller lists for three years ...(展开全部)

迪帕克·K. 阿加瓦尔（Deepak K. Agarwal） LinkedIn公司副总裁，领导人工智能/机器学习团队的研发工作。之前曾任Yahoo!研究院研究主管和首席研究员，以及AT&T公司研究员。20多年来，他致力于为Web应用开发、部署机器学习和统计方法，以及解决推荐系统和计算广告领域的大数据问题。 陈必衷（Bee-Chung Chen）　LinkedIn公司首席主任工程师、应用研究员，曾任Yahoo!研究院研究员。作为核心开发者，他为LinkedIn和Yahoo!设计了前沿的推荐算法，