moonflower的专栏

一本很好的学习推荐系统的参考手册，全面而系统。由全球做推荐系统的研究人员参与编写。目录主干： 1 Introduction to Recommender Systems Handbook Part I Basic Techniques 2 Data Mining Methods for Recommender Systems 3 Content-based Recommender Systems: State of the Art and Trends 4 A Comprehensive Survey of Neighborhood-based Recommendation Methods 5 Advances in Collaborative Filtering 6 Developing Constraint-based Recommenders 7 Context-Aware Recommender Systems Part II Applications and Evaluation of RSs 8 Evaluating Recommendation Systems 9 A Recommender System for an IPTV Service Provider: a Real Large-Scale Production Environment. 10 How to Get the Recommender Out of the Lab? 11 Matching Recommendation Technologies and Domains 12 Recommender Systems in Technology Enhanced Learning Part III Interacting with Recommender Systems 13 On the Evolution of Critiquing Recommenders 14 Creating More Credible and Persuasive Recommender Systems:The Influence of Source Characteristics on Recommender System Evaluations 15 Designing and Evaluating Explanations for Recommender Systems 16 Usability Guidelines for Product Recommenders Based on Example Critiquing Research 17 Map Based Visualization of Product Catalogs Part IV Recommender Systems and Communities 18 Communities, Collaboration, and Recommender Systems in PersonalizedWeb Search 19 Social Tagging Recommender Systems 20 Trust and Recommendations 21 Group Recommender Systems: Combining Individual Models Part V Advanced Algorithms 22 Aggregation of Preferences in Recommender Systems 23 Active Learning in Recommender Systems 24 Multi-Criteria Recommender Systems 25 Robust Collaborative Recommendation