Introduction to Recommender Systems Handbook
Part I Basic Techniques
- Data Mining Methods for Recommender Systems- Content-based Recommender Systems: State of the Art and Trends- A Comprehensive Survey of Neighborhood-based Recommendation Methods- Advances in Collaborative Filtering- Developing Constraint-based Recommenders- Context-Aware Recommender SystemsPart II Applications and Evaluation of RSs
- Evaluating Recommendation Systems- A Recommender System for an IPTV Service Provider: a Real Large-Scale Production Environment- How to Get the Recommender Out of the Lab?- Matching Recommendation Technologies and Domains- Recommender Systems in Technology Enhanced LearningPart III Interacting with Recommender Systems
- On the Evolution of Critiquing Recommenders- Creating More Credible and Persuasive Recommender Systems: The Influence of Source Characteristics on Recommender System Evaluations- Designing and Evaluating Explanations for Recommender Systems- Usability Guidelines for Product Recommenders Based on Example Critiquing Research- Map Based Visualization of Product CatalogsPart IV Recommender Systems and Communities
- Communities, Collaboration, and Recommender Systems in Personalized Web Search- Social Tagging Recommender Systems- Trust and Recommendations- Group Recommender Systems: Combining Individual Models- Aggregation of Preferences in Recommender Systems- Active Learning in Recommender Systems- Multi-Criteria Recommender Systems- Robust Collaborative RecommendationIndex