Recommender systems handbook
Francesco Ricci (Editor), Lior Rokach (Editor), Bracha Shapira (Editor)
This second edition of a well-received text, with 20 new chapters, presents a coherent and unified repository of recommender systemsℓ́ℓ 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: decision making and recommender systems, reciprocal recommender systems, recommender systems in social networks, mobile recommender systems, explanations for recommender systems, music recommender systems, cross-domain recommendations, privacy in recommender systems, and semantic-based recommender systems. This multi-disciplinary handbook involves world-wide experts from diverse fields such as artificial intelligence, human-computer interaction, information retrieval, data mining, mathematics, statistics, adaptive user interfaces, decision support systems, psychology, marketing, and consumer behavior. Theoreticians and practitioners from these fields will find this reference to be an invaluable source of ideas, methods and techniques for developing more efficient, cost-effective and accurate recommender systems
1 online resource (xvii, 1003 pages) : illustrations
9781489976376, 9781489976369, 148997637X, 1489976361
929952078
Printed edition:
Recommender Systems: Introduction and Challenges
A Comprehensive Survey of Neighborhood-based Recommendation Methods
Advances in Collaborative Filtering
Semantics-aware Content-based Recommender Systems
Constraint-based Recommender Systems
Context-Aware Recommender Systems
Data Mining Methods for Recommender Systems
Evaluating Recommender Systems
Evaluating Recommender Systems with User Experiments
Explaining Recommendations: Design and Evaluation
Recommender Systems in Industry: A Netflix Case Study
Panorama of Recommender Systems to Support Learning
Music Recommender Systems
The Anatomy of Mobile Location-Based Recommender Systems
Social Recommender Systems
People-to-People Reciprocal Recommenders
Collaboration, Reputation and Recommender Systems in Social Web Search
Human Decision Making and Recommender Systems
Privacy Aspects of Recommender Systems
Source Factors in Recommender System Credibility Evaluation
Personality and Recommender Systems
Group Recommender Systems: Aggregation, Satisfaction and Group Attributes
Aggregation Functions for Recommender Systems
Active Learning in Recommender Systems
Multi-Criteria Recommender Systems
Novelty and Diversity in Recommender Systems
Cross-domain Recommender Systems
Robust Collaborative Recommendation