Recommender Systems The Textbook /

• Main Author: Aggarwal, Charu C. (Author)
• Corporate Author: SpringerLink (Online service)
• Format: Electronic eBook
• Language: English
• Published: Cham : Springer International Publishing : Imprint: Springer, 2016.
• Subjects: Computer science.; Data mining.; Artificial intelligence.; Computer Science.; Data Mining and Knowledge Discovery.; Artificial Intelligence (incl. Robotics).

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 networ...

Table of Contents:

• An Introduction to Recommender Systems
• Neighborhood-Based Collaborative Filtering
• Model-Based Collaborative Filtering
• Content-Based Recommender Systems
• Knowledge-Based Recommender Systems
• Ensemble-Based and Hybrid Recommender Systems
• Evaluating Recommender Systems
• Context-Sensitive Recommender Systems
• Time- and Location-Sensitive Recommender Systems
• Structural Recommendations in Networks
• Social and Trust-Centric Recommender Systems
• Attack-Resistant Recommender Systems
• Advanced Topics in Recommender Systems.