Recommender Systems Handbook

by 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 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 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.

Genres: Artificial Intelligence, Reference, Programming, Business, Technical

1020 pages, Paperback

First published October 23, 2010

Reviews

[Leonie · Rating 4 out of 5]

Even 15 years after publication, this handbook still provides valuable insight into the world of recommender systems for both newly enthusiastic readers as well as researchers trying to refresh their memory.
Especially during the start of my thesis, this was a valuable book to have on hand, providing thorough insights as well as broad overviews of a topic as complex as recommender systems.