Recommender Systems Handbook


Recommender Systems Handbook
Authors: Francesco Ricci
Year: 2022
Publisher: Springer
Language: English
ISBN 13: 9781071621967
ISBN 10: 1071621963
Categories: Computers, Computer Science
Pages: 320 / 319
Edition: 3

Availability: 5000 in stock

SKU: 9781071621967 Categories: ,

Recommender Systems Handbook Francesco Ricci, Lior Rokach, Bracha Shapira
This third edition handbook describes in detail the classical methods as well as extensions and novel approaches that were more recently introduced within this field. It consists of five parts: general recommendation techniques, special recommendation techniques, value and impact of recommender systems, human computer interaction, and applications. The first part presents the most popular and fundamental techniques currently used for building recommender systems, such as collaborative filtering, semantic-based methods, recommender systems based on implicit feedback, neural networks and context-aware methods. The second part of this handbook introduces more advanced recommendation techniques, such as session-based recommender systems, adversarial machine learning for recommender systems, group recommendation techniques, reciprocal recommenders systems, natural language techniques for recommender systems and cross-domain approaches to recommender systems. The third part covers a wide perspective to the evaluation of recommender systems with papers on methods for evaluating recommender systems, their value and impact, the multi-stakeholder perspective of recommender systems, the analysis of the fairness, novelty and diversity in recommender systems. The fourth part contains a few chapters on the human computer dimension of recommender systems, with research on the role of explanation, the user personality and how to effectively support individual and group decision with recommender systems. The last part focusses on application in several important areas, such as, food, music, fashion and multimedia recommendation. This informative third edition handbook provides a comprehensive, yet concise and convenient reference source to recommender systems for researchers and advanced-level students focused on computer science and data science. Professionals working in data analytics that are using recommendation and personalization techniques will also find this handbook a useful tool. Categories:
Computers – Computer Science
ISBN 10:
ISBN 13:
121 MB


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Recommender Systems Handbook

Availability: 5000 in stock