This second edition of a well-received text, with 20 new chapters, presents a coherent and unified repository of recommender systemsa 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.ElektrotehniAiki vestnik 78(5), 270a274 (2011) Lang, P.J., Bradley, M.M., Cuthbert, B.N.: International affective picture system (IAPS): Affective ratings of pictures and instruction manual. ... User Modeling and User-Adapted Interaction: The Journal of Personalization Research 16(3-4), 281a319 (2006). ... Personality and Individual Differences 36(3), 587a596 (2004). ... DOI 10.1109/PASSAT/ SocialCom.2011.26 Quijano-Sanchez, L., Recio-Garcia, J.a., Diaz-Agudo, B.: Personality andanbsp;...
|Title||:||Recommender Systems Handbook|
|Author||:||Francesco Ricci, Lior Rokach, Bracha Shapira|
|Publisher||:||Springer - 2015-11-17|