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 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.
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Francesco Ricci is a professor of computer science at the Free University of Bozen-Bolzano, Italy. His current research interests include recommender systems, intelligent interfaces, mobile systems, machine learning, case-based reasoning, and the applications of ICT to health and tourism. He has published more than one hundred thirty of academic papers on these topics. He is the editor in chief of the Journal of Information Technology & Tourism and on the editorial board of User Modeling and User Adapted Interaction. Lior Rokach is a data scientist and an associate professor of information systems and software engineering at Ben-Gurion University of the Negev (BGU). Rokach established the machine learning laboratory in BGU which promotes innovative adaptations of machine learning and data mining methods to create the next generation of intelligent systems. Rokach is known for his contributions to the advancement of machine learning, recommender systems and cyber security. Bracha Shapira is an associate professor and the head of the information systems and engineering Department at Ben-Gurion University of the Negev (BGU). She leads large scale research projects at the Telekom Innovation Laboratories at BGU in the area of data analytics, recommender systems and personalization that delivers innovative technologies to address challenges in these fields. Shapira is known for her contribution in integrating social network, context awareness and privacy consideration to recommender systems.
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Librería: Brook Bookstore On Demand, Napoli, NA, Italia
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Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Includes major updates as well as 20 new chapters Presents detailed case studies Shares tips and insights from renowned experts in the fieldIncludes major updates as well as 20 new chaptersPresents detailed case studies. Nº de ref. del artículo: 447929080
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Taschenbuch. Condición: Neu. Recommender Systems Handbook | Francesco Ricci (u. a.) | Taschenbuch | xvii | Englisch | 2016 | Springer US | EAN 9781489977809 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu. Nº de ref. del artículo: 109582774
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Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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 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. 1024 pp. Englisch. Nº de ref. del artículo: 9781489977809
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Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -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 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.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 1024 pp. Englisch. Nº de ref. del artículo: 9781489977809
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Taschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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 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. Nº de ref. del artículo: 9781489977809
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Librería: Revaluation Books, Exeter, Reino Unido
Paperback. Condición: Brand New. 2nd reprint edition. 1003 pages. 9.25x6.10x2.05 inches. In Stock. Nº de ref. del artículo: x-1489977805
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