Articles liés à Recommender Systems Handbook
Synopsis
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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À propos de l?auteur
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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Etat : 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. N° de réf. du vendeur 447929080
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Recommender Systems Handbook
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Recommender Systems Handbook
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Taschenbuch. Etat : 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. N° de réf. du vendeur 9781489977809
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Recommender Systems Handbook
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Springer New York, Springer US Aug 2016, 2016
ISBN 10 : 1489977805
ISBN 13 : 9781489977809
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Taschenbuch. Etat : Neu. 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. N° de réf. du vendeur 9781489977809
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Recommender Systems Handbook
Edité par
Springer New York, Springer US, 2016
ISBN 10 : 1489977805
ISBN 13 : 9781489977809
Neuf
Taschenbuch
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Taschenbuch. Etat : 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. N° de réf. du vendeur 9781489977809
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Recommender Systems Handbook
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Recommender Systems Handbook
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Springer, 2016
ISBN 10 : 1489977805
ISBN 13 : 9781489977809
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Recommender Systems Handbook
Edité par
Springer, 2016
ISBN 10 : 1489977805
ISBN 13 : 9781489977809
Ancien ou d'occasion
Couverture souple
Vendeur : GreatBookPrices, Columbia, MD, Etats-Unis
Évaluation du vendeur 5 sur 5 étoiles
Etat : As New. Unread book in perfect condition. N° de réf. du vendeur 30333337
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