Recommender Systems HandbookFrom Springer

Recommender Systems HandbookFrom Springer

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Recommender Systems HandbookFrom Springer

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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.

Recommender Systems HandbookFrom Springer

• Amazon Sales Rank: #935404 in Books
• Published on: 2015-11-19
• Original language: English
• Number of items: 1
• Dimensions: 9.21" h x 2.06" w x 6.14" l, 3.51 pounds
• Binding: Hardcover
• 1003 pages

Recommender Systems HandbookFrom Springer

About the Author 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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Most helpful customer reviews

2 of 2 people found the following review helpful. A must-have resource if you're serious about building effective recommenders By Amazon Customer If you've got a serious interest in learning the concepts and techniques for building recommender systems - that is, the code, the computing resources, the architecture, and the tools to evaluate their performance - this is a wonderful resource to have by your side. It's a serious of in-depth essays by some of the heavyweights in the recommender system research community, describing the major areas you'll need to know. It's a very good read with ample case studies, tips, and sound, up-to-date formulas and algorithms you'll need to become a competent recommender system developer.What's best: because the chapters are independent units focusing on specific topics, you can jump around for reference or re-read them for refresher without needing to tackle the entire work from scratch.

0 of 0 people found the following review helpful. Great authors, but I have to say only limited ... By Victor Great authors, but I have to say only limited knowledge was inside this book. Reading this book is like reading the Background and Introduction part of a research paper, to understand details, its necessary to read individual papers.

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Recommender Systems HandbookFrom Springer

Recommender Systems HandbookFrom Springer

Recommender Systems HandbookFrom Springer

Recommender Systems HandbookFrom Springer