This book introduces different approaches to developing recommender systems that automate choice-making strategies to provide affordable, personal, and high-quality recommendations.
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Dietmar Jannach is a chaired Professor of Computer Science at TU Dortmund, Germany. The author of more than 100 scientific papers, he is a member of the editorial board of the Applied Intelligence journal and the review board of the International Journal of Electronic Commerce.
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Anbieter: Better World Books: West, Reno, NV, USA
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Zustand: Good. Your purchase helps support Sri Lankan Children's Charity 'The Rainbow Centre'. Ex-library, so some stamps and wear, but in good overall condition. Our donations to The Rainbow Centre have helped provide an education and a safe haven to hundreds of children who live in appalling conditions. Artikel-Nr. Z1-AA-007-00639
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Anbieter: Revaluation Books, Exeter, Vereinigtes Königreich
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Buch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - In this age of information overload, people use a variety of strategies to make choices about what to buy, how to spend their leisure time, and even whom to date. Recommender systems automate some of these strategies with the goal of providing affordable, personal, and high-quality recommendations. This book offers an overview of approaches to developing state-of-the-art recommender systems. The authors present current algorithmic approaches for generating personalized buying proposals, such as collaborative and content-based filtering, as well as more interactive and knowledge-based approaches. They also discuss how to measure the effectiveness of recommender systems and illustrate the methods with practical case studies. The final chapters cover emerging topics such as recommender systems in the social web and consumer buying behavior theory. Suitable for computer science researchers and students interested in getting an overview of the field, this book will also be useful for professionals looking for the right technology to build real-world recommender systems. This book offers an overview of approaches to developing state-of-the-art recommender systems that automate a variety of choice-making strategies with the goal of providing affordable, personal, and high-quality recommendations. The authors present algorithmic approaches for generating personalized buying proposals, as well as more interactive and knowledge-based approaches. They discuss how to measure the effectiveness of recommender systems and illustrate the methods with practical case studies. Artikel-Nr. 9780521493369
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