Recommender Systems Handbook

Recommender Systems Handbook

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The explosive growth of e-commerce and online environments has made the issue of information search and selection increasingly serious; users are overloaded by options to consider and they may not have the time or knowledge to personally evaluate these options. Recommender systems have proven to be a valuable way for online users to cope with the information overload and have become one of the most powerful and popular tools in electronic commerce. Correspondingly, various techniques for recommendation generation have been proposed. During the last decade, many of them have also been successfully deployed in commercial environments. Recommender Systems Handbook, an edited volume, is a multi-disciplinary effort that involves world-wide experts from diverse fields, such as artificial intelligence, human computer interaction, information technology, data mining, statistics, adaptive user interfaces, decision support systems, marketing, and consumer behavior. Theoreticians and practitioners from these fields continually seek techniques for more efficient, cost-effective and accurate recommender systems. This handbook aims to impose a degree of order on this diversity, by presenting a coherent and unified repository of recommender systemsa€™ major concepts, theories, methodologies, trends, challenges and applications. Extensive artificial applications, a variety of real-world applications, and detailed case studies are included. Recommender Systems Handbook illustrates how this technology can support the user in decision-making, planning and purchasing processes. It works for well known corporations such as Amazon, Google, Microsoft and ATaT. This handbook is suitable for researchers and advanced-level students in computer science as a reference.Expert Systems with Applications, 27(4):549a€“557, 2004. Chow, C., Liu, C. ... Computer science and decision theory: Applications of notions of consensus description of the research issues in the project. In COST Action ... Journal of the American Society for Information Science and Technology, 57(4):538a€“549, 2006.

Title:Recommender Systems Handbook
Author:Francesco Ricci, Lior Rokach, Bracha Shapira, Paul B. Kantor
Publisher:Springer Science & Business Media - 2010-10-21


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