Recommender Systems Handbook

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...

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Những tác giả chính: Ricci, Francesco, Rokach, Lior, Shapira, Bracha, Kantor, Paul B.
Định dạng: Sách
Ngôn ngữ:English
Được phát hành: Springer - Verlag 2011
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Truy cập trực tuyến:http://scholar.dlu.edu.vn/thuvienso/handle/DLU123456789/25949
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spelling oai:scholar.dlu.edu.vn:DLU123456789-259492012-03-03T04:33:38Z Recommender Systems Handbook Ricci, Francesco Rokach, Lior Shapira, Bracha Kantor, Paul B. Tin học Database 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 systems’ 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 AT&T. This handbook is suitable for researchers and advanced-level students in computer science as a reference. 2011-09-21T08:39:49Z 2011-09-21T08:39:49Z 2011 Book 978-0-387-85819-7 978-0-387-85820-3 http://scholar.dlu.edu.vn/thuvienso/handle/DLU123456789/25949 en application/pdf Springer - Verlag
institution Thư viện Trường Đại học Đà Lạt
collection Thư viện số
language English
topic Tin học
Database
spellingShingle Tin học
Database
Ricci, Francesco
Rokach, Lior
Shapira, Bracha
Kantor, Paul B.
Recommender Systems Handbook
description 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 systems’ 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 AT&T. This handbook is suitable for researchers and advanced-level students in computer science as a reference.
format Book
author Ricci, Francesco
Rokach, Lior
Shapira, Bracha
Kantor, Paul B.
author_facet Ricci, Francesco
Rokach, Lior
Shapira, Bracha
Kantor, Paul B.
author_sort Ricci, Francesco
title Recommender Systems Handbook
title_short Recommender Systems Handbook
title_full Recommender Systems Handbook
title_fullStr Recommender Systems Handbook
title_full_unstemmed Recommender Systems Handbook
title_sort recommender systems handbook
publisher Springer - Verlag
publishDate 2011
url http://scholar.dlu.edu.vn/thuvienso/handle/DLU123456789/25949
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