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| 文件名: Recommender Systems Handbook.pdf | |
| 资料下载链接地址: https://bbs.pinggu.org/a-805878.html | |
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推荐系统非常有用,可以看成是当前面对信息过载问题的一种有效处理手段。与搜索这种Pull信息形式不同的是,个性化推荐并不需要用户输入关键词而直接将用户可能感兴趣的信息Push给用户。相信不少朋友都访问过Amazon的书籍介绍页面,经常看到“买了这本书的人还买了。。。”这样一种推荐。推荐是怎么做到的?困难在哪儿?目前的研究情况如何?将来的发展趋势?这本handbook将会帮助大家释疑,带领大家进入个性化推荐技术领域,希望大家喜欢。
Recommender Systems Handbook 842 pages Publisher: Springer; 1st Edition. edition (October 28, 2010) Language: English ISBN-10: 0387858199 ISBN-13: 978-0387858197 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. |
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