个性化技术和推荐系统

Gulden Uchyigit, Matthew Y. Ma
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引用次数: 32

摘要

互联网的惊人增长导致了大量的在线信息,这种情况对最终用户来说是压倒性的。为了克服这个问题,个性化技术得到了广泛的应用。这本书是同类书中的第一本,代表了个性化和推荐技术多样性的研究成果。这些包括用户建模、内容、协作、混合和基于知识的推荐系统。从移动信息访问、营销与销售、网络服务到图书馆和个性化电视推荐系统的各种应用背景下进行理论研究。本卷将作为一个基础的研究人员谁希望学习更多的领域推荐系统,也为那些打算部署先进的个性化技术在他们的系统。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Personalization Techniques and Recommender Systems
The phenomenal growth of the Internet has resulted in huge amounts of online information, a situation that is overwhelming to the end users. To overcome this problem, personalization technologies have been extensively employed. The book is the first of its kind, representing research efforts in the diversity of personalization and recommendation techniques. These include user modeling, content, collaborative, hybrid and knowledge-based recommender systems. It presents theoretic research in the context of various applications from mobile information access, marketing and sales and web services, to library and personalized TV recommendation systems. This volume will serve as a basis to researchers who wish to learn more in the field of recommender systems, and also to those intending to deploy advanced personalization techniques in their systems.
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