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2013-04-27
Contributions to Management Science
2009
Recommender Systems for Information ProvidersDesigning Customer Centric Paths to InformationAuthors:
ISBN: 978-3-7908-2133-8 (Print) 978-3-7908-2134-5  (Online)

Recommender Systems for Information Providers

Designing Customer Centric Paths to Information

Series: Contributions to Management Science

Neumann, Andreas W.

2009

A product of Physica Verlag Heidelberg

ISBN 978-3-7908-2134-5

  Immediately available per PDF-download (no DRM, watermarked)


About this book
Information providers are a very promising application area of recommender systems due to the general problem of assessing the quality of information products prior to the purchase. Recommender systems automatically generate product recommendations: customers profit from a faster finding of relevant products, stores profit from rising sales. All aspects of recommender systems are covered: the economic background, mechanism design, a survey of systems in the Internet, statistical methods and algorithms, service oriented architectures, user interfaces, as well as experiences and data from real-world applications. Specific solutions for areas with strong privacy concerns, scalability issues for large collections of products, as well as algorithms to lessen the cold-start problem for a faster return on investment of recommender projects are addressed. This book describes all steps it takes to design, implement, and successfully operate a recommender system for a specific information platform.

Table of contents Introduction.- The Market of Scientific and Technical Information.- Classification and Mechanism Design of Recommender Systems.- A Survey of Recommender Systems at Major STI Providers.- Case Study: Explicit Recommender Services for Scientific Libraries.- General Concepts of Behavior-Based Recommender Services.- Algorithms for Behavior-Based Recommender Systems.- Case Study: Behavior-Based Recommender Services for Scientific Libraries.- Visualizing and Exploring Information Spaces. Discussion.

Recommender Systems for Information Providers.pdf
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2013-6-11 17:27:11
太贵了!!
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2013-9-19 08:24:55
信息提供者由于质量评估信息产品购买前的一般问题的推荐系统是一个非常有前途的应用领域。推荐系统自动生成产品的建议:客户利润更快的发现有关产品,店铺销售上升利润。包括:推荐系统的所有方面的经济背景,机制设计,系统在互联网上的一项调查,统计方法和算法,面向服务的架构,用户界面,以及经验和现实世界的应用程序的数据。具体解决方案领域具有强大的隐私的关注,大集合产品的可扩展性问题,以及一个更快的推荐项目的投资回报率的算法,以减少冷启动的问题得到解决。这本书描述了所有步骤,它需要设计,实施和推荐系统成功运行一个特定的信息平台。
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