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Recommender Systems for Information Providers: Designing Customer Centric Paths to Information: Contributions to Management Science

Autor Andreas W. Neumann
en Limba Engleză Hardback – 20 mar 2009
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.
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Specificații

ISBN-13: 9783790821338
ISBN-10: 3790821330
Pagini: 172
Ilustrații: X, 158 p. 47 illus.
Dimensiuni: 155 x 235 x 17 mm
Greutate: 0.42 kg
Ediția:2009
Editura: Physica-Verlag HD
Colecția Physica
Seria Contributions to Management Science

Locul publicării:Heidelberg, Germany

Public țintă

Research

Cuprins

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 Scientificc Libraries.- Visualizing and Exploring Information Spaces.- Discussion.

Textul de pe ultima copertă

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.