Recommender Systems for Information Providers: Designing Customer Centric Paths to Information

  • Authors:
  • Andreas W. Neumann

  • Affiliations:
  • -

  • Venue:
  • Recommender Systems for Information Providers: Designing Customer Centric Paths to Information
  • Year:
  • 2009

Quantified Score

Hi-index 0.00

Visualization

Abstract

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.