Abstract
Recommender systems [Resnick and Varian, 1997] have gained wide-spread acceptance and attracted increased public interest during the last decade, levelling the ground for new sales opportunities in e-commerce [Schafer et al, 1999; Sarwar et al, 2000a]. For instance, online retailers like Amazon.com (http://www.amazon.com) successfully employ an extensive range of different types of recommender systems.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
Copyright information
© 2013 Springer International Publishing Switzerland
About this chapter
Cite this chapter
Ziegler, CN. (2013). On Recommender Systems. In: Social Web Artifacts for Boosting Recommenders. Studies in Computational Intelligence, vol 487. Springer, Cham. https://doi.org/10.1007/978-3-319-00527-0_2
Download citation
DOI: https://doi.org/10.1007/978-3-319-00527-0_2
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-00526-3
Online ISBN: 978-3-319-00527-0
eBook Packages: EngineeringEngineering (R0)