Manipulation Robustness of Collaborative Filtering Systems
A collaborative filtering system recommends to users products that similar users like. Collaborative filtering systems influence purchase decisions, and hence have become targets of manipulation by unscrupulous vendors. We provide theoretical and empirical results demonstrating that while common nearest neighbor algorithms, which are widely used in commercial systems, can be highly susceptible to manipulation, two classes of collaborative filtering algorithms which we refer to as linear and asymptotically linear are relatively robust. These results provide guidance for the design of future collaborative filtering systems.
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Nolan Miller & Paul Resnick & Richard Zeckhauser, 2005. "Eliciting Informative Feedback: The Peer-Prediction Method," Management Science, INFORMS, vol. 51(9), pages 1359-1373, September.
- Gossner, Olivier & Tomala, Tristan, 2008.
"Entropy bounds on Bayesian learning,"
Journal of Mathematical Economics,
Elsevier, vol. 44(1), pages 24-32, January.
- Olivier Gossner & Tristan Tomala, 2008. "Entropy bounds on Bayesian learning," Post-Print halshs-00754314, HAL.
- Tristan Tomala & Olivier Gossner, 2008. "Entropy bounds on Bayesian learning," Post-Print hal-00464554, HAL.
- Chrysanthos Dellarocas, 2006. "Strategic Manipulation of Internet Opinion Forums: Implications for Consumers and Firms," Management Science, INFORMS, vol. 52(10), pages 1577-1593, October.
- repec:dau:papers:123456789/6067 is not listed on IDEAS
- Sangkil Moon & Gary J. Russell, 2008. "Predicting Product Purchase from Inferred Customer Similarity: An Autologistic Model Approach," Management Science, INFORMS, vol. 54(1), pages 71-82, January. Full references (including those not matched with items on IDEAS)
When requesting a correction, please mention this item's handle: RePEc:net:wpaper:0921. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Nicholas Economides)
If references are entirely missing, you can add them using this form.