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Please use this identifier to cite or link to this item:
http://hdl.handle.net/2451/29516
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| Title: | Manipulation Robustness of Collaborative Filtering Systems |
| Authors: | Van Roy, Benjamin - Stanford University
Yan, Xiang - Stanford University |
| Issue Date: | 2009 |
| Series/Report no.: | Net Institute Working Paper;09-21 |
| Abstract: | 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. |
| URI: | http://hdl.handle.net/2451/29516 |
| Appears in Collections: | NET Institute Working Papers Series
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