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Manipulation Robustness of Collaborative Filtering.
- Source :
- Management Science; Nov2010, Vol. 56 Issue 11, p1911-1929, 19p, 1 Chart, 3 Graphs
- Publication Year :
- 2010
-
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 demonstrate that nearest neighbors algorithms, which are widely used in commercial systems, are highly susceptible to manipulation and introduce new collaborative filtering algorithms that are relatively robust. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 00251909
- Volume :
- 56
- Issue :
- 11
- Database :
- Complementary Index
- Journal :
- Management Science
- Publication Type :
- Academic Journal
- Accession number :
- 55192682
- Full Text :
- https://doi.org/10.1287/mnsc.1100.1232