Manipulation Robustness of Collaborative Filtering

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.

• 저널Management Science · 56(11) · 1911–1929
• 토픽Mobile Crowdsensing and Crowdsourcing · Computer Science Applications
• DOI10.1287/mnsc.1100.1232
• 저자Benjamin Van Roy, Xiang Yan