Detecting Sponsored Recommendations
ACM transactions on modeling and performance evaluation of computing systems(2016)
摘要
Personalized recommender systems provide great opportunities for targeted advertisements, by displaying ads alongside genuine recommendations. We consider a biased recommendation system where such ads are displayed without any tags (disguised as genuine recommendations), rendering them indistinguishable to users. We consider the problem of detecting such a bias and propose an algorithm that uses statistical analysis based on binary feedback data from a subset of users. We prove that the proposed algorithm detects bias with high probability for a broad class of recommendation systems with sufficient number of feedback samples.
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关键词
Behavioral Analysis,Bot Detection,Spam Detection
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