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CORR
2007
Springer

Iterative Filtering for a Dynamical Reputation System

11 years 6 months ago
Iterative Filtering for a Dynamical Reputation System
The paper introduces a novel iterative method that assigns a reputation to n + m items: n raters and m objects. Each rater evaluates a subset of objects leading to a n × m rating matrix with a certain sparsity pattern. From this rating matrix we give a nonlinear formula to define the reputation of raters and objects. We also provide an iterative algorithm that superlinearly converges to the unique vector of reputations and this for any rating matrix. In contrast to classical outliers detection, no evaluation is discarded in this method but each one is taken into account with different weights for the reputation of the objects. The complexity of one iteration step is linear in the number of evaluations, making our algorithm efficient for large data set. Experiments show good robustness of the reputation of the objects against cheaters and spammers and good detection properties of cheaters and spammers. Keywords Ranking, Reputation System, Trust, Outlier Detection, Iterative Refinem...
Cristobald de Kerchove, Paul Van Dooren
Added 13 Dec 2010
Updated 13 Dec 2010
Type Journal
Year 2007
Where CORR
Authors Cristobald de Kerchove, Paul Van Dooren
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