Rank Centrality: Ranking from Pairwise Comparisons

  title={Rank Centrality: Ranking from Pairwise Comparisons},
  author={Sahand Negahban and Sewoong Oh and Devavrat Shah},
  journal={Operations Research},
The question of aggregating pairwise comparisons to obtain a global ranking over a collection of objects has been of interest for a very long time: be it ranking of online gamers (e.g. MSR’s TrueSkill system) and chess players, aggregating social opinions, or deciding which product to sell based on transactions. In most settings, in addition to obtaining a ranking, finding ‘scores’ for each object (e.g. player’s rating) is of interest for understanding the intensity of the preferences. In this… CONTINUE READING
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