Rank Centrality: Ranking from Pairwise Comparisons

Rank Centrality: Ranking from Pairwise Comparisons

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 bas...

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Bibliographic Details
Main Authors: Negahban, Sahand (Author), Oh, Sewoong (Author), Shah, Devavrat (Contributor)
Other Authors: Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science (Contributor), Massachusetts Institute of Technology. Laboratory for Information and Decision Systems (Contributor)
Format: Article
Language:English
Published: Institute for Operations Research and the Management Sciences (INFORMS), 2017-08-28T18:16:55Z.
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