论文标题
通过成对比较的有效计算排名
Efficient computation of rankings from pairwise comparisons
论文作者
论文摘要
我们使用Bradley-Terry模型根据他们之间的成对比较来研究个人，团队或对象的排名。该模型中排名的估计通常是使用Zermelo在大约一个世纪前首次提出的简单迭代算法进行的。在这里，我们描述了一种替代性且同样简单的迭代，该迭代可证明可以返回相同的结果，但效果更快得多 - 在某些情况下，超过一百倍。我们将该算法与应用程序应用于示例数据集的应用，并获得有关其收敛性的许多结果。
We study the ranking of individuals, teams, or objects, based on pairwise comparisons between them, using the Bradley-Terry model. Estimates of rankings within this model are commonly made using a simple iterative algorithm first introduced by Zermelo almost a century ago. Here we describe an alternative and similarly simple iteration that provably returns identical results but does so much faster -- over a hundred times faster in some cases. We demonstrate this algorithm with applications to a range of example data sets and derive a number of results regarding its convergence.
