论文标题
与多种类型的成对比较进行排名
Ranking with multiple types of pairwise comparisons
论文作者
论文摘要
基于对成对之间的一系列比较，对个人或团队进行排名的任务是在各种情况下出现的，包括体育比赛和对动物和人类之间的优势等级制度的分析。鉴于竞争对手击败其他人的数据，挑战是将竞争对手从最佳到最糟糕进行排名。在这里，我们研究计算排名的问题时，当存在多种相互冲突的比较模式，例如动物之间多种类型的优势行为。我们假设我们不知道每个行为传达有关排名的哪些信息，或者它们是否完全传达了任何信息。尽管如此，我们表明可以根据期望最大化算法和修改后的Bradley-Terry模型的组合来计算这种情况下的排名，并提出一种快速的方法。我们为动物和人类竞争提供了一些示例申请。
The task of ranking individuals or teams, based on a set of comparisons between pairs, arises in various contexts, including sporting competitions and the analysis of dominance hierarchies among animals and humans. Given data on which competitors beat which others, the challenge is to rank the competitors from best to worst. Here we study the problem of computing rankings when there are multiple, potentially conflicting modes of comparison, such as multiple types of dominance behaviors among animals. We assume that we do not know a priori what information each behavior conveys about the ranking, or even whether they convey any information at all. Nonetheless we show that it is possible to compute a ranking in this situation and present a fast method for doing so, based on a combination of an expectation-maximization algorithm and a modified Bradley-Terry model. We give a selection of example applications to both animal and human competition.
