We present an improved library for the ranking problem called RPLIB. RPLIB includes the following data and features. (1) Real and artificial datasets of both pairwise data (i.e., information about the ranking of pairs of items) and feature data (i.e., a vector of features about each item to be ranked). These datasets range in size (e.g., from small $n=10$ item datasets to large datasets with hundred of items), application (e.g., from sports to economic data), and source (e.g. real versus artificially generated to have particular structures). (2) RPLIB contains code for the most common ranking algorithms such as the linear ordering optimization method and the Massey method. (3) RPLIB also has the ability for users to contribute their own data, code, and algorithms. Each RPLIB dataset has an associated .JSON model card of additional information such as the number and set of optimal rankings, the optimal objective value, and corresponding figures.

翻译：我们为排名问题提出了一个改进的图书馆,名为 RPLIB。 RIPIB, 包括下列数据和特征:(1) 双对数据(即关于对项目排序的信息)和特征数据(即每个项目排名的特性矢量)的真实和人工数据集,这些数据集的规模(例如,从小美元=10美元到有100个项目的大型数据集)、应用(例如,从体育到经济数据)和来源(例如,实际和人为生成的具有特定结构的数据集)。 (2) REPLIB 包含最常用排序算法的代码,例如线性排序优化方法和Massey方法。 (3) RIB 也有能力让用户贡献自己的数据、代码和算法。 每一 RPLIB 数据集都有一个相关的额外信息模型卡,如最佳排序数和数据集、最佳目标值和相应数字。