论文标题
从面向数据的角度开发排名问题库（RPLIB）
Developing a Ranking Problem Library (RPLIB) from a data-oriented perspective
论文作者
论文摘要
我们为RPLIB的排名问题提供了改进的库。 RPLIB包括以下数据和功能。 （1）成对数据的真实和人工数据集（即有关对项目对排名的信息）和特征数据（即，有关每个项目的特征向量）。这些数据集的范围（例如，从小$ n = 10 $项目数据集到具有数百个项目的大型数据集），应用程序（例如，从体育数据到经济数据）和源（例如，真实的与人为生成的特定结构）。 （2）RPLIB包含最常见的排名算法的代码，例如线性排序优化方法和Massey方法。 （3）RPLIB还具有用户贡献自己的数据，代码和算法的能力。每个RPLIB数据集都有一个相关的.json模型卡的其他信息，例如最佳排名的数字和集合，最佳目标值和相应的数字。
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.
