In this work we analyse a number of variants of the Wasserstein distance which allow to focus the classification on the prescribed parts (fragments) of classified 2D curves. These variants are based on the use of a number of discrete probability measures which reflect the importance of given fragments of curves. The performance of this approach is tested through a series of experiments related to the clustering analysis of 2D curves performed on data coming from the field of archaeology.

翻译：本文分析了Wasserstein距离的若干变体，这些变体能够将分类重点聚焦于待分类二维曲线的指定部分（片段）。这些变体基于多种离散概率测度的运用，这些测度反映了曲线特定片段的重要性。该方法的性能通过一系列实验进行验证，这些实验涉及考古学领域数据的二维曲线聚类分析。