Lattices and their order diagrams are an essential tool for communicating knowledge and insights about data. This is in particular true when applying Formal Concept Analysis. Such representations, however, are difficult to comprehend by untrained users and in general in cases where lattices are large. We tackle this problem by automatically generating textual explanations for lattices using standard scales. Our method is based on the general notion of ordinal motifs in lattices for the special case of standard scales. We show the computational complexity of identifying a small number of standard scales that cover most of the lattice structure. For these, we provide textual explanation templates, which can be applied to any occurrence of a scale in any data domain. These templates are derived using principles from human-computer interaction and allow for a comprehensive textual explanation of lattices. We demonstrate our approach on the spices planner data set, which is a medium sized formal context comprised of fifty-six meals (objects) and thirty-seven spices (attributes). The resulting 531 formal concepts can be covered by means of about 100 standard scales.

翻译：格及其序图是传达数据知识与洞见的重要工具，这在形式概念分析应用中尤为突出。然而，此类表示对未经训练的用户以及处理大规模格结构时往往难以理解。我们通过利用标准尺度自动生成格的文本解释来解决这一问题。该方法基于格中序数模式的一般概念，并针对标准尺度这一特例进行优化。我们揭示了识别覆盖大部分格结构的少量标准尺度的计算复杂度。针对这些标准尺度，我们提供了可跨数据域应用于任何尺度实例的文本解释模板，这些模板借鉴人机交互原理设计，能够对格进行全面的文本化解释。我们在香料规划数据集上验证了该方法——该中等规模的形式背景包含56个餐食（对象）与37种香料（属性），生成的531个形式概念可通过约100个标准尺度实现全覆盖。