Abstract When designing a sign language dictionary or lexical database, a criterion that needs to be decided on is how to organize handshapes in the search-by-sign interface. Although notation systems do exist for indexing and searching sign entries, dictionaries do not often use them. This study investigates how to classify and order images of handshapes without relying on the alphabetical order of handshape names or phonological parameters. For this purpose, a cluster analysis using three variables was applied, resulting in groups based on visual similarities between handshapes. The objects in the resulting clusters were reordered based on similarity and shape gradation principles, aiming for an optimal organization with regard to Prägnanz. Ultimately, as we expect native signers to rely on the visual features of signs, the taxonomy proposed in this study makes it possible to display handshapes in a way that requires fewer metalinguistic skills to support signers’ search actions.

中文翻译：

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寻找标志：开发基于视觉相似度的手形分类法

摘要 在设计手语词典或词汇数据库时，需要确定的一个标准是如何在按符号搜索界面中组织手形。尽管确实存在用于索引和搜索符号条目的符号系统，但字典并不经常使用它们。本研究探讨如何在不依赖手形名称或语音参数的字母顺序的情况下对手形图像进行分类和排序。为此，应用了使用三个变量的聚类分析，从而根据手形之间的视觉相似性进行分组。生成的集群中的对象根据相似性和形状渐变原则重新排序，旨在实现 Prägnanz 的最佳组织。最终，正如我们期望本地签名者依赖标志的视觉特征一样，