1. INTRODUCTION
The analysis of human similarity judgements is important in a range of fields, such as cognitive science, linguistics, and market research. Due to the recent advent of crowd sourcing, human similarity judgements analysis has recently also received significant attention in machine learning [1], [2], [3], [4], [5], [6]. In particular, a number of machine-learning techniques have been developed that facilitate the visual exploration of simi-1arity judgements via embeddings.