Clustering is a task that divides objects into groups based on the similarity between objects. It is usually used as a tool for exploratory knowledge discovery, i.e., it is used to extract potentially useful and previously unknown knowledge from data, before experts have any insight. Because of the exploratory nature of clustering tasks, it is usually not adequate to simply provide clustering results that separate samples into groups. The domain scientists or data analysts in general also want to gain insight into the data. Therefore, it is desired to develop interpretable clustering models, which help the experts to attain deeper knowledge, by understanding what characterizes a cluster