  When doing a study on a large number of video games, it may be difficult to
cluster them into coherent groups to better study them. In this paper, we
introduce a novel algorithm, that takes as input any set of games S that are
released on Steam and an integer k, and cluster S into k groups. Each group is
then assigned a distinctive name in the form of a Steam tag. We believe our
tool to be valuable for gaining deeper insights into the video game market. We
show that our algorithm maximises an objective function that we introduce, the
naming score, which assesses the quality of a clustering and how distinctive
its name is.
