Minimum cuts can cluster data. Build a graph where vertices are data points and edge weights represent similarity. The minimum cut splits the graph into two clusters with minimal inter-cluster connections. For clusters, you recursively apply minimum cuts or use more advanced techniques.
Each cut separates the most distinct groups based on the similarity metric. This works when you want to minimize connections between clusters. The cut naturally finds boundaries between dense regions.