We chose two relatively high levels of similarity (0.8 and 0.9), and used complete-link agglomerative (i.e., bottom-up) clustering to merge similar caseframes.
each caseframe begins as a separate cluster, and the two most similar clusters are merged at each step until the desired similarity threshold is reached.