Clustering algorithms are usually a form of unsupervised learning possibly with cluster labels attached post-hoc. However, each implicitly or explcitly has an idea of a 'good' cluster, such as a small distance between items and the centre, or no obvious sub-clusters. For clustering of text dcuemnts, teher is often a desire to have clusters that are meaningful for humans, and various specialised coherence scores have been proposed for this.
Used in Chap. 9: page 134
Links:
ACM Digital Library:
Automatic evaluation of topic coherence
ACM Digital Library:
Exploring the Space of Topic Coherence Measures