Hierarchical Clustering

Semantic Clustering
Hierarchical Clustering
Hierarchical Clustering creates a tree (dendrogram) of cluster relationships—useful when you don't know the optimal number of groups upfront.

Hierarchical Clustering is an algorithm that creates a tree (dendrogram) of cluster relationships, showing how subclusters merge into larger groups at successive levels. In SEO, it's used to build site category hierarchies—the dendrogram maps directly to navigation structure: main branches = categories, sub-branches = subcategories, leaves = articles. Unlike K-means (flat division into k groups), hierarchical clustering provides multi-level structure without needing to specify k upfront.

Hierarchical clustering complements K-means—K-means gives clusters, the dendrogram shows how those clusters connect to each other.

In practice, visualize the dendrogram and cut it at the level matching your site's navigation depth (2-3 levels for typical blogs, 4-5 for e-commerce).

Source: AI Semantic SEO Expert, Robert Niechciał (sensai.io)