Chapter 16 - Spectral and graph clustering. In this chapter we consider clustering over graph data, that is, given a graph, the goal is to cluster the nodes by using the edges and their weights, which represent the similarity between the incident nodes. Graph clustering is related to divisive hierarchical clustering, as many methods partition the set of nodes to obtain the final clusters using the pairwise similarity matrix between nodes. |