Spectral clustering in telephone call graphs
Miklós Kurucz, András A. Benczúr, Károly Csalogány, Lukács László · 2007
We evaluate various heuristics for hierarchical spectral clustering in large telephone call graphs. Spectral clustering without additional heuristics often produces very uneven cluster sizes or low quality clusters that may consist of several disconnected components, a fact that appears to be common for several data sources but, to our knowledge, not described in the literature. Divide-and-Merge, a recently described postfiltering procedure may be used to eliminate bad quality branches in a binary tree hierarchy. We propose an alternate solution that enables k-way cuts in each step by immediately filtering unbalanced or low quality clusters before splitting them further.