Graph Clustering

Sven A. Wegner ()

Chapter Chapter 5 in Mathematical Introduction to Data Science, 2024, pp 61-79 from Springer

Abstract: Abstract We revisit the example of social networks from Chapter 1 and deal with the question of how clusters can be found in such a setting. After introducing some terms from graph theory—in particular, the adjacency and Laplace matrix—we explain heuristically how clusters and eigenvalues are linked via the Courant-Fischer formula. After introducing further terms, in particular: normalized Laplace matrix, volume, conductance, we formalize the aforementioned connection via Cheeger’s inequality.

Date: 2024
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DOI: 10.1007/978-3-662-69426-8_5

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