Flow-based Algorithms for Improving Clusters: A Unifying Framework, Software, and Performance

Understand

Clustering points in a vector space or nodes in a graph is a ubiquitous primitive in statistical data analysis, and it is commonly used for exploratory data analysis.

• In practice, it is often of interest to "refine" or "improve" a given cluster that has been obtained by some other method.
• In this survey, we focus on principled algorithms for this cluster improvement problem.
• Many such cluster improvement algorithms are flow-based methods, by which we mean that operationally they require the solution of a sequence of maximum flow problems on a (typically implicitly) modified data graph.