Graph- and multigrafh-theoretic partitioning clustering algorithms for large data sets

Abstract

This work aims at introducing two clustering algorithms conceived to make the application of particular graph and multigraph theoretic clustering methods possible for large data sets. Results obtained by applying the suggested algorithms to simulated data sets are presented.