Exploração do comportamento de um algoritmo combinatório para o particionamento de grafos núcleo-periferia

Abstract

Most real life large-scale networks present a topological structure that can be partitioned into two substructures, the Core and the Periphery. When such a partitioning is achieved, an analysis of the behaviour of the core can be extrapolated to obtain an understanding of the behaviour of the entire network. Due to their reliability, spectral algorithms have so far dominated the field of study when it comes to identifying the core of a network; however, spectral algorithms perform very complex computations, which are computationally expensive, and educationally complicated. This study is an exploration into the way an algorithm, based on a non-spectral approach, would perform when tested on a set of graphs with varied structures, attempting to determine whether it could be a viable, simple, and fast alternative to the complex and costly algorithms currently dominating this subject.