Application of Graph Neural Networks in a Selected Domain

Abstract

This bachelor thesis focuses on complex networks analysis with graph neural networks. The aim was to classify nodes and edges in complex networks and evaluate the classifier’s performance. This work has the theoretical part, where we introduce concepts we are using, and the practical part, where we build, train and evaluate a classifier in three independent experiments. The results showed that classifiers based on graph neural networks are effective and useful in transductive learning.