Development of graph-based management tool based on Graph Neural Networks

Knowledge Graphs, a form of connected data, created a new research field to apply machine learning algorithms called Graph Neural Networks (GNN). We study several GNN models by integrating them into a newly proposed framework called GrafAE, introducing multiple novel GNN models. Furthermore, in this work, we research the effect of embedding dimensionality, a vector representation of the knowledge graphs’ features, and the impact of embedding initialization. Finally, we report several improvements on the studied GNN models and propose an enhancement to a GNN that yields state-of-the-art results with the original evaluation method which may return too high performance and could benefit from a new evaluation process