The presented knowledge graph illustrates a complex decision making process utilising {model_name}. The graph consists of {number_nodes} nodes, restricted to the top {number_nodes} from the generated WSDDT. For this reason, some nodes identified as being on the shortest path may not be present in the graph.
The graph illustrates a layered connection of nodes, demonstrating importance in the network layer with the most important nodes on the inner rings. The nodes are coloured and scaled in size to further convey importance.
Nodes are connected to one another by edges and are presented in grey and red. There are a total of {connections} edges connecting {number_nodes} nodes in the graph. This demonstrates the relationships that have been identified through precomputing differentials and {model_name} path finding logic. While there are {connections} edges in total, there are {best_connections} edges (highlighted in red) that are on the best paths to the optimal differential.
However, identifying the shortest path from the data is difficult due to the number of total relationships ({connections}), and highlighted best paths to the optional differential ({best_connections}). By applying careful insights and processing the data, the best and shortest path travels through nodes {shortest_path}. In this visualisation, the highest value nodes may not be visible due to the pruning of the graph.