Abstract: In some examples, a computer receives event data relating to events of a system, and builds a graph comprising nodes representing respective values of attributes of the events, and edges between the nodes, each respective edge of the edges representing co-occurrence of values of attributes represented by nodes connected by the respective edge. The computer computes edge weights of corresponding edges of the edges, and identifies paths in the graph, where each path of the paths comprises two or more nodes and a corresponding edge or edges. The computer determines an affinity among the values of the attributes based on a shortest path determining process that uses the edge weights for distances of the identified paths, and resolves an anomaly in the system based on the determined affinity.

Abstract: In some examples, a computer receives event data relating to events of a system, and builds a graph comprising nodes representing respective values of attributes of the events, and edges between the nodes, each respective edge of the edges representing co-occurrence of values of attributes represented by nodes connected by the respective edge. The computer computes edge weights of corresponding edges of the edges, and identifies paths in the graph, where each path of the paths comprises two or more nodes and a corresponding edge or edges. The computer determines an affinity among the values of the attributes based on a shortest path determining process that uses the edge weights for distances of the identified paths, and resolves an anomaly in the system based on the determined affinity.