Apparatus and method for staged graph processing to produce a risk inference measure

A computer implemented method, comprising:

• collecting at a first machine information characterizing an incident on a second machine, wherein the first machine and the second machine communicate via a network;
• processing a deterministic factual graph to produce superfacts, wherein the deterministic factual graph has deterministic factual graph leaf nodes individually resolving facts characterizing the incident to discrete-valued outcomes, and parent nodes of the deterministic factual graph leaf nodes resolving the discrete-valued outcomes to superfacts, wherein each superfact is a qualitative characterization summarizing discrete-valued outcomes;
• processing a stochastic factual graph to produce a risk inference measure for the incident, wherein the stochastic factual graph has stochastic factual graph leaf nodes incorporating the facts or superfacts, wherein the stochastic factual graph is a Bayesian network wherein except for a base node each stochastic factual graph node is associated with a probability function and edges between stochastic factual graph nodes represent conditional dependencies;
• comparing the risk inference measure to an escalation threshold;
• evaluating the incident when the risk inference measure exceeds the escalation threshold;
• evaluating the incident to reach a risk conclusion;
• and
• updating a probability function in the Bayesian network based upon the risk conclusion.