Cross-Environment Event Correlation Using Domain-Space Exploration and Machine Learning Techniques

A non-transitory computer-readable storage medium tangibly embodying a computer-readable program code having computer-readable instructions that, when executed, causes a computer device to perform a method of cross-environment event correlation, the method comprising:

• determining one or more correlated events about an issue across a plurality of domains;
• extracting a knowledge data of the issue determined from the one or more correlated events;
• generating a correlation graph of the extracted knowledge data to trace the issue;
• grouping the correlated events into one or more event groups to represent a relationship with the issue;
• constructing a logical reasoning description based on the generated correlation graph for a domain-space exploration related to how the issue in one domain affects another domain of the plurality of domains;
• and
• providing the one or more event groups of correlated events with an explanation about a cause of the issue for the one or more correlated events based on the logical reasoning description.

A computing device for cross-environment event correlation using space-exploration, comprising:

• a processor;
• a memory coupled to the processor, the memory storing instructions to cause the processor to perform acts comprising:
• determining one or more correlated events about an issue across a plurality of domains;
• extracting a knowledge data of the issue determined from the one or more correlated events;
• constructing a logical reasoning description for domain-space exploration related to how the issue in one domain affects another domain of the plurality of domains;
• generating one or more correlation graphs based on the domain-space exploration to trace the issue;
• grouping the correlated events in one or more groups;
• constructing semantic relationships between different domains, and
• recommending the most probable event groups of correlated events with an explanation about a cause of the issue for the one or more correlated events based on the logical reasoning description.