Systems and methods for determining historical incident similarity predictions using signal similarities based on graph modelling

A computer-implemented method for finding historically similar incidents in a system, the method comprising:

• obtaining a plurality of historical embedding vectors for a plurality of historical data objects;
• receiving a current data object indicating an occurrence of a current incident associated with a configurable item, the current data object being associated with a line of business data object;
• determining a configurable item graph including one or more subtrees, wherein the configurable item graph is a graph of logical associations of the line of business data object and related IT operation events;
• determining an amount of events that occurred within a set period of time for each of the one or more subtrees:
• determining a set of subtrees with a most amount of events that occurred;
• generating embeddings for only the set of subtrees, of the one or more subtrees;
• computing a feature embedding vector for the current data object by averaging the embeddings for each of the set of subtrees;
• and
• determining a set of historically similar incidents by applying a Euclidean distance formula to the feature embedding vector and the plurality of historical embedding vectors.

A system for finding historically similar incidents in a system, the system comprising:

• a memory having processor-readable instructions stored therein;
• and
• at least one processor configured to access the memory and execute the processor-readable instructions to perform operations including:
• receiving a plurality of historical data objects corresponding to a plurality of previous events, each of the plurality of historical data objects indicating an occurrence of a previous event and being associated with a corresponding line of business data object;
• determining a plurality of historical embedding vectors for the plurality of historical data objects;
• receiving a current data object indicating an occurrence of a current incident associated with a configurable item, the current data object being associated with a line of business data object;
• determining a configurable item graph including one or more subtrees, wherein the configurable item graph is a graph of logical associations of the line of business data object and related IT operation events;
• determining an amount of events that occurred within a set period of time for each of the one or more subtrees;
• determining a set of subtrees with a most amount of events that occurred;
• generating embeddings for only the set of subtrees, of the one or more subtrees;
• computing a feature embedding vector for the current data object by averaging the embeddings for each of the set of subtrees;
• and
• determining a set of historically similar incidents by applying a Euclidean distance formula to the feature embedding vector and the plurality of historical embedding vectors.