Discovering representative composite CI patterns in an it system

A system for discovering representative composite configuration item (CI) patterns for an Information Technology (IT) system that includes a plurality of configuration items (CIs), the system comprising:

• a processor to:
• for a graph representing the IT system, prune attributes of a plurality of CI nodes, wherein each CI node of the graph represents a respective one of the CIs of the IT system;
• data mine the plurality of CI nodes of the graph representing the IT system to extract composite CI patterns;
• determine a plurality of similarity measures for the composite CI patterns, each similarity measure measuring a similarity between a unique pair of composite CI patterns, wherein each similarity measure is a product of multiplying a Jaccard coefficient times a diffusion kernel similarity value;
• cluster a first plurality of the composite CI patterns into a cluster based on the plurality of similarity measures for the composite CI patterns, wherein each composite CI pattern included in the cluster comprises multiple CI nodes;
• extract a single representative composite CI pattern from the cluster to represent the first plurality of composite CI patterns in the cluster;
• a communication interface to interface between the processor and the IT system;
• and
• an output device to output the single representative composite CI pattern for the cluster.

A non-transitory computer readable medium having stored thereon instructions for discovering representative composite configuration item (CI) patterns for an Information Technology (IT) system that includes a plurality of configuration items (CIs), which when executed by a processor cause the processor to:

• for a graph representing the IT system, prune attributes of a plurality of CI nodes, wherein each CI node of the graph represents a respective one of the CIs of the IT system;
• data mine the plurality of CI nodes of the graph representing the IT system to extract composite CI patterns;
• determine a plurality of similarity measures for the composite CI patterns, each similarity measure measuring a similarity between a unique pair of composite CI patterns, wherein each similarity measure is calculated by multiplying a Jaccard coefficient times a diffusion kernel similarity value;
• cluster a first plurality of the composite CI patterns into a cluster based on the plurality of similarity measures for the composite CI patterns, wherein each composite CI pattern included in the cluster comprises multiple CI nodes;
• extract a single representative composite CI pattern from the cluster to represent the first plurality of composite CI patterns in the cluster;
• using an output device, output the single representative composite CI pattern for the cluster.