Network Graph
Network Graph is a Cortex-side job designed to construct and analyze network structures by generating scoped subgraphs and computing quantitative scores for nodes and edges. The job processes input parameters that define analytical boundaries and scope constraints, producing isolated subgraph representations focused on specific regions of interest within a larger network. This scoped approach enables targeted analysis without requiring full-graph processing, thereby reducing computational overhead.
Subgraph Generation
The primary function of the job is to extract and isolate specific portions of the network based on defined criteria. By limiting the scope to relevant nodes and their immediate connections, the system creates manageable subgraphs that retain structural integrity while excluding irrelevant data. This isolation allows for more efficient traversal and analysis, ensuring that computational resources are allocated only to the segments of the network that require evaluation.
Scoring and Analysis
Once the subgraphs are generated, the job computes quantitative scores for both nodes and edges within the scoped area. These scores reflect the relative importance, connectivity, or other relevant metrics of the network elements. The resulting data provides a detailed view of the local network topology, facilitating deeper insights into specific clusters or pathways without the noise and complexity of the global graph structure.