Definition
The algorithmic partitioning of a knowledge graph into clusters of highly interconnected entities to enable hierarchical summarization in GraphRAG. It trades high pre-computation costs and graph complexity for the ability to answer 'global' questions across an entire dataset that standard RAG cannot address.
Distinct from vector-based clustering; it relies on graph topology (edges) rather than just embedding proximity.
"A multi-level city map where neighborhoods are defined by the density of footpaths between buildings rather than administrative borders."
Conceptual Overview
The algorithmic partitioning of a knowledge graph into clusters of highly interconnected entities to enable hierarchical summarization in GraphRAG. It trades high pre-computation costs and graph complexity for the ability to answer 'global' questions across an entire dataset that standard RAG cannot address.
Disambiguation
Distinct from vector-based clustering; it relies on graph topology (edges) rather than just embedding proximity.
Visual Analog
A multi-level city map where neighborhoods are defined by the density of footpaths between buildings rather than administrative borders.