HNSW
HNSW, or Hierarchical Navigable Small World graphs, is a graph-based algorithm for approximate nearest neighbor search in high-dimensional vector spaces. It builds a multi-layer, navigable graph where each node represents a data point and edges connect neighboring points. The graph exploits small-world properties to enable fast search for approximate nearest neighbors.
The construction process assigns each data point a random level, with higher levels containing fewer connections.
Key parameters control performance and resource use. M is the maximum number of connections per node per
Time complexity is data-dependent, but searches typically scale sublinearly with data size and often exhibit near-logarithmic
HNSW has become a widely used technique for approximate nearest neighbor search. It is implemented in several