Vectorburen

Vectorburen is a concept in computational geometry and data indexing describing a method to organize large sets of vectors by local neighborhoods. The term fuses vector with the Dutch word buren, meaning neighbors, reflecting its emphasis on locality and proximity in vector spaces.

Construction involves mapping a set of vectors into neighborhoods such that each vector relates to nearby vectors within a given radius or number of neighbors. Implementations may use graphs where edges connect close vectors or hierarchical indices that preserve locality, often employing approximate nearest-neighbor techniques.

Operations include insertion, deletion, and updating of vectors, as well as queries for nearest neighbors or all vectors within a radius. The aim is to maintain stable neighborhood relations to reduce search space and improve performance, with build times varying by method and query times typically sublinear under favorable conditions.

Applications span graphics and physics simulations, machine learning for fast similarity search, robotics for spatial awareness and planning, and high-dimensional data analysis in embedding spaces and recommender systems where locality is important.

Relation to existing methods: vectorburen share goals with k-d trees, ball trees, and locality-sensitive hashing, but emphasize dynamic neighborhood maintenance. Ongoing work focuses on robustness to high dimensionality and streaming updates, and integration with vector quantization.