(1+ε)-approximate nearest neighbor search

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(1+ε)-approximate nearest neighbor search is a special case of the nearest neighbor search problem. The solution to the (1+ε)-approximate nearest neighbor search is a point or multiple points within distance (1+ε) R from a query point, where R is the distance between the query point and its true nearest neighbor.[1]

Reasons to approximate nearest neighbor search include the space and time costs of exact solutions in high-dimensional spaces (see curse of dimensionality) and that in some domains, finding an approximate nearest neighbor is an acceptable solution.

Approaches for solving (1+ε)-approximate nearest neighbor search include kd-trees, Locality Sensitive Hashing and brute force search.


References[edit]

  1. ^ Ma, Zongmin. Artificial Intelligence for Maximizing Content Based Image Retrieval. IGI Global. p. 135. ISBN 9781605661759.