TY - JOUR
AU - Edgar Chávez
AU - Verónica Ludueña
AU - Nora Reyes
AU - Fernando Kasián
PY - 2018/04/25
Y2 - 2019/01/17
TI - All Near Neighbor GraphWithout Searching
JF - Journal of Computer Science and Technology
JA - JCS&T
VL - 18
IS - 01
SE - Original Articles
DO - 10.24215/16666038.18.e07
UR - http://journal.info.unlp.edu.ar/JCST/article/view/695
AB - Given a collection of n objects equipped with a distance function d(·, ·), the Nearest Neighbor Graph (NNG) consists in finding the nearest neighbor of each object in the collection. Without an index the total cost of NNG is quadratic. Using an index the cost would be sub-quadratic if the search for individual items is sublinear. Unfortunately, due to the so called curse of dimensionality the indexed and the brute force methods are almost equally inefficient. In this paper we present an efficient algorithm to build the Near Neighbor Graph (nNG), that is an approximation of NNG, using only the index construction, without actually searching for objects.
ER -