The problem of finding clusters in data is challenging when clusters are of widely differing sizes, densities and shapes, and when the data contains large amounts of noise and out...
The reverse k-nearest neighbor (RkNN) problem, i.e. finding all objects in a data set the k-nearest neighbors of which include a specified query object, is a generalization of the...
We researched to try to find a way to reduce the cost of nearest neighbor searches in metric spaces. Many similarity search indexes recursively divide a region into subregions by u...
This is an algorithm for finding neighbors for point objects that can freely move and have no predefined position. The query sphere consists of a center location and a given radiu...
This paper addresses the challenging problem of rapidly searching and matching high-dimensional features for the applications of multimedia database retrieval and pattern recognit...