In this paper we focus on the problem of continuously monitoring the set of Reverse k-Nearest Neighbors (RkNNs) of a query object in a moving object database using a client server...
Abstract. We consider approximate nearest neighbor searching in metric spaces of constant doubling dimension. More formally, we are given a set S of n points and an error bound &g...
Sunil Arya, David M. Mount, Antoine Vigneron, Jian...
We present a new Bi-level LSH algorithm to perform approximate k-nearest neighbor search in high dimensional spaces. Our formulation is based on a two-level scheme. In the first ...
We consider approaches for exact similarity search in a high dimensional space of correlated features representing image datasets, based on principles of clustering and vector qua...
Handling large amounts of data, such as large image databases, requires the use of approximate nearest neighbor search techniques. Recently, Hamming embedding methods such as spec...