HnSRTree : the SR-tree library

This is an implementation of the SR-tree [KS97]. The SR-tree is a multidimensional index structure designed for the acceleration of the nearest-neighbor search of high-dimensional points in the Euclidean space. The SR-tree is a disk-based index structure and applicable to large data sets, say, a database containing more than 10,000 points. The efficiency of the SR-tree depends on multiple factors, i.e., data distribution, dimensionality of points, etc. According to our experimental evaluation, the SR-tree provides satisfactory performance for the data sets containing more than 40,000 points in 24 to 48 dimensional space which are feature vectors (color histograms) of natural photo images. The major part of this library is written in C++. However, the interface for the C language programs is also provided.

Table of contents

• Usage of this Library

• Classes used in this Library

• Sample Commands

• Source Code Examples

• References