Pivot selection techniques for proximity searching in metric spaces
Pattern Recognition Letters
A Data Structure and an Algorithm for the Nearest Point Problem
IEEE Transactions on Software Engineering
Selecting vantage objects for similarity indexing
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
Similarity grid for searching in metric spaces
DELOS'04 Proceedings of the 6th Thematic conference on Peer-to-Peer, Grid, and Service-Orientation in Digital Library Architectures
Hi-index | 0.00 |
In general metric spaces, one of the most widely used indexing techniques is the partitioning of the objects using pivot elements. The efficiency of partitioning depends on the selection of the appropriate set of pivot elements. In the paper, some methods are presented to improve the quality of the partitioning in GHT structure from the viewpoint of balancing factor. The main goal of the investigation is to determine the conditions when costs of distance computations can be reduced. We show with different tests that the proposed methods work better than the usual random and incremental pivot search methods.