Please use this identifier to cite or link to this item: http://hdl.handle.net/1783.1/178

Efficient historical R-trees

Authors Tao, Y.
Papadias, D.
Issue Date 2001
Source Proceedings of the International Conference on Scientific and Statistical Database Management, SSDBM, 2001, p. 223-232
Summary The Historical R-tree is a spatio-temporal access method aimed at the retrieval of window queries in the past. The concept behind the method is to keep an R-tree for each timestamp in history, but allow consecutive trees to share branches when the underlying objects do not change. New branches are only created to accommodate updates from the previous timestamp. Although existing implementations of HR-trees process timestamp (window) queries very efficiently, they are hardly applicable in practice due to excessive space requirements and poor interval query performance. This paper addresses these problems by proposing the HR+-tree, which occupies a small fraction of the space required for the corresponding HR-tree (for typical conditions about 20%), while improving interval query performance several times. Our claims are supported by extensive experimental evaluation.
Subjects
ISBN 0-7695-1218-6
Rights © 2001 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in orther works must be obtained from the IEEE. This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therin are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.
Language English
Format Conference paper
Access View full-text via Scopus
View full-text via Web of Science
Find@HKUST
Files in this item:
File Description Size Format
ssdbm01.pdf 140464 B Adobe PDF