7. Summary
The R-tree structure has been proposed in 1984 by Guttman to efficiently manipulate rectangles in VLSI chip design. This work influenced many researchers towards the application of the structure for other purposes as well. During the last twenty years many variations of the original structure have been proposed to either improve the performance of spatial queries, or to enable the application of the structure to different contexts. Among the most widely accepted R-tree variants are the R+-tree, the R-tree and the Hilbert R-tree. If the dataset is known in advance, more efficient (static) structures can be constructed resulting in considerable performance improvement. The query processing capabilities of the structure have been thoroughly studied in the literature, resulting in efficient algorithms for spatial and spatiotemporal query processing. Recently, the structure has been adopted for query processing purposes in emerging application domains such as OLAP, data warehouses and data mining.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
8. Further Reading
S. Berchtold, D. Keim and H.-P. Kriegel: “The X-tree: an Index Structure for High-Dimensional Data”, Proceedings of the 22nd International Conference on Very Large Databases (VLDB’96), pp.28–39, Bombay, India, 1996.
V. Gaede and 0. Guenther: “Multidimensional Access Methods”, ACM Computing Surveys, Vol.30, No.2, pp.170–231, 1998.
N. Katayama and S. Satoh: “The SR-tree: an Index Structure for High-Dimensional NearestNeighbor Queries”, Proceedings of the ACM International Conference on Management of Data (SIGMOD’97), pp.369–380, Tucson, AZ, 1997.
K. Lin, H.V. Jagadish and C. Faloutsos: “The TV-tree: an Index Structure for High Dimensional Data”, The VLDB Journal, Vol.3, No.4, pp.517–542, 1995.
Y. Manolopoulos, Y. Theodoridis and V. J. Tsotras: “Advanced Database Indexing”, Kluwer Academic Publishers, 1999.
Y. Manolopoulos, A. Nanopoulos, A.N. Papadopoulos and Y. Theodoridis: “R-trees Have Grown Everywhere”, Technical Report, 2003. Available at http://www.rtreeportal.org/pubs/MNPT03.pdf
Y. Sakurai, M. Yoshikawa, A. Uemura and H. Kojima: “The A-tree: an Index Structure for High-Dimensional Spaces Using Relative Approximation”, Proceedings of the 26th International Conference on Very Large Databases (VLDB’00), pp.516–526, Cairo, Egypt, 2000.
D. White and R. Jain: “Similarity Indexing with the SS-tree”, Proceedings of the 12th IEEE International Conference on Data Engineering (ICDE’96), pp.516–523, New Orleans, LO, 1996.
Rights and permissions
Copyright information
© 2005 Springer Science+Business Media, Inc.
About this chapter
Cite this chapter
(2005). The R-Tree and Variations. In: Nearest Neighbor Search. Series in Computer Science. Springer, Boston, MA . https://doi.org/10.1007/0-387-27544-4_2
Download citation
DOI: https://doi.org/10.1007/0-387-27544-4_2
Publisher Name: Springer, Boston, MA
Print ISBN: 978-0-387-22963-8
Online ISBN: 978-0-387-27544-4
eBook Packages: Computer ScienceComputer Science (R0)