Abstract
In this paper, we propose a novel high-dimensional index method, the BM + -tree, to support efficient processing of similarity search queries in high-dimensional spaces. The main idea of the proposed index is to improve data partitioning efficiency in a high-dimensional space by using a rotary binary hyperplane, which further partitions a subspace and can also take advantage of the twin node concept used in the M + -tree. Compared with the key dimension concept in the M + -tree, the binary hyperplane is more effective in data filtering. High space utilization is achieved by dynamically performing data reallocation between twin nodes. In addition, a post processing step is used after index building to ensure effective filtration. Experimental results using two types of real data sets illustrate a significantly improved filtering efficiency.
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Berkmann, N., Krigel, H.-P., Schneider, R., Seeger, B.: The R*-tree: an Efficient and Robust Access Method for Points and Rectangles. In: ACM SIGMOD 1990, pp. 322–331 (1990)
Katayama, N., Satoh, S.: The SR-tree: an Index Structure for High-dimensional Nearest Neighbor Queries. In: ACM SIGMOD 1997, pp. 369–380 (1997)
White, D.A., Jain, R.: Similarity Indexing with the SS-tree. In: ICDE 1996, pp. 516–523 (1996)
Lin, K.-I., Jagadish, H.V., Faloutsos, C.: The TV-tree: An Index Structure for High-Dimensional Data. VLDB Journal 3(4), 517–542 (1994)
Uhlmann, J.K.: Satisfying General Proximity/ Similarity Queries with Metric Trees. Information Processing Letters 40, 175–179 (1991)
Zezula, P., Ciaccia, P., Rabitti, F.: M-tree: A Dynamic Index for Similarity Queries in Multimedia Databases. TR 7, HERMES ESPRIT LTR Project (1996)
Bozkaya, T., Ozsoyoglu, M.: Distance-based Indexing for High-dimensional Metric Spaces. In: ACM SIGMOD 1997, pp. 357–368 (1997)
Ciaccia, P., Patella, M., Zezula, P.: M-tree: An Efficient Access Method for Similarity Search in Metric Spaces. In: VLDB 1997, Greece (1997)
Ishikawa, M., Chen, H., Furuse, K., Yu, J.X., Ohbo, N.: MB + tree: a Dynamically Updatable Metric Index for Similarity Search. In: Lu, H., Zhou, A. (eds.) WAIM 2000. LNCS, vol. 1846, pp. 356–366. Springer, Heidelberg (2000)
Traina Jr., C., Traina, A., Seeger, B., Faloutsos, C.: Slim-trees: High Performance Metric Trees Minimizing Overlap Between Nodes. In: Zaniolo, C., Grust, T., Scholl, M.H., Lockemann, P.C. (eds.) EDBT 2000. LNCS, vol. 1777, pp. 51–65. Springer, Heidelberg (2000)
Zhou, X., Wang, G., Yu, J.X., Yu, G.: M + -tree: A New Dynamical Multidimensional Index for Metric Spaces. In: Proc. of 14th Australasian Database Conference (ADC 2003), pp. 161–168 (2003)
Wang, G., Lu, H., Yu, G., Bao, Y.: Managing Very Large Document Collections Using Semantics. Journal of Computer Science and Technology 18(3), 403–406 (2003)
Böhm, C., Berchtold, S., Keim, D.A.: High-dimensional Spaces - Index Structures for Improving the Performance of Multimedia Databases. ACM Computing Surveys (2002)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2005 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Zhou, X., Wang, G., Zhou, X., Yu, G. (2005). BM + -Tree: A Hyperplane-Based Index Method for High-Dimensional Metric Spaces. In: Zhou, L., Ooi, B.C., Meng, X. (eds) Database Systems for Advanced Applications. DASFAA 2005. Lecture Notes in Computer Science, vol 3453. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11408079_36
Download citation
DOI: https://doi.org/10.1007/11408079_36
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-25334-1
Online ISBN: 978-3-540-32005-0
eBook Packages: Computer ScienceComputer Science (R0)