Adaptive quantization of the high-dimensional data for efficient KNN processing

Cui, B, Hu, J, Shen, HT and Yu, C (2004). Adaptive quantization of the high-dimensional data for efficient KNN processing. In: YoonJoon Lee, Kyu-Young Whang, Jianzhong Li and Doheon Lee, Database Systems for Advanced Applications: 9th International Conference, DASFAA 2004 Jeju Island, Korea, March 17-19, 2004 Proceedings. 9th International Conference on Database Systems for Advanced Applications (DASFAA 2004), Jeju Island, Korea, (302-313). 17-19 March 2004.


Author Cui, B
Hu, J
Shen, HT
Yu, C
Title of paper Adaptive quantization of the high-dimensional data for efficient KNN processing
Conference name 9th International Conference on Database Systems for Advanced Applications (DASFAA 2004)
Conference location Jeju Island, Korea
Conference dates 17-19 March 2004
Proceedings title Database Systems for Advanced Applications: 9th International Conference, DASFAA 2004 Jeju Island, Korea, March 17-19, 2004 Proceedings   Check publisher's open access policy
Journal name Database Systems for Advanced Applications   Check publisher's open access policy
Place of Publication New York, U.S.A.
Publisher Springer
Publication Year 2004
Sub-type Fully published paper
DOI 10.1007/978-3-540-24571-1_27
ISBN 9783540210474
3540210474
ISSN 0302-9743
1611-3349
Editor YoonJoon Lee
Kyu-Young Whang
Jianzhong Li
Doheon Lee
Volume 2973
Start page 302
End page 313
Total pages 12
Language eng
Formatted Abstract/Summary In this paper, we present a novel index structure, called the SA-tree, to speed up processing of high-dimensional K-nearest neighbor (KNN) queries. The SA-tree employs data clustering and compression, i.e. utilizes the characteristics of each cluster to adaptively compress feature vectors into bit-strings. Hence our proposed mechanism can reduce the disk I/O and computational cost significantly, and adapt to different data distributions. We also develop efficient KNN search algorithms using MinMax Pruning and Partial MinDist Pruning methods. We conducted extensive experiments to evaluate the SA-tree and the results show that our approaches provide superior performance.
© Springer-Verlag 2004.
Keyword Computer science
KNN processing
Q-Index Code E1
Q-Index Status Provisional Code
Institutional Status Unknown

 
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Created: Fri, 25 Jan 2008, 16:08:09 EST