Proceedings of the 2012 National Conference on Information Technology and Computer Science

Pivot Selection Methods Based on Covariance and Correlation for Metric-space Indexing

Authors
Kewei Ma, Yuanjun Liu, Honglong Xu, Pang Yue, Fuli Lei, Sheng Liu, Rui Mao, Jiaxin Han
Corresponding Author
Kewei Ma
Available Online November 2012.
DOI
https://doi.org/10.2991/citcs.2012.258How to use a DOI?
Keywords
similarity query; metric-space indexing; pivot space model; pivot selection;
Abstract
Metric-space indexing is a general method for similarity queries of complex data. The quality of the index tree is a critical factor of the query performance. Bulkloading a metricspace indexing tree can be represented by two recursive steps, pivot selection and data partition, while pivot selection dominants the quality of the index tree. Two heuristics, based on covariance and correlation, for pivot selection are proposed. Empirical results show that their performance is superior or comparable to existing methods.
Open Access
This is an open access article distributed under the CC BY-NC license.

Download article (PDF)

Proceedings
2012 National Conference on Information Technology and Computer Science
Part of series
Advances in Intelligent Systems Research
Publication Date
November 2012
ISBN
978-94-91216-39-8
ISSN
1951-6851
DOI
https://doi.org/10.2991/citcs.2012.258How to use a DOI?
Open Access
This is an open access article distributed under the CC BY-NC license.

Cite this article

TY  - CONF
AU  - Kewei Ma
AU  - Yuanjun Liu
AU  - Honglong Xu
AU  - Pang Yue
AU  - Fuli Lei
AU  - Sheng Liu
AU  - Rui Mao
AU  - Jiaxin Han
PY  - 2012/11
DA  - 2012/11
TI  - Pivot Selection Methods Based on Covariance and Correlation for Metric-space Indexing
BT  - 2012 National Conference on Information Technology and Computer Science
PB  - Atlantis Press
SP  - 1015
EP  - 1020
SN  - 1951-6851
UR  - https://doi.org/10.2991/citcs.2012.258
DO  - https://doi.org/10.2991/citcs.2012.258
ID  - Ma2012/11
ER  -