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

DOI

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.

Copyright

© 2012, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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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  - Proceedings of the 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  - 10.2991/citcs.2012.258
ID  - Ma2012/11
ER  -