Query size estimation using clustering techniques

Xiaoyuan Su; Miroslav Kubat; Moiez A. Tapia; Chao Hu

doi:10.1109/ICTAI.2005.105

Query size estimation using clustering techniques

Xiaoyuan Su, Miroslav Kubat, Moiez A. Tapia, Chao Hu

Electrical and Computer Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

4 Scopus citations

Abstract

For managing the performance of database management systems, we need to be able to estimate the size of queries. Query Size Estimation (QSE) is difficult if the queries are associated with more than one attribute. Here, we propose, and experimentally evaluate, a novel technique that builds on cluster analysis. Empirical results indicate that, in particular, density-based clustering QSE techniques are beneficial for medium and large sized databases where they compare favourably with partitioning clustering QSE ones such as k-means. This is observed especially in the case of noisy and dense datasets.

Original language	English (US)
Title of host publication	ICTAI 2005
Subtitle of host publication	17th IEEE International Conference on Tools with Artificial Intelligence, ICTAI'05
Pages	185-189
Number of pages	5
DOIs	https://doi.org/10.1109/ICTAI.2005.105
State	Published - Dec 1 2005
Event	ICTAI 2005: 17th IEEE International Conference on Tools with Artificial Intelligence, ICTAI'05 - Hong Kong, China Duration: Nov 14 2005 → Nov 16 2005

Publication series

Name	Proceedings - International Conference on Tools with Artificial Intelligence, ICTAI
Volume	2005
ISSN (Print)	1082-3409

Other

Other	ICTAI 2005: 17th IEEE International Conference on Tools with Artificial Intelligence, ICTAI'05
Country	China
City	Hong Kong
Period	11/14/05 → 11/16/05

ASJC Scopus subject areas

Engineering(all)

Access to Document

10.1109/ICTAI.2005.105

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Su, X., Kubat, M., Tapia, M. A., & Hu, C. (2005). Query size estimation using clustering techniques. In ICTAI 2005: 17th IEEE International Conference on Tools with Artificial Intelligence, ICTAI'05 (pp. 185-189). [1562934] (Proceedings - International Conference on Tools with Artificial Intelligence, ICTAI; Vol. 2005). https://doi.org/10.1109/ICTAI.2005.105

Query size estimation using clustering techniques. / Su, Xiaoyuan; Kubat, Miroslav; Tapia, Moiez A.; Hu, Chao.

ICTAI 2005: 17th IEEE International Conference on Tools with Artificial Intelligence, ICTAI'05. 2005. p. 185-189 1562934 (Proceedings - International Conference on Tools with Artificial Intelligence, ICTAI; Vol. 2005).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Su, X, Kubat, M, Tapia, MA & Hu, C 2005, Query size estimation using clustering techniques. in ICTAI 2005: 17th IEEE International Conference on Tools with Artificial Intelligence, ICTAI'05., 1562934, Proceedings - International Conference on Tools with Artificial Intelligence, ICTAI, vol. 2005, pp. 185-189, ICTAI 2005: 17th IEEE International Conference on Tools with Artificial Intelligence, ICTAI'05, Hong Kong, China, 11/14/05. https://doi.org/10.1109/ICTAI.2005.105

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