Query size estimation using clustering techniques

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

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)

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 languageEnglish
Title of host publicationProceedings - International Conference on Tools with Artificial Intelligence, ICTAI
Pages185-189
Number of pages5
Volume2005
DOIs
StatePublished - Dec 1 2005
EventICTAI 2005: 17th IEEE International Conference on Tools with Artificial Intelligence, ICTAI'05 - Hong Kong, China
Duration: Nov 14 2005Nov 16 2005

Other

OtherICTAI 2005: 17th IEEE International Conference on Tools with Artificial Intelligence, ICTAI'05
CountryChina
CityHong Kong
Period11/14/0511/16/05

Fingerprint

Cluster analysis

ASJC Scopus subject areas

  • Engineering(all)

Cite this

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

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

Proceedings - International Conference on Tools with Artificial Intelligence, ICTAI. Vol. 2005 2005. p. 185-189 1562934.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Su, X, Kubat, M, Tapia, MA & Hu, C 2005, Query size estimation using clustering techniques. in Proceedings - International Conference on Tools with Artificial Intelligence, ICTAI. vol. 2005, 1562934, 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
Su X, Kubat M, Tapia MA, Hu C. Query size estimation using clustering techniques. In Proceedings - International Conference on Tools with Artificial Intelligence, ICTAI. Vol. 2005. 2005. p. 185-189. 1562934 https://doi.org/10.1109/ICTAI.2005.105
Su, Xiaoyuan ; Kubat, Miroslav ; Tapia, Moiez A. ; Hu, Chao. / Query size estimation using clustering techniques. Proceedings - International Conference on Tools with Artificial Intelligence, ICTAI. Vol. 2005 2005. pp. 185-189
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