Proceedings of the 2015 International Conference on Automation, Mechanical Control and Computational Engineering

Optimization for massive data query method in database

Authors
Xiao dong Xie, Jinping Zou, Xi Huang
Corresponding Author
Xiao dong Xie
Available Online April 2015.
DOI
https://doi.org/10.2991/amcce-15.2015.272How to use a DOI?
Keywords
Database; inquiry; correlation clustering;
Abstract
The massive data query methods in database is studied to improve accuracy of query. In the process of data querying in the database, once the data volume is overflow and thetype of data becomes complex, the query requires a lot of restrictions, resulting in time-consuming and low query accuracy rate for data query. To this end, optimization for massive data query method in database based oncorrelation clustering algorithm is proposed. Correlation clustering is processed to all the data in the database to obtain the correlation between different data. Query for the specified categories of data to achieve query optimization of massive data in database. Experimental results show that the proposed method for mass data query in database can improve the accuracy and efficiency of the query, and reduce time for querying.
Open Access
This is an open access article distributed under the CC BY-NC license.

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Cite this article

TY  - CONF
AU  - Xiao dong Xie
AU  - Jinping Zou
AU  - Xi Huang
PY  - 2015/04
DA  - 2015/04
TI  - Optimization for massive data query method in database
BT  - Proceedings of the 2015 International Conference on Automation, Mechanical Control and Computational Engineering
PB  - Atlantis Press
SN  - 1951-6851
UR  - https://doi.org/10.2991/amcce-15.2015.272
DO  - https://doi.org/10.2991/amcce-15.2015.272
ID  - Xie2015/04
ER  -