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

Study on effective detection method for specific data of large database

Authors
Jin-feng Li
Corresponding Author
Jin-feng Li
Available Online April 2015.
DOI
https://doi.org/10.2991/amcce-15.2015.318How to use a DOI?
Keywords
data detection; database; mapping;
Abstract
in the process of detecting specific data of large database, when the traditional detection method is utilized for detecting specific data, it is vulnerable for interference of mass information, which makes the specific data detection process time-consuming, and of low efficiency. For this, an effective detection method for specific data of large database is proposed based on improved TFIDF algorithm, the information entropy between the specific data features of large database and the information entropy within the features are viewed as the weighted factor for specific data detection, nonlinear mapping ability of neural network is adopted to achieve calculation of weights and fuzzification of TFIDF algorithm, thus solving the detection problem for specific data of large database. The experimental results show that, improved algorithm for effective detection of specific data in large databases, can effectively reduce time consumed for detection of specific data, ensure the detection quality of specific data to meet customer requirements.
Open Access
This is an open access article distributed under the CC BY-NC license.

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Proceedings
2015 International Conference on Automation, Mechanical Control and Computational Engineering
Part of series
Advances in Intelligent Systems Research
Publication Date
April 2015
ISBN
978-94-62520-64-6
ISSN
1951-6851
DOI
https://doi.org/10.2991/amcce-15.2015.318How 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  - Jin-feng Li
PY  - 2015/04
DA  - 2015/04
TI  - Study on effective detection method for specific data of large database
BT  - 2015 International Conference on Automation, Mechanical Control and Computational Engineering
PB  - Atlantis Press
SN  - 1951-6851
UR  - https://doi.org/10.2991/amcce-15.2015.318
DO  - https://doi.org/10.2991/amcce-15.2015.318
ID  - Li2015/04
ER  -