Study on effective detection method for specific data of large database

DOI

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.

Copyright

© 2015, 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  - Jin-feng Li
PY  - 2015/04
DA  - 2015/04
TI  - Study on effective detection method for specific data of large 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-15.2015.318
DO  - 10.2991/amcce-15.2015.318
ID  - Li2015/04
ER  -