Proceedings of the 2013 International Conference on Advanced ICT and Education

Classification of Deep Web Data Sources Based on Feature Weight Estimate

Authors
Xiaoqing ZHOU, Jiaxiu SUN, Shubin Wang
Corresponding Author
Xiaoqing ZHOU
Available Online August 2013.
DOI
https://doi.org/10.2991/icaicte.2013.44How to use a DOI?
Keywords
deep web; web database; feature extraction; feature valuation; Naive Bayes classifier
Abstract
The traditional search engine is unable to correct search for the magnanimous information in Deep Web hides. The Web database's classification is the key step which integrates with the Web database classification and retrieves. This article has proposed one kind of classification based on machine learning's web database. The experiment has indicated that after this taxonomic approach undergoes few sample training, it can achieve the very good classified effect, and along with training sample's increase, this classifier's performance maintains stable and the rate of accuracy and the recalling rate fluctuate in the very small scope.
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This is an open access article distributed under the CC BY-NC license.

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Proceedings
2013 International Conference on Advanced ICT and Education (ICAICTE-13)
Part of series
Advances in Intelligent Systems Research
Publication Date
August 2013
ISBN
978-90786-77-79-6
ISSN
1951-6851
DOI
https://doi.org/10.2991/icaicte.2013.44How 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  - Xiaoqing ZHOU
AU  - Jiaxiu SUN
AU  - Shubin Wang
PY  - 2013/08
DA  - 2013/08
TI  - Classification of Deep Web Data Sources Based on Feature Weight Estimate
BT  - 2013 International Conference on Advanced ICT and Education (ICAICTE-13)
PB  - Atlantis Press
SP  - 207
EP  - 210
SN  - 1951-6851
UR  - https://doi.org/10.2991/icaicte.2013.44
DO  - https://doi.org/10.2991/icaicte.2013.44
ID  - ZHOU2013/08
ER  -