Gambling web page recognition algorithm design based on deep residual neural network
The Internet has an important impact on people′s life and work. However, there are a large number of harmful gambling websites hidden in cyberspace, which is easy to cause losses and troubles to netizens, it can even disturb society order. Therefore, it is of great significance to study the efficien...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | zho |
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National Computer System Engineering Research Institute of China
2022-02-01
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| Series: | Dianzi Jishu Yingyong |
| Subjects: | |
| Online Access: | http://www.chinaaet.com/article/3000146226 |
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| _version_ | 1850082777316196352 |
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| author | Zhang Cong Zhang Heng Zhang Likun Zhao Tong Deng Guiying |
| author_facet | Zhang Cong Zhang Heng Zhang Likun Zhao Tong Deng Guiying |
| author_sort | Zhang Cong |
| collection | DOAJ |
| description | The Internet has an important impact on people′s life and work. However, there are a large number of harmful gambling websites hidden in cyberspace, which is easy to cause losses and troubles to netizens, it can even disturb society order. Therefore, it is of great significance to study the efficient recognition method of such websites. In this paper, the deep residual neural network is used to solve the problem of gambling web page recognition, and the algorithm GamblingRec is designed based on principle of deep residual network. The results show that the accuracy of GamblingRec reaches 95.16%, and the positive sample recall rate is 93.21%，which indicates that the method based on deep residual neural network can be applied for gambling web page recognition, and can achieve high recognition performance. |
| format | Article |
| id | doaj-art-b8c9b4b6a04c44968d7ef5efa7caa653 |
| institution | DOAJ |
| issn | 0258-7998 |
| language | zho |
| publishDate | 2022-02-01 |
| publisher | National Computer System Engineering Research Institute of China |
| record_format | Article |
| series | Dianzi Jishu Yingyong |
| spelling | doaj-art-b8c9b4b6a04c44968d7ef5efa7caa6532025-08-20T02:44:27ZzhoNational Computer System Engineering Research Institute of ChinaDianzi Jishu Yingyong0258-79982022-02-01482161810.16157/j.issn.0258-7998.2117573000146226Gambling web page recognition algorithm design based on deep residual neural networkZhang Cong0Zhang Heng1Zhang Likun2Zhao Tong3Deng Guiying4Technological Research and Development Department，China Internet Network Information Center(CNNIC)，Beijing 100190，ChinaTechnological Research and Development Department，China Internet Network Information Center(CNNIC)，Beijing 100190，ChinaTechnological Research and Development Department，China Internet Network Information Center(CNNIC)，Beijing 100190，ChinaTechnological Research and Development Department，China Internet Network Information Center(CNNIC)，Beijing 100190，ChinaTechnological Research and Development Department，China Internet Network Information Center(CNNIC)，Beijing 100190，ChinaThe Internet has an important impact on people′s life and work. However, there are a large number of harmful gambling websites hidden in cyberspace, which is easy to cause losses and troubles to netizens, it can even disturb society order. Therefore, it is of great significance to study the efficient recognition method of such websites. In this paper, the deep residual neural network is used to solve the problem of gambling web page recognition, and the algorithm GamblingRec is designed based on principle of deep residual network. The results show that the accuracy of GamblingRec reaches 95.16%, and the positive sample recall rate is 93.21%，which indicates that the method based on deep residual neural network can be applied for gambling web page recognition, and can achieve high recognition performance.http://www.chinaaet.com/article/3000146226convolutional neural networkresidual networkgamblingweb page classificationresnet |
| spellingShingle | Zhang Cong Zhang Heng Zhang Likun Zhao Tong Deng Guiying Gambling web page recognition algorithm design based on deep residual neural network Dianzi Jishu Yingyong convolutional neural network residual network gambling web page classification resnet |
| title | Gambling web page recognition algorithm design based on deep residual neural network |
| title_full | Gambling web page recognition algorithm design based on deep residual neural network |
| title_fullStr | Gambling web page recognition algorithm design based on deep residual neural network |
| title_full_unstemmed | Gambling web page recognition algorithm design based on deep residual neural network |
| title_short | Gambling web page recognition algorithm design based on deep residual neural network |
| title_sort | gambling web page recognition algorithm design based on deep residual neural network |
| topic | convolutional neural network residual network gambling web page classification resnet |
| url | http://www.chinaaet.com/article/3000146226 |
| work_keys_str_mv | AT zhangcong gamblingwebpagerecognitionalgorithmdesignbasedondeepresidualneuralnetwork AT zhangheng gamblingwebpagerecognitionalgorithmdesignbasedondeepresidualneuralnetwork AT zhanglikun gamblingwebpagerecognitionalgorithmdesignbasedondeepresidualneuralnetwork AT zhaotong gamblingwebpagerecognitionalgorithmdesignbasedondeepresidualneuralnetwork AT dengguiying gamblingwebpagerecognitionalgorithmdesignbasedondeepresidualneuralnetwork |