基于深度残差神经网络的博彩网页识别算法设计

Gambling web page recognition algorithm design based on deep residual neural network

互联网对人民群众的生活和工作产生了重要影响,然而网络空间中隐藏着大量有害的博彩网站或赌博网站,很容易给网民造成损失和困扰,甚至可能扰乱社会秩序,因而研究对此类网站进行高效识别的方法具有重要意义。提出利用深度残差神经网络解决博彩类网页识别问题,基于深度残差网络的原理设计了算法GamblingRec。经验证,算法准确率达到了95.16%,正样本召回率为93.21%,表明基于深度残差神经网络的方法能够用于博彩类网页识别,并能达到较高的识别性能。

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.