基于多模态数据的博彩网站检测识别模型

Detection and Identification Model of Gambling Websites Based on Multi-Modal Data

文章提出一种基于多模态数据的博彩网站检测识别模型,首先构建基于文本特征的Bert特征提取模型和基于图像特征的VGG19特征提取模型;然后通过特征融合及改变损失函数的方式提升博彩网站检测识别分类效果。在自建的正负样本1:5、1:10和1:20的数据集上对模型进行验证,实验结果表明,正负样本不均衡情况越明显,该模型的优势越明显,越能高效检测识别博彩网站。

This paper proposed a gambling website detection and recognition model based on multimodal data.Firstly,it constructed a Bert feature extraction model based on text features and a VGG19 feature extraction model based on image features;secondly,the method improved the classification effect of gambling website detection and recognition based on feature fusion and changing the loss function;lastly,this paper validated the method on self-constructed positive and negative samples of 1:5,1:10,and 1:20 datasets.The experimental results indicate that the more obvious the imbalance of positive and negative samples is,the more obvious the advantage of the proposed method is,and it can detect and recognise gambling websites well.