Design And Implementation Of Mail Management System Based On Convolutional Neural Network

With the development of information technology,e-mail services have rapidly become popular among network users due to their cost-effective communication advantages,and have become an important tool for people to exchange information.However,the convenience of e-mail also brings about the problem of spam flooding.Spam not only occupies Internet resources,but also causes serious problems for users and enterprises,consumes time and effort,and causes economic losses.Therefore,the spam filtering technology has become more and more important and the use of a mail management system with spam filtering functions has become a demand of people.According to the characteristics and applicable scenarios of the current main spam filtering technology,the paper constructs a Chinese spam filtering model based on the convolutional neural network algorithm.Before the model construction,the thesis carried out text preprocessing and word2vec word vector generation on the email content,and then completed the basic model construction based on the structure and algorithm principle of the convolutional neural network.In order to improve the efficiency and accuracy of the model,according to the structural characteristics of the convolutional neural network algorithm,the paper proposes optimization methods for Dropout and L2 regularization.According to the text characteristics of normal emails and spam emails,the paper proposes an improved method of variable-step convolution and weighted pooling.Then through experiments,observe the impact of optimization and improvement programs on the model.The experimental results show that the optimized and improved Chinese spam filtering algorithm,compared with the unoptimized and unimproved Chinese spam filtering algorithm,has an accuracy rate of 4.43%,a precision rate of 4.91%,a recall rate of 6.10%,and an F1 value of 5.50%.And the model's indicators are improving faster than before the algorithm was improved.It shows that with the optimized method of Dropout and L2 regularization,and the method of variable-step convolution and weighted pooling,it has achieved certain effect in improving the classification efficiency and accuracy of the model.After improving the Chinese spam filtering algorithm of the convolutional neural network,the paper uses the JavaMail framework and vue-cli scaffolding to design and implement the mail management system,and applies the Chinese spam filtering model based on the improved algorithm to the system.It makes the mail management system provide users with the main functions of logging in,sending and receiving emails,saving drafts,viewing inboxes,outboxes,draft boxes and trash bins,managing address books,filtering spam and other functions.