Intelligent Optimization of New Media Advertising Content Combining Deep Neural Networks and Blockchain

New media advertising is a standard mechanism used to increase the operating income of the platform, and intelligent optimization and recommendation of advertising content is a very beneficial mechanism for new media platforms. In this paper, a multi-task deep learning neural network model is used to realize the intelligent optimization of new media advertisement content, improve the model’s effect on advertisement content optimization through the attention mechanism in the model, and further improve the performance of the model by using the loss function. The model is then combined with blockchain technology to establish an intelligent optimization and recommendation system for new media advertisement content, which achieves personalized and accurate new media advertisement content recommendation. It is verified that the multi-task deep learning neural network model proposed in this paper achieves good results in the intelligent optimization of new media advertising content, and the system performance meets the functional and non-functional load requirements. In addition, under the application of intelligent content optimization and recommendation system, most of the new media users’ advertisement browsing duration is higher than 50 s. Compared with the traditional advertisement recommendation system, the advertisement content intelligent optimization system proposed in this study has the advantages of strong purpose, strong targeting, fast effect, low cost, etc., and it has obvious advantages in enhancing the user’s interest in the advertisement content.