Image Recognition and Product Recommendation Algorithms Based on Deep Learning
Weiqiang Diwu, Rui Zhang, Lin Feng, Qing Mu · 2024
In response to the poor performance of traditional e-commerce systems in image recognition and product recommendation, this paper uses deep learning as the basis and convolutional neural network algorithms to study the image recognition and product recommendation algorithms in e-commerce systems. Firstly, the basic knowledge and citation principles of convolutional neural network algorithms were introduced. Then a detailed description of the model construction process based on convolutional neural networks was provided, and the model was trained. Finally, through experimental comparison, the performance of the model designed in this article was explored. The experimental results showed that the accuracy and recall of the model in image recognition in e-commerce systems are between 95.2%-96.5% and 91%-85%, respectively. At the same time, users show a very satisfactory attitude towards product recomme$n$d\\\\\\\\datio$n$results. Therefore, the model designed in this article has the effect of improving the performance of image recognition and product recommendation algorithms.