Research on the impact of artificial intelligence-based e-commerce personalization on traditional accounting methods

Abstract

With the development of artificial intelligence technology in various fields, the traditional accounting method is no longer applicable to the personalized development of e-commerce industry; Therefore, it is essential to improve the accounting method and construct a personalized recommendation model for e-commerce. Based on this background, this study firstly reconstructs the steps of accounting element recognition in the traditional accounting system and constructs an automated accounting recognition mechanism using BP neural network algorithm, aiming to improve the accuracy and efficiency of accounting element recognition; Secondly, a personalized e-commerce recommendation model based on multiple intelligence is built, which uses intelligent Q-learning algorithm to optimize the recommendation module, aiming to improve the accuracy of personalized recommendation. By comparing the performance of different accounting models under different personalized e-commerce systems, the accounting model proposed in this paper can predict the accounting entries well under the three-layer BP neural network, and the error between the maximum predicted value and the actual value is 0.23%. The recommendation model proposed in the study outperforms the traditional recommendation model and the recommendation model under collaborative filtering algorithm in predicting customers' personal preferences, whose predicted value is closer to the real situation. In summary, both the accounting method and the personalized recommendation model for e-commerce proposed in this study can achieve better application results, thus providing a new idea for the development of the e-commerce industry.