Design And Development Of Commercial AI Marketing System Based On Deep Learning

With the development of science and technology,enterprise informatization and intelligence have become the current development trend.Large shopping malls have built corresponding information and intelligent integrated marketing systems,applying artificial intelligence,machine learning,and big data to modern commercial marketing systems.Aiming at the status quo of the marketing management model of large shopping malls,this paper studies and designs a solution for the commercial marketing AI system,which mainly includes frontend POS,middle-station management and AI intelligence.Through distributed data management,business logic analysis and intelligent decision-making in the middle office,it overcomes the shortcomings of the original system marketing management,improves the reliability and flexibility of the system,and enhances the system’s comprehensive marketing management capabilities.This article uses deep learning technology to analyze and model the dynamic characteristics and overall trends of commercial marketing,and focuses on the analysis and discussion of the network structure of LSTM.Aiming at the characteristics of commercial marketing,a method of data segmentation and backward difference is designed for model training and learning,which better handles the correlation between dynamic data and improves the prediction effect of the model.In order to further optimize the network model,a NP-LSTM model was researched and designed,and the performance evaluation and structure optimization of the basic LSTM model were performed,and good results were achieved.In order to make up for the problem of incomplete model training and learning information after data segmentation,a mixed prediction model of long and short interval data based on NP-LSTM was designed,and the corresponding test and analysis were performed to achieve the expected effect.In the aspect of system design,UML is used to describe its main functions and business logic,the data relationship of the system is established through the ER diagram,and the system function modules are designed and realized through the sequence diagram.Designed and encapsulated the AI model class,realized the interaction between the background modeling and the system,and provided an AI predictive analysis support for the system.The overall architecture of the system is designed and implemented based on SSM and My SQL.It uses multi-threading technology to realize the interaction with the big back-end data,providing managers with a dynamic predictive business intelligence service.