Application Research Of Intelligent Recommendation Technology In HS Agricultural E-Commerce Platform

With the continuous development of e-commerce and the gradual popularization of mobile internet,e-commerce systems provide more and more recommendation services for platforms and users,and the types of recommendation services are becoming increasingly complex.How to accurately recommend massive agricultural product data has become a key research point in the field of agricultural e-commerce.This article presents the design of the HS(Hot Shop: Popular Store)agricultural ecommerce platform using intelligent recommendation technology,and completes the development and implementation of the HS agricultural e-commerce platform with intelligent recommendation technology.Firstly,based on reviewing the current status and trends of e-commerce platforms both domestically and internationally,the application of intelligent recommendation technology in e-commerce platforms was analyzed,and a HS agricultural e-commerce platform solution with intelligent recommendation technology was proposed.Based on the operational characteristics of the HS agricultural e-commerce platform,starting from the user and management sides,combined with the characteristics of fresh activity,regional,seasonal,and decentralized agricultural products,a demand analysis was conducted for intelligent recommendation services.Secondly,the preliminary design,detailed design,data interaction design,system technology selection design and database design of the HS agricultural e-commerce platform were carried out.At the same time,the technology of intelligent recommendation of agricultural products using user based collaborative filtering algorithm and hybrid recommendation algorithm integrating multi-attribute recommendation method is proposed.Among them,user based collaborative filtering algorithm is used for primary intelligent recommendation,and integrated multiattribute recommendation method is used for secondary intelligent recommendation.The collaborative filtering algorithm based on personalized features is used to calculate the user similarity and obtain the agricultural products that users are interested in.Form a recommended agricultural product pool and store it in the backend database;Utilizing the agricultural product pool data from one intelligent recommendation and integrating multiple attributes for secondary intelligent recommendation calculation,generate and output the final agricultural product recommendation list for display on the user’s mobile end.The intelligent recommendation algorithm was applied through examples,and the experimental results showed the accuracy and effectiveness of the primary intelligent recommendation technology and the secondary intelligent recommendation technology.Finally,using Alibaba Cloud services,using technologies such as MySQL,Redis,Elasticsearch,SpringBoot,and Spring Cloud,and using Java,Objective-C,and VUE development languages,the management and mobile end were built.Recommendation algorithms were written using Java,Python,stored procedures,and other technologies,achieving an HS agricultural e-commerce platform with intelligent recommendation technology.The application of intelligent recommendation technology in the HS agricultural e-commerce platform has improved the accuracy of agricultural product recommendation and improved the operational efficiency of the platform,achieving the expected results.