Research And Implementation Of Agricultural Products Recommendation Model And E-Commerce System

In recent years,with the rise of the Internet,various e-commerce platforms have mushroomed.Agriculture is an important investment and construction field in China.The online sale of agricultural products solves the problem of sluggish sales of agricultural products.However,with the continuous development of the e-commerce platform for agricultural products,it is becoming more and more time-consuming for users to find target products quickly and efficiently from massive information.Therefore,this paper constructs an e-commerce platform for agricultural products that meets the current needs,and improves user satisfaction by mining user preferences.This thesis improves the collaborative filtering recommendation algorithm and realizes the agricultural product e-commerce system with personalized recommendation function.The main work is as follows:1.Research on the characteristics of online trading of agricultural products,combined with the problems of sparse data,cold start,etc.,based on the traditional collaborative filtering recommendation algorithm,constructed a farm product recommendation model based on agricultural product attributes and categories.This model proposes a similarity improvement algorithm that combines the weighted Jaccard coefficients of information entropy to calculate the similarity of agricultural product attributes.At the same time,the user preference degree factor is introduced to calculate the similarity of agricultural product categories,and then the calculated results are used as a weighted value synthesis.In the calculation of the corrected cosine similarity,the deficiencies caused by data sparse are solved.Through crawler technology,data such as agricultural product categories,attributes,and user ratings are crawled from the agricultural product website.Two experimental measures,MAE and accuracy,are used to compare the improved algorithm with the traditional algorithm,and the effectiveness of the improved algorithm is verified.The expected goal of this thesis.2.Based on the actual needs of the agricultural e-commerce system,we designed the ER diagram and database of the e-commerce system,and designed an e-commerce platform for agricultural products using the MVC design pattern,REACT framework technology,PHP language,and RBAC framework technology.The recommended function for agricultural products.This thesis proposes a farm product recommendation model based on collaborative filtering recommendation algorithm,and realizes the demand for personalized product recommendation.At the same time,an e-commerce system for agricultural products was designed,a website technology framework that meets current business needs was constructed,and a complete front-office service function and back-office management function were implemented.