Agricultural Product Recommendation Model and E-Commerce System based on CFR Algorithm

With the development of e-commerce, people have more pursuit for online shopping. In the online shopping environment, users also need a good experience when browsing goods online. So now more and more people choose to buy their favorite agricultural products with certain characteristics, affordable and reassuring through the Internet. Therefore, the research on agricultural product recommendation model and e-commerce system design based on collaborative filtering recommendation (CFR) algorithm is very useful. Firstly, this paper introduces the characteristics of agricultural product recommendation, then studies the application of collaborative filtering algorithm, designs and develops the agricultural product recommendation model and e-commerce system based on the algorithm, and tests the function of the model. Finally, the test results show that the short-term prediction accuracy of the system is slightly low, but the accuracy is relatively high, covering a wide range of agricultural products, and the user coverage is also high, which can meet the shopping needs of users for agricultural products.