Review and Analysis of E-Commerce Agricultural Products Based on Big Data Algorithm

With the popularization and development of the Internet, e-commerce has become an indispensable part of modern business models. Faced with the increasing demand from consumers, e-commerce platforms require a large amount of agricultural product information to meet their needs. At the same time, e-commerce platforms based on big data algorithms can also provide more refined services, optimize marketing strategies, improve shopping experience, and so on. This article focuses on the review and analysis of e-commerce agricultural products based on big data algorithms. It introduces the process, model design, experimental results, and analysis of agricultural product data construction based on big data algorithms on current e-commerce platforms, and ultimately concludes that e-commerce agricultural products based on big data algorithms can better meet consumer needs, optimize agricultural product procurement, increase sales volume, and improve the quality of agricultural product supply chain.The review and analysis is a method that can be used to analyze the comments and comments left by customers in the product review part of online stores. This technology is not new, but it has improved over time. It was first developed for Amazon in 2009. Today, many companies use this technology as part of their marketing strategies to increase sales and improve customer satisfaction. The determine how consumers like certain products, so as to more effectively advertise on websites or social media platforms (such as Twitter and Facebook).