Research on intelligent recommendation system model supported by data mining and algorithm optimization

With the rapid development of China's mobile Internet and the advent of 5g era, employees from all walks of life will basically use websites to buy all kinds of goods needed in life. As we all know, big data has become a key direction in the work of various Internet companies and the recommendation system can be said to be one of the best landing applications of big data. The benefits it brings to Internet companies are real and visible. Especially for e-commerce, intelligent recommendation system can directly affect the sales performance of an e-commerce enterprise[1]. How to store these massive data and efficiently mine valuable user information is the real challenge of big data technology[2]. In this paper, based on the modified Chinese Amazon e-commerce data set well-known in the field of recommendation system construction, and based on the real business data architecture of an e-commerce website, the project constructs an integrated e-commerce recommendation system, offline recommendation service and real-time recommendation service provide a variety of methods to achieve mixed recommendation effect. It provides a variety of off-line analysis methods and clever and accurate real-time recommendation model to realize data mining.