LAUSR

Abstract In the traditional e-commerce system, the keyword matching algorithm is used to implement the function of commodity search, and only the goods containing the customer input keyword can be obtained. In view of this limitation, a personalized recommendation system for e-commerce based on big data analysis is studied. The use of improving the search algorithm for goods, personalization system rules of e-commerce and text matching algorithm are introduced, so in the search of goods, it not only displays the exact matching of goods, but provides the goods similar to their requirements, for reference. The research shows that the personalized recommendation system of e-commerce based on big data analysis can not only increase the transaction opportunities, explore potential customers, but also improve the level of personalized service. This is very important for the enterprise economy and the personalized development of e-commerce.