Abstract
<p style="text-align: justify;"><span style="font-family: "times new roman";">With the accelerating pace of life of Chinese residents, the expansion of the new media marketing market and the surge in the number of online shoppers have prompted e-commerce platforms to generate a wealth of e-commerce sales data. Faced with complex sales data, merchants need to analyze and understand the data in depth. Based on this, the purpose of this article is to study the application of e-commerce new media marketing based on data mining technology. This article first summarizes the basic theories of data mining, and then studies and analyzes its mining process, functions and methods. This paper systematically expounds the data preprocessing process, data preprocessing method selection and system algorithm realization of data mining technology in e-commerce new media marketing, and uses comparative method, observation method and other research forms to study the subject of this article. Experimental research shows that when user similarity calculation adopts the method Attribute-SimRank in this paper, the average hit rate of product recommendation for cluster center users is in most cases higher than that of SimRank and Attribute methods.</span>
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