Personalised advertising push method based on semantic similarity and data mining

Abstract

This paper designed a personalised advertising push method based on semantic similarity and data mining. Firstly, in order to improve the matching degree of advertising keywords, the similarity theory is used to classify advertising categories. According to the classification results, search engine technology is used to match user preferences and advertising keywords to increase the matching degree between advertising content and users. Finally, on the basis of determining the target advertising project, the ads with high semantic similarity are pushed to users as the results. The results show that the matching degree of advertising keywords in this method is between 85% and 95%, the highest accuracy of advertising classification can reach 94%, and the user satisfaction is the highest, indicating that this method has greatly improved the effect of advertising push.