Title: Personalised advertising push method based on semantic similarity and data mining

Authors: Shibiao Mu; Shuaijing Yu

Addresses: Yiwu Industrial and Commercial College, Yiwu 322000, China ' Yiwu Industrial and Commercial College, Yiwu 322000, China

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.

Keywords: semantic similarity; data mining; advertising push; search engine technology; key word; association rules.

DOI: 10.1504/IJWBC.2023.131385

International Journal of Web Based Communities, 2023 Vol.19 No.2/3, pp.93 - 103

Received: 03 Sep 2021
Accepted: 21 Feb 2022
Published online: 09 Jun 2023 *

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