Title: Intelligent evaluation model of e-commerce transaction volume based on the combination of k-means and SOM algorithms

Authors: Junjie Niu

Addresses: Qingdao Vocational and Technical College of Hotel Management, Qingdao 266000, China

Abstract: Due to the lack of steps to process sensitive data in the traditional intelligent evaluation model of e-commerce transaction volume, which leads to poor evaluation effect, an intelligent evaluation model of e-commerce transaction volume based on the combination of k-mean and SOM algorithm is proposed. Taking system intelligent clustering as the core, the transaction volume data in the web log is collected through the collection system. The desensitisation rule is used to establish the data transmission model of trading volume. The detection of sensitive data adopts signal detection technology and analytical processing. Based on k-means algorithm, data desensitisation is accomplished to achieve data denoising and a clustering evaluation model is established to complete data mining and analysis. The experimental results show that the model has a good denoising effect, and the ROC curve is closer to the upper left corner with an AUC value of 0.9712, which verifies the effectiveness and superiority of the model.

Keywords: system intelligent clustering; e-commerce transaction volume; evaluation model; k-means; SOM.

DOI: 10.1504/IJICT.2021.113043

International Journal of Information and Communication Technology, 2021 Vol.18 No.2, pp.189 - 206

Received: 12 Oct 2019
Accepted: 12 Dec 2019
Published online: 16 Feb 2021 *

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