Prediction method of e-commerce consumers' purchase behaviour based on social network data mining Online publication date: Thu, 15-Feb-2024
by Ming Yang
International Journal of Web Based Communities (IJWBC), Vol. 20, No. 1/2, 2024
Abstract: In order to effectively improve the prediction accuracy of e-commerce consumers' purchase behaviour and shorten the prediction time of e-commerce consumers' purchase behaviour, a prediction method of e-commerce consumers' purchase behaviour based on social network data mining is proposed. Firstly, according to the statistical characteristics of e-commerce consumers' purchase behaviour, data mining method is used to extract the characteristics of e-commerce consumers' purchase behaviour. Secondly, the social network analysis method is used to analyse the purchase behaviour characteristics of e-commerce consumers and the social network model. Finally, build the prediction model of e-commerce consumers' purchase behaviour to realise the prediction of e-commerce consumers' purchase behaviour. The experimental results show that the proposed method has a good effect on the prediction of e-commerce consumers' purchase behaviour, and can effectively improve the prediction accuracy of e-commerce consumers' purchase behaviour. The prediction deviation rate is only 1.8%.
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Web Based Communities (IJWBC):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.
If you still need assistance, please email subs@inderscience.com
Our Blog 
Follow us on Twitter 
Visit us on Facebook