Study on mining repeated purchase behaviour intention of online consumers based on big data clustering
by Kai Niu
International Journal of Web Based Communities (IJWBC), Vol. 20, No. 1/2, 2024

Abstract: In order to improve the performance of traditional repeat purchase behaviour intention mining methods in mining accuracy, a repeat purchase behaviour intention mining method of online consumer users based on big data clustering is proposed. Users' repeated purchase behaviour can be combined to reduce the dimension of network data. Extract the characteristics of repeated purchase behaviour of online consumers, judge the similarity of repeated purchase behaviour intention data of online consumers, establish a behaviour association rule mining model, and obtain the mining results of repeated purchase behaviour intention of online consumers. The simulation results show that the proposed method has high accuracy and short time to mine the repeated purchase behaviour intention of online consumers. The highest intention mining accuracy of this method can reach 99.99%.

Online publication date: Thu, 15-Feb-2024

The full text of this article is only available to individual subscribers or to users at subscribing institutions.

 
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.

Pay per view:
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:

    Username:        Password:         

Forgotten your 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