Social wireless network user big data mining based on Python platform and hierarchical clustering computing
by Kun Wang; Xiangbo Liang
International Journal of Networking and Virtual Organisations (IJNVO), Vol. 25, No. 1, 2021

Abstract: Human behaviour, because of its complexity, makes it very important and interesting to explore the law of human behaviour. In recent years, the online social network represented by online personal community, online dating network and social network makes the amount of data of network users surge. The era of big data online social network gives us unprecedented opportunities to study human behaviour. The development of information science, the emergence of computer and the development of modern data storage technology provide us with a new objective material basis for the study of human behaviour. Data mining is an interdisciplinary subject, involving statistics, pattern recognition, information retrieval, machine learning and other disciplines. Data mining has been paid more and more attention by domestic and foreign academic circles, and has become a research hotspot. Therefore, this paper studies social wireless network user big data mining based on hierarchical clustering computing, the system is implemented via Python and compared with the latest models. The convincing results have proven the effectiveness.

Online publication date: Thu, 23-Sep-2021

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 Networking and Virtual Organisations (IJNVO):
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