Abstract
With the development of big data technology more and more perfect, many colleges and universities have begun to use it to analyze the construction work. In daily life, such as class, study, and entertainment, the campus network exists. The purpose of this article is to study the online behavior of users, analyze students’ use of the campus network by analyzing students, and not only have a clear understanding of the students’ online access but also feedback on the operation and maintenance of the campus network. Based on the big data, this article uses distributed clustering algorithm to study the online behavior of users. This article selects a college online user as the research object and studies and analyzes the online behavior of school users. This study found that the second-year student network usage is as high as 330,000, which is 60.98% more than the senior. In addition, the majority of student users spend most of their online time on the weekend, and the other time is not much different. The duration is concentrated within 1 h, 1–2 h, 2–3 h in these three time periods. By studying the user’s online behavior, you can understand the utilization rate of the campus network bandwidth resources and the distribution of the use of the network, to prevent students from indulging in the virtual network world, and to ensure that the network users can improve the online experience of the campus network while accessing the network resources reasonably. The research provides a reference for network administrators to adjust network bandwidth and optimize the network.
Highlights
With the advent of the robot era, with the rise and widespread application of big data technologies such as Hadoop and Spark, robot technology is becoming more and more mature, and people are using robots to deal with more and more things.[1,2] With the development of the times, people need to process more and more data, and the labor costs increase
We can understand the utilization rate of the campus network bandwidth resources and the distribution of the use of the network, prevent students from indulging in the virtual network world, and ensure that the network users can improve the online experience of the campus network while accessing the network resources reasonably, so as to facilitate the network
The university system stores a large amount of data about student behaviors
Summary
With the advent of the robot era, with the rise and widespread application of big data technologies such as Hadoop and Spark, robot technology is becoming more and more mature, and people are using robots to deal with more and more things.[1,2] With the development of the times, people need to process more and more data, and the labor costs increase . In the analysis, they may feel that the load is very large and they cannot be processed as they please. With the robot technology, people are no longer worried about the data. They can use artificial intelligence to process the data in any way according to their own ideas, and the load is not very high. Even as data grow faster and faster, people are no longer powerless when dealing with them.[3,4] From the data point of view, the data are generated by people’s behavior. If there is only a small amount of data, it is not very meaningful for the analyst, the user can be analyzed in depth and a reasonable prediction can be School of Accounting and Finance, Xi’an Peihua University, Xi’an, Shaanxi, People’s Republic of China
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
