Academic Journal of Computing & Information Science, 2021, 4(6); doi: 10.25236/AJCIS.2021.040605.
Yantao Lan1, Jinshuai Qu1, Jian Chen2
1Key Laboratory of Campus Information and Communication Security Disaster Backup and Recovery, Yunnan Minzu University, Kunming 650500, China
2College of Electronic Engineering, Shenyang Polytechnic College, Shengyang 110045, China
With the rapid development of computer technology, the network behavior in the era of big data has become an important activity in students' campus life, which is quietly changing students' study and life. However, the behavior of students' network users directly reflects the purpose and demand of users and the state and performance of the network. The author analyzes the data of student users' online logs, and uses Apriori algorithm to analyze its association rules. Summarize the characteristics of student users' online behavior, including online time analysis, user's visit to websites and other user behavior analysis, which is of great significance for network optimization, personalizedj and differentiated design of services, standardized management, rational allocation of network bandwidth, enhancing information security, improving the efficiency of daily management of college counselors and network administrators, and ensuring the stability and efficiency of campus network environment.
big data, Internet surfing behavior, association rules
Yantao Lan, Jinshuai Qu, Jian Chen. Research on Internet Surfing Behavior of College Students Based on Big Data. Academic Journal of Computing & Information Science (2021), Vol. 4, Issue 6: 21-34. https://doi.org/10.25236/AJCIS.2021.040605.
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