Implementation of The K-Means Clustering Algorithm to Analyze the User Interest by Analyzing the University Web Log Servers
Journal Title: International Journal for Research in Applied Science and Engineering Technology (IJRASET) - Year 2017, Vol 5, Issue 7
Abstract
Web Usage mining is considered as one of the very important category of the web data mining, which manages the extraction of useful and interesting data from the web log documents. Web utilization has turned out to be the essential part among the young people. The teenage group peoples are inexorably open and shared the online and social culture, which enables them to get data and keep up kinships and connections. But, however they are the very crucial young stage, which sometimes can lead to risky and immature decisions. To keep check on them we analyze the user behavior to predict their interests. The web documents are collected from the university computer center. In this work, K-means clustering algorithm is used. The clusters are formed according to the frequency of the sites visited, and then the analysis is done to judge the interest of the student. It has been find out that most of the student’s interest falls in the category of the Information technology.
Authors and Affiliations
Anmol Kaur, Raman Maini
Keywords
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