英文摘要 |
Understanding the trends of Web users behavior is an important factor for running a successful website. Owners or adminstrators of websites need to make efficient marketing strategies and provide better services according to the change of users hehaviors. Data mining has become a significant tool to explore such kinds of information in the Internet age. In this paper, FP-Growth algorithm was applied to discover frequent itermsets on cllected data at different periods. Three types of changes for frequent itemsets (i.e., emerging pattern, perished pattern and persistent pattern) were defined to observe the behaviors of Web users. Among the results that data were collected from 104 tutoring Web site, we showed the charactertics of changes of Web users behaviors by analyzing these derived patterns. |