International Journal of Computer Applications |
Foundation of Computer Science (FCS), NY, USA |
Volume 100 - Number 15 |
Year of Publication: 2014 |
Authors: S. Muthu Mari, T. Meyyappan |
10.5120/17604-8311 |
S. Muthu Mari, T. Meyyappan . Analyzing the Usage Pattern of University Website using Apriori Algorithm through Frequent Item set Generation. International Journal of Computer Applications. 100, 15 ( August 2014), 40-46. DOI=10.5120/17604-8311
Data Mining plays important role in finding previously unknown patterns from huge volume of data. The data mining extends its branches in many areas in which Web Mining is one of the important arena. Analyzing the web usage and its content becomes very important aspect. The web log servers are maintained to estimate total number of usage of the pages in websites. It holds the details such as the Internet Protocol Address of the user, Session, Browser as well as cookies information along with the date and time of visit. To find the effective pattern analysis and collecting the interesting patterns in website (web mining), association rule mining, clustering techniques were employed. Apriori is a classic algorithm for learning association rules. In this paper, the Web server log is analyzed into two different ways. Frequent pattern and analyzed with IP address of the visitor and also with time of visit. Based on the two refinements the Apriori algorithm generates the mined patterns that occur frequently.