Discovering Web Server Logs Patterns Using Generalized Association Rules Algorithm
Mohd Helmy Abd Wahab, Mohd Norzali Haji Mohd, Mohamad Farhan Mohamad Mohsi · InTech eBooks · 2010
Web Usage Mining is an aspect of data mining that has received a lot of attention in recent year (Kerkhofs et al., 2001). Commercial companies as well as academic researchers have developed an extensive array of tools that perform several data mining algorithms on log files coming from web servers in order to identify user behaviour on a particular web site. Performing this kind of investigation on the web site can provide information that can be used to better accommodate the user's needs. Web usage mining has been applied to several applications such as business and finance (Lee and Liu, 2001), E-commerce (Srivastava, 2000), information retrieval (Pal, 2002) and Academic and Industry (Srivastava et al., 2000). In this study, generalized association rules have been applied to web server log from Tutor.com. It is important to mention that the most efforts have relied on relatively simple techniques which can be inadequate for real user profile data since noise in the data has to be firstly tackled. Thus, there is a need for robust methods that integrates different intelligent techniques that are free of any assumptions about the noise contamination rate.