  Most of the organizations put information on the web because they want it to
be seen by the world. Their goal is to have visitors come to the site, feel
comfortable and stay a while and try to know completely about the running
organization. As educational system increasingly requires data mining, the
opportunity arises to mine the resulting large amounts of student information
for hidden useful information (patterns like rule, clustering, and
classification, etc). The education domain offers ground for many interesting
and challenging data mining applications like astronomy, chemistry,
engineering, climate studies, geology, oceanography, ecology, physics, biology,
health sciences and computer science. Collecting the interesting patterns using
the required interestingness measures, which help us in discovering the
sophisticated patterns that are ultimately used for developing the site. We
study the application of data mining to educational log data collected from
Guru Nanak Institute of Technology, Ibrahimpatnam, India. We have proposed a
custom-built apriori algorithm to find the effective pattern analysis. Finally,
analyzing web logs for usage and access trends can not only provide important
information to web site developers and administrators, but also help in
creating adaptive web sites.
