  World Wide Web is a huge data repository and is growing with the explosive
rate of about 1 million pages a day. As the information available on World Wide
Web is growing the usage of the web sites is also growing. Web log records each
access of the web page and number of entries in the web logs is increasing
rapidly. These web logs, when mined properly can provide useful information for
decision-making. The designer of the web site, analyst and management
executives are interested in extracting this hidden information from web logs
for decision making. Web access pattern, which is the frequently used sequence
of accesses, is one of the important information that can be mined from the web
logs. This information can be used to gather business intelligence to improve
sales and advertisement, personalization for a user, to analyze system
performance and to improve the web site organization. There exist many
techniques to mine access patterns from the web logs. This paper describes the
powerful algorithm that mines the web logs efficiently. Proposed algorithm
firstly converts the web access data available in a special doubly linked tree.
Each access is called an event. This tree keeps the critical mining related
information in very compressed form based on the frequent event count. Proposed
recursive algorithm uses this tree to efficiently find all access patterns that
satisfy user specified criteria. To prove that our algorithm is efficient from
the other GSP (Generalized Sequential Pattern) algorithms we have done
experimental studies on sample data.
