As
on discovering the web usage patterns of websites from the server log files. The
Web is a huge, explosive, diverse, dynamic and mostly unstructured data
repository, which supplies incredible amount of information, and also raises
the complexity of how to deal with the information from the different
perspectives of view, users, web service providers, business analysts. The
users want to have the effective search tools to find relevant information
easily and precisely. The Web service providers want to find the way to predict
the users’ behaviors and personalize information to reduce the traffic load and
design the Website suited for the different group of users. The business
analysts want to have tools to learn the user/consumers’ needs. All of them are
expecting tools or techniques to help them satisfy their demands and/or solve
the problems encountered on the Web. Therefore, Web mining becomes a popular
active area and is taken as the research topic for this investigation. Web
Usage Mining is the application of data mining techniques to discover
interesting usage patterns from Web data, in order to understand and better
serve the needs of Web-based applications. Usage data captures the identity or origin of Web users along with
their browsing behavior at a Web site.
Web
usage mining itself can be classified further depending on the kind of usage
data considered. They are web server data, application server data and
application level data. Web server data correspond to the user logs that are collected
at Web server. Some of the typical data collected at a Web server include IP
addresses, page references, and access time of the users and is the main input
to the present Research. This Research work concentrates on web usage mining
and in particular focuse