  A real world challenging task of the web master of an organization is to
match the needs of user and keep their attention in their web site. So, only
option is to capture the intuition of the user and provide them with the
recommendation list. Most specifically, an online navigation behavior grows
with each passing day, thus extracting information intelligently from it is a
difficult issue. Web master should use web usage mining method to capture
intuition. A WUM is designed to operate on web server logs which contain user's
navigation. Hence, recommendation system using WUM can be used to forecast the
navigation pattern of user and recommend those to user in a form of
recommendation list. In this paper, we propose a two tier architecture for
capturing users intuition in the form of recommendation list containing pages
visited by user and pages visited by other user's having similar usage profile.
The practical implementation of proposed architecture and algorithm shows that
accuracy of user intuition capturing is improved.
