An improved Usage Mining using Back Propagation Algorithm With Functional Update

Web usage mining is an important area that requires providing information to the user appropriately for quicker navigation to the desired Web page. In this research work, we are applying Web usage mining for quicker navigation to the desired Web page. A supervised back propagation algorithm (BPA) has been applied to learn the navigated Web pages by different users at different sessions. Online training of BPA is done during browsing of pages and parallelly online testing is done to suggest next probable Web page to the user. The inputs to the BPA are the codified form of Web page IDs and the target outputs are the successive pages. The topology of the network used is 12 X 3 X 1. The log records are used for collecting the details of the Web page contains minimum 6 Web pages and maximum 12 Web pages visited. The performance of the BPA in predicting the next possible web page is above 90%.