Improved Navigational Pattern Prediction in Web Usage Mining Using Flame Algorithm
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Date
2016-08
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Abstract
Web mining is used to extract the usefiil infoiTnation from the web documents and
sei"vices. Web usage mining is the automatic discovery of user access pattern from web servers.
Organizations collect a large volume of data in their daily operations, generated automatically by
web servers and collected in server access logs. The web pages and links present in the World
Wide Web helps the user to gather required information. The process of mining the weblogs to
obtain the accurate results and the pattern prediction of the navigation are irrefutably vital for
tuning up websites. This work aims at improving the prediction of navigation pattern which in
mm helps in efficient web page caching. The existing strategies such as DBscan and FP-growth
are experimented and an attempt has been made to improve the prediction using Flame
algorithm, which has been applied in the area of sequential pattern mining. The experiments
show that the Flame algorithm improves the navigation pattern prediction in web usage mining.