Improved Navigational Pattern Prediction in Web Usage Mining Using Flame Algorithm

dc.contributor.advisor	B Kalpana
dc.contributor.author	T Nandhini
dc.date.accessioned	2016-12-28T01:24:23Z
dc.date.available	2016-12-28T01:24:23Z
dc.date.issued	2016-08
dc.department	Computer Science	en_US
dc.description.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.	en_US
dc.identifier.uri	https://ir.avinuty.ac.in/handle/avu/376
dc.lang	English	en_US
dc.title	Improved Navigational Pattern Prediction in Web Usage Mining Using Flame Algorithm	en_US