• mani

Abstract- In the digital era, An end user mostly depend on the WWW for information,but the search engines which are used frequently often retrieves a large number of results many of which are not always relevant to the users’ need. Web Logs are repositories that store vital information of user activities and navigation. Suitable data mining techniques when applied to it can definitely improve the performance of search engines, making the user to attain his goal of getting the relevant information. The web search can be optimized to provide the user with exact web pages from where he can obtain the information of his search goal. In this paper, we propose a web recommendation approach which based on machine learning from web logs and to recommend users with web pages that are of importance to his interests by comparing it with users’ historic browsing pattern. Finally, the result is optimized by assigning new ranks to the result pages. The proposed system proves to be efficient in terms of the page ordering and thus reducing the search time. Keywords- WWW, Web log; web usage mining; recommendations;Ranking ;Machine Learning

Keywords- WWW, Web log; web usage mining; recommendations;Ranking ;Machine Learningmani

"Two phase methodology for optimized web page recommendation ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.5, Issue 12, page no.119-124, December-2018, Available :http://www.jetir.org/papers/JETIR1812817.pdf

"Two phase methodology for optimized web page recommendation ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.5, Issue 12, page no. pp119-124, December-2018, Available at : http://www.jetir.org/papers/JETIR1812817.pdf