WEB PAGE RECOMMENDATION BY ELEPHANT HERD OPTIMIZATION & KNN MODEL

Abstract

Recommender systems open new opportunities of retrieving personalized information on the Internet. It also helps to alleviate the problem of information overload which is a very common phenomenon with information retrieval systems and enables users to have access to products and services which are not readily available to users on the system. In this paper weblog and web content features were used for the web page recommendation. Weblog features were optimize by the use KNN model finds the possible pages as per page views. Further predicted pages were optimize by the use of web content in elephant herd optimization algorithm. Experiment was done on real website weblog data. Use of dynamic algorithm for page recommendation is highly favorable as web visitors are new and develop new weblog patterns. Result shows that proposed model Elephant Herd based Web page Recommendation (EHWPP) has increases the work efficiency. 

Keywords— Data mining, Feature Extraction, Page Recommendation, Web mining.