Linear Regression Feature and Frog Leaping Algorithm based Web Page Recommendation

Abstract

Website content and services attract surfers to visit page. Random visitor or first time visitor need more user suggestion for increasing the retaining of user. This work has worked in field of web page prediction as per user previous visits. Web mining logs and content features were further processed to extract the linear regression feature from the work. Extracted features were used for the page prediction in testing phase. Frog leaping genetic algorithm was used for the population generation and possible page prediction. Experiment was done on real dataset extracted from projecttunnel.com website. Results were compared with existing page prediction models and it was obtained that Web Page Prediction Frog Leaping Algorithm (WPPFLA) model has improved the work performance with respect to precision value, accuracy, Fitness measure and Metric values.