Open AccessApplication of Monte Carlo Search for Performance Improvement of Web Page Prediction
Author(s) -
K. Shyamala,
S. Kalaivani
Publication year - 2018
Publication title -
international journal of engineering and technology
Language(s) - English
Resource type - Journals
ISSN - 2227-524X
DOI - 10.14419/ijet.v7i3.4.16761
Subject(s) - instruction prefetch , computer science , web server , web page , latency (audio) , monte carlo method , data mining , algorithm , the internet , world wide web , operating system , mathematics , telecommunications , cache , statistics
Prediction in web mining is one of the most complex tasks which will reduce web user latency. The main objective of this research work is to reduce web user latency by predicting and prefetching the users future request page. Web user activities were analyzed and monitored from the web server log file. The present work consists of two phases. In the first phase a directed graph is constructed for web user navigation with the reduction of repeated path. In the second phase, Monte Carlo search is applied on the constructed graph to predict the future request and prefetch the page. This work is successfully implemented and the prediction technique gives a better accuracy. This implementation paves a new way to prefetch the predicted pages at user end to reduce the user latency. Proposed Monte Carlo Prediction (MCP) Algorithm is compared with the existing algorithm Hidden Markov model. Proposed algorithm achieved better accuracy than the Hidden Markov Model. Accuracy is measured for the predicted web pages and achieved the optimal results.