Probability Density Feature and Teacher Learning Based Web Page Recommendation

Abstract

With the drastic increase of the digital content on the servers, it is necessary to develop a algorithm for reducing a latency time of web pages. This work has proposed user behavior based page recommendation by the analysis of web features. Proposed work has utilizes two existing web features named as logs and content. With the help of existing features new probability density web feature was proposed by the work to increase the work efficiency. Due to dynamic nature of web user TLWPP (Teacher Learning Based Web Page prediction) model was proposed in this paper. Experimental work was done on real, live web-portal of a international Journal. Result shows that Use of two phase crossover operation in TLWPP model has reduces the time to get better solution.