Open AccessIntegration of the PageRank Algorithm, Sequence Processing, and CPT+ for Webpage Access Prediction
Author(s) -
Nguyen Thon Da,
Tan Hanh,
Pham Hoang Duy
Publication year - 2020
Publication title -
international journal of recent technology and engineering
Language(s) - English
Resource type - Journals
ISSN - 2277-3878
DOI - 10.35940/ijrte.f8209.038620
Subject(s) - pagerank , computer science , sequence (biology) , web page , data mining , algorithm , information retrieval , world wide web , biology , genetics
In this article, we provide a novel model to address the issue of webpage access prediction. In particular, the main approach we propose aims to reduce execution time by reducing the sequence space. This solution combines calculation of PageRank values of sequences in sequence databases and analysis of sequences from these shortened sequence databases. To evaluate the solution, we chose K-fold validation with K = 10 by randomizing the dataset 10 times; then the system calculated the average PageRank values of sequences. Next, with acceptable accuracy (when the size of datasets was reduced by up to 30% by PageRank calculation), we performed next access page prediction by analysing 1000 sequences. Experimental results for the real FIFA dataset show that our new proposed approach is much better than previous approaches in terms of prediction execution time.