Article Per Year (5 Year)
p-Index From 2021 - 2026
0.23
P-Index
This Author published in this journals
All Journal International Journal of Electrical and Computer Engineering
Tan Hanh
Posts and Telecommunications Institute of Technology
Computer Science & IT Electrical & Electronics Engineering

Published : 1 Documents Claim Missing Document
Claim Missing Document
Check
Articles

Found 1 Documents
Search

 1 
Investigating the PageRank and sequence prediction based approaches for next page prediction Nguyen Thon Da; Tan Hanh
International Journal of Electrical and Computer Engineering (IJECE) Vol 11, No 3: June 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v11i3.pp2229-2237

Abstract

Discovering unseen patterns from web clickstream is an upcoming research area. One of the meaningful approaches for making predictions is using sequence prediction that is typically the improved compact prediction tree (CPT+). However, to increase this method's effectiveness, combining it with at least other methods is necessary. This work investigates such PageRank-based methods related to sequence prediction as All-K-Markov, DG, Markov 1st, CPT, CPT+. The experimental results proved that the integration of CPT+ and PageRank is the right solution for next page prediction in terms of accuracy, which is more than a standard method of approximately 0.0621%. Still, the size of the newly created sequence database is reduced up to 35%. Furthermore, our proposed solution has an accuracy that is much higher than other ones. It is intriguing for the next phase (testing one) to make the next page prediction in terms of time performance.
Co-Authors Nguyen Thon Da