Recommender System for Website Content Management System Selection

Authors

  • Dmitrij Kolodynskij Faculty of Fundamental Sciences, Vilnius Gediminas Technical University, Vilnius, Lithuania

DOI:

https://doi.org/10.5281/zenodo.11213467

Keywords:

content management system, data mining, machine learning, recommender system, web scraper

Abstract

The aim of this study is to automate the process of selecting content management systems based only on company profile data. In this study, a web-browser scenario has been developed to extract enterprise data from publicly available sources. The study was carried out in the Republic of Lithuania. The analysis of the data mining models showed that by applying the Decision Tree algorithm to the classification problem, it is possible to achieve model accuracy of more than 90% in predicting the CMS used by companies based on company profile data.

Downloads

Download data is not yet available.

Downloads

Published

18-05-2024

Issue

Vol. 5 No. 5 (2024)

Section

Articles

License

Copyright (c) 2024 Dmitrij Kolodynskij

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
D. Kolodynskij, “Recommender System for Website Content Management System Selection”, IJRAMT, vol. 5, no. 5, pp. 86–93, May 2024, doi: 10.5281/zenodo.11213467.