Content-Based Recommender System for Plugin Selection in Wordpress-Based Content Management Systems

Abstract

Content Management Systems (CMSs) play a vital role in modern website development and management. WordPress, Drupal, and Joomla are widely used open-source CMS platforms, with WordPress being the most popular due to its flexibility and ease of use. CMS platforms enable users to create, edit, and manage website content without extensive technical knowledge. This study analyzes the performance of WordPress-based web applications and explores the use of a component-based recommender system for website configuration. Content-based filtering algorithms are applied to recommend suitable implementation components. The results demonstrate the effectiveness of the proposed approach in improving website development and configuration processes. Overall, WordPress provides a reliable and scalable platform for content management