In item cold-start, collaborative filtering techniques cannot be used directly since newly added items have no interactions with users. Hence, content-based filtering is usually the only viable option left. In this paper we propose a feature-based machine learning model that addresses the item cold-start problem by jointly exploiting item content features, past user preferences and interactions...

This paper proposes a system enforcing content-based message filtering conceived as a key service for On-line Social Networks (OSNs). The system allows OSN users to have a direct control on the messages posted on their walls. This is achieved trough a flexible rule-based system, that allows a user to customize the filtering criteria to be applied to their walls, and a Machine Learning based sof...

Aim: This research aim is to determine the level of user satisfaction using Delone and Mclean models obtained from implementation content-based filtering method in anime recommendation system.
 Study Design: study was designed with a Content-based Filtering web-scrapping build an Place Duration Study: Department Informatic Universitas Multimedia Nusantara, between July 2022 December 2022.&...