A Web-Based Academic Article Recommendation System: Survey

The rise of the internet and intelligent gadgets has increased platform traffic, collecting data to detect user preferences. Researchers need help finding relevant material due to the rapid proliferation of academic papers across fields. Academic article recommendation systems (ARSs) help solve this problem by suggesting articles based on research interests and needs. Academic article recommendation algorithms help navigate the vast scholarly literature. Researchers, students, and academics utilize them to find articles that match their interests and study emphasis in enormous databases. This review covers recommendation algorithms, data sources, assessment metrics, and user interfaces in ARS research. This survey also examines new trends and research directions, such as advanced machine learning and semantic analysis