A Web-Based Academic Article Recommendation System: Survey
Keywords:
recommendation system, natural language processing, Content-Based filtering, Collaborative Filtering, text mining, deep learning, machine learningAbstract
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.
