Kaustubh Sathe Abhishek Aute Abhishek Kolhe Pratham Tribhuvan Dr.Suvarna Patil Mrs.Sneha Kanawade

In the age of digital information overload, person- alized news recommendation systems are essential for enhancing user experience by tailoring news content to individual prefer- ences and behaviors. Our project, FocusFeed, aims to manage information overload and increase user engagement by using advanced algorithms and user profiling to deliver relevant news. We utilize a hybrid model consisting of Neural Collaborative Filtering (NCF) and Content-Based Filtering (CBF) to improve recommendation efficiency. Additionally, our system provides a summary feature for each news article, offering users the option to view either the full article or a concise summary. This approach aims to improve user satisfaction and offers monetization opportunities for news provider

https://doi.org/10.58357/jedcs.2025.v4.i1.15