AI for Personalized News Recommendations

For a mini project on AI for personalized news recommendations, you can develop a system that leverages machine learning algorithms to curate news articles based on user preferences and behaviors. The project can begin with data collection, where you gather articles from various sources, along with metadata such as categories, publication dates, and user engagement metrics. You can use collaborative filtering or content-based filtering techniques to analyze user interactions, such as clicks and read times, to identify patterns in user preferences. Implementing a recommendation algorithm like matrix factorization or k-nearest neighbors can help generate tailored news feeds. The project can also include a user interface where users can provide feedback on recommended articles, allowing the model to refine its suggestions over time. By evaluating the system’s performance through metrics like precision and recall, you can demonstrate the effectiveness of your personalized news recommendation engine.