Recommendation System
A recommendation system is a subclass of information filtering system that seeks to predict the 'rating' or 'preference' a user would give to an item. It is commonly used in e-commerce websites and online platforms to suggest products, services, or content to users based on their past behavior, preferences, and interests. Recommendation systems can be based on various techniques such as collaborative filtering, content-based filtering, and hybrid filtering. Collaborative filtering is based on the assumption that people who agreed in the past will agree in the future, and it recommends items based on the similarity of users' behavior. Content-based filtering recommends items based on the similarity of their attributes and features. Hybrid filtering combines both techniques to provide more accurate and diverse recommendations. Recommendation systems can also be evaluated using metrics such as precision, recall, and F1-score.
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