User-based filtering

User-based filtering is a recommendation method that suggests items to a person by identifying other users with similar preferences or behaviors. For example, if you like certain movies, the system finds other users who enjoyed those movies and recommends other movies they liked. It relies on analyzing user patterns to predict what else you might enjoy, based on the idea that people with similar tastes tend to like similar things. This approach personalizes recommendations by leveraging community preferences to improve relevance.