Strict collaborative filtering is a method of recommendation that utilizes the collective opinions and preferences of a group of individuals to suggest items or content to a specific user. Unlike traditional collaborative filtering, which takes into account a user’s past interactions and behavior, strict collaborative filtering only considers the input of a select group of users who have similar tastes and interests. This approach ensures a more targeted and accurate recommendation, as it relies on the collective wisdom of a trusted group rather than the individual user’s history alone. Strict collaborative filtering is often used in online platforms and services, such as streaming sites and e-commerce websites, to provide personalized and relevant suggestions to users.