A collaborative filtering recommender system is a type of artificial intelligence system that uses the preferences and ratings of a group of users to make recommendations to individual users. This type of system is often used in online retail and other applications where users can rate or review products or services. In a collaborative filtering system, the system collects ratings and reviews from a group of users and uses them to build a model of their preferences. The system then uses this model to make recommendations to individual users based on what similar users have liked or rated highly in the past. For example, if a user gives a high rating to a particular book, the system may recommend other books that other users who have also rated that book highly have enjoyed. Overall, collaborative filtering recommender systems use the collective wisdom of a group of users to make personalized recommendations to individual users.
Necessary cookies are absolutely essential for the website to function properly. This category only includes cookies that ensures basic functionalities and security features of the website. These cookies do not store any personal information.
Any cookies that may not be particularly necessary for the website to function and is used specifically to collect user personal data via analytics, ads, other embedded contents are termed as non-necessary cookies. It is mandatory to procure user consent prior to running these cookies on your website.