Item-Item Collaborative Filtering

Item-Item Collaborative Filtering is a recommendation method used by online platforms to suggest products or content based on user preferences. It compares items to identify similarities, looking at how users have rated different items. For example, if you and others enjoyed a particular book, the system will recommend similar books that those users liked. This approach focuses on the relationships between items rather than users, making it effective at identifying patterns and suggesting relevant options, enhancing your experience by connecting you to things you might like based on the preferences of others with similar tastes.