K2

K² (K squared) is an algorithm used in personalization systems, such as search engines and recommendation engines. It analyzes data about how users interact with content—like clicks, views, or preferences—to identify and rank relevant items. By understanding patterns and the importance of different attributes, K² helps deliver more accurate and tailored results for each individual. Essentially, it’s a mathematical tool that enhances the relevance of content by learning from user behavior, improving the overall experience in finding what users are most likely interested in.