  This survey examines the most effective retrieval algorithms utilized in ad
recommendation and content recommendation systems. Ad targeting algorithms rely
on detailed user profiles and behavioral data to deliver personalized
advertisements, thereby driving revenue through targeted placements.
Conversely, organic retrieval systems aim to improve user experience by
recommending content that matches user preferences. This paper compares these
two applications and explains the most effective methods employed in each.
