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.

翻译：本综述探讨了广告推荐与内容推荐系统中应用的最有效的检索算法。广告定向算法依赖于详细的用户画像与行为数据来投放个性化广告，从而通过定向投放驱动收入。相反，有机检索系统旨在通过推荐符合用户偏好的内容来提升用户体验。本文比较了这两种应用场景，并分别阐释了各自采用的最有效方法。