haruhi
2020-06-14 22:47:09 +08:00
The candidate generation network takes events from the user’s YouTube activity history as input and retrieves a small subset (hundreds) of videos from a large corpus. These candidates are intended to be generally relevant to the user with high precision. The candidate generation network only provides broad personalization via collaborative filtering. The similarity between users is expressed in terms of coarse features such as IDs of video watches, search query tokens and demographics.
Presenting a few “best” recommendations in a list requires a fine-level representation to distinguish relative importance among candidates with high recall. The ranking network accomplishes this task by assigning a score to each video according to a desired objective function using a rich set of features describing the video and user. The highest scoring videos are presented to the user, ranked by their score.
协同过滤、数据标签阈值。一直给你推 ASMR 内容,说明 YouTube 上看这类内容的人(或和你行为类似的人),基本只看 ASMR,不看其他内容;如果这些人还看、点赞(等等行为)其他内容,那么也会给你推其他内容…