The main goal of the ads selection component is to narrow down the set of ads that are relevant for a given query. In a search-based system, the ads selection component is responsible for retrieving the top relevant ads from the ads database (built using all the active ads in the system) according to the user and query context. In a feed-based system, the ads selection component will select the top k relevant ads based more on user interests than search terms.
Based on our discussions about the funnel-based approach for modeling, it would make sense to structure the ad selection process in the following three phases:
- Phase 1: Quick selection of ads for the given query and user context according to selection criteria
- Phase 2: Rank these selected ads based on a simple and fast algorithm to trim ads.
- Phase 3: Apply the machine learning model on the trimmed ads to select the top ones.