Using long-term features and short-term features to filter content before a selection process to reduce latency of a content distribution system

Abstract

Using long-term features and short-term features to reduce latency in providing recommendations is described. A user device in a session with an online system may request a recommendation. The online system identifies a set of recommendations based in part on the request. The online system retrieves long-term features for each of the set, and determines short-term features for each of the set. The short-term features are based on the session. The online system applies the long-term features and the short-term features to a scoring model that scores the recommendations of the set. The online system selects a subset of the set based on the scores, and provides the selected subset to a selector that selects a recommendation from the subset. The recommendation may be provided to the user device prior to expiration of a latency period associated with serving the recommendation request.