1. A computer-implemented method, comprising: identifying event data for a user identifier based on past user sessions associated with the user identifier that occurred during a first time period, the event data specifying events that occurred during the past user sessions; categorizing, by one or more processors, each of the events as belonging to one or more vertical categories; for each vertical category, determining a user identifier interest weight for the user identifier based on the events that belong to the vertical category; generating long-term user identifier profile data for the user identifier based on the user identifier interest weights from the event data that are based on past user sessions that occurred during the first time period; generating short-term user identifier profile data for the user identifier based on the user identifier interest weights from the event data that are based on past user sessions that occurred during a second time period that is a most recent sub-period of the first time period; selecting a candidate advertisement set based on the long-term user identifier profile data; and adjusting a ranking order of the candidate advertisement set based on the short-term user-identifier profile data.