1. A content recommendation system, comprising: one or more computer processors to: determine a plurality of user behavior categories pertaining to a plurality of user behaviors within a preset time period, and a plurality of user behavior frequencies corresponding to the plurality of user behavior categories; determine, based at least on the user behavior categories and corresponding user behavior frequencies, user preference data comprising frequency distribution information of a plurality of pieces of content information targeted by user behaviors in the user behavior categories; divide the preset time period into a plurality of time segments; analyze content information targeted by user behaviors in each time segment to determine user preference data for each time segment; determine whether a drifting user preference, a sudden user preference, or a combination thereof exists based on the analyzed content information; in the event that the drifting user preference exists, remove the drifting user preference from the content information; in the event that the sudden user preference exists, remove the sudden user preference from the content information; recommend content information to a user based at least in part on the user preference data, wherein the user is a target user; identify a plurality of similar users who are similar to the target user, comprising to: determine whether a geographical region corresponding to a current Internet Protocol (IP) address of the target user matches a registered geographical region of the target user; in the event that the geographical region corresponding to the current IP address of the target user matches the registered geographical region of the target user, select a reference user set among other users with the same registered geographical region as the registered geographical region of the target user; in the event that the geographical region corresponding to the current IP address of the target user does not match the registered geographical region of the target user, select a reference user set among other users with the same registered geographical region as the geographical region corresponding to the IP address of the target user; and identify the plurality of similar users by comparing the target user with users in the reference user set; obtain user behavior categories and corresponding user behavior frequencies of the plurality of similar users; determine, based on the user behavior categories and corresponding user behavior frequencies of the plurality of similar users, population preference data comprising frequency distribution of a plurality of pieces of content information targeted by user behaviors of the plurality of similar users; and recommend content information to the target user based at least in part on the population preference data and one or more memories coupled to the one or more processors, configured to provide the one or more processors with instructions.