Abstract: Recommendation information is associated with an information classification label by a server of an online interaction platform, and a correspondence between the recommendation information and the information classification label is stored in a feature label database. The recommendation information associated with the information classification label is delivered to a user. Upon triggering of the recommendation information by a user, the information classification label associated with the recommendation information and an unique identifier associated with the user are obtained. By using the unique identifier, a user feature database is queried to determine whether a correspondence between the information classification label and the unique identifier has been established. If it is determining that the correspondence is not established, the correspondence between the information classification label and the unique identifier is established in the user feature database.

Abstract: This specification techniques for targeted information display based on historical user behavior. One example method include receiving an information acquisition request sent by a client, wherein the information acquisition request comprises an identifier of a source display location and an identifier of a user that requests to obtain information; identifying a display location trajectory diagram that corresponds to the user identifier, wherein an order in which the user historically browses display locations is recorded in the display location trajectory diagram; identifying a target display location based on the display location trajectory diagram, the target display location adjacent to the source display location and after the source display location, wherein the target display location is a predicted location that is most likely to be browsed by the user; and transmitting the information to the client that corresponds to the user identifier for display in the target display location.

Abstract: Recommendation information is associated with an information classification label by a server of an online interaction platform, and a correspondence between the recommendation information and the information classification label is stored in a feature label database. The recommendation information associated with the information classification label is delivered to a user. Upon triggering of the recommendation information by a user, the information classification label associated with the recommendation information and an unique identifier associated with the user are obtained. By using the unique identifier, a user feature database is queried to determine whether a correspondence between the information classification label and the unique identifier has been established. If it is determining that the correspondence is not established, the correspondence between the information classification label and the unique identifier is established in the user feature database.

Abstract: Recommendation information is associated with an information classification label by a server of an online interaction platform, and a correspondence between the recommendation information and the information classification label is stored in a feature label database. The recommendation information associated with the information classification label is delivered to a user. Upon triggering of the recommendation information by a user, the information classification label associated with the recommendation information and an unique identifier associated with the user are obtained. By using the unique identifier, a user feature database is queried to determine whether a correspondence between the information classification label and the unique identifier has been established. If it is determining that the correspondence is not established, the correspondence between the information classification label and the unique identifier is established in the user feature database.

Abstract: This specification techniques for targeted information display based on historical user behavior. One example method include receiving an information acquisition request sent by a client, wherein the information acquisition request comprises an identifier of a source display location and an identifier of a user that requests to obtain information; identifying a display location trajectory diagram that corresponds to the user identifier, wherein an order in which the user historically browses display locations is recorded in the display location trajectory diagram; identifying a target display location based on the display location trajectory diagram, the target display location adjacent to the source display location and after the source display location, wherein the target display location is a predicted location that is most likely to be browsed by the user; and transmitting the information to the client that corresponds to the user identifier for display in the target display location.

Abstract: Recommendation information is associated with an information classification label by a server of an online interaction platform, and a correspondence between the recommendation information and the information classification label is stored in a feature label database. The recommendation information associated with the information classification label is delivered to a user. Upon triggering of the recommendation information by a user, the information classification label associated with the recommendation information and an unique identifier associated with the user are obtained. By using the unique identifier, a user feature database is queried to determine whether a correspondence between the information classification label and the unique identifier has been established. If it is determining that the correspondence is not established, the correspondence between the information classification label and the unique identifier is established in the user feature database.