A method for recommending a multimedia content, comprising: acquiring data of a user viewing a multimedia content to be recommended in a trial playing range, wherein the user viewing data comprises at least user audio, video data and user video depth data, said trial playing range being an area for trial playing said multimedia content to be recommended; analyzing the user viewing data, to obtain user action data corresponding to the multimedia content to be recommended; alculating a first user preference score of the multimedia content to be recommended according to the user action data corresponding to the multimedia content to be recommended; acquiring second user preference scores of a plurality of recommended multimedia contents; and recommending the multimedia content to be recommended according to the first user preference score and the second user preference scores. wherein the step of calculating the first user preference score of the multimedia content comprises: determining at least one user action comprised in each piece of the user action data; inquiring pre-stored corresponding relationships between the user actions and user preference values, to obtain a user preference value corresponding to the at least one user action; determining a weight corresponding to each of the user actions according to a ratio of a duration time of the user action to a playing time length of a recommended multimedia content; and calculating the first user preference score of the multimedia content to be recommended according to the user preference value and the weight corresponding to each of the user actions. acquiring data of a user viewing a multimedia content to be recommended in a trial playing range, wherein the user viewing data comprises at least user audio, video data and user video depth data, said trial playing range being an area for trial playing said multimedia content to be recommended; analyzing the user viewing data, to obtain user action data corresponding to the multimedia content to be recommended; alculating a first user preference score of the multimedia content to be recommended according to the user action data corresponding to the multimedia content to be recommended; acquiring second user preference scores of a plurality of recommended multimedia contents; and recommending the multimedia content to be recommended according to the first user preference score and the second user preference scores. wherein the step of calculating the first user preference score of the multimedia content comprises: determining at least one user action comprised in each piece of the user action data; inquiring pre-stored corresponding relationships between the user actions and user preference values, to obtain a user preference value corresponding to the at least one user action; determining a weight corresponding to each of the user actions according to a ratio of a duration time of the user action to a playing time length of a recommended multimedia content; and calculating the first user preference score of the multimedia content to be recommended according to the user preference value and the weight corresponding to each of the user actions. determining at least one user action comprised in each piece of the user action data; inquiring pre-stored corresponding relationships between the user actions and user preference values, to obtain a user preference value corresponding to the at least one user action; determining a weight corresponding to each of the user actions according to a ratio of a duration time of the user action to a playing time length of a recommended multimedia content; and calculating the first user preference score of the multimedia content to be recommended according to the user preference value and the weight corresponding to each of the user actions.