Method of recommending media content and media playing system thereof

1. A method of recommending media content for a media playing system, the method comprising:

identifying a user in a viewing area;

determining whether personal information of the user is stored in a database; and

generating information related to a first media content recommendation according to the personal information when the personal information of the user is stored in the database;

wherein the step of generating the information related to the first media content recommendation according to the personal information comprises:

determining whether there are any other users in the viewing area apart from the user who have personal information stored in the database;

when determining there is only the user in the viewing area having personal information stored in the database, generating the information related to the first media content recommendation according to preference information among the personal information of the user; and

when determining there are other users in the viewing area having personal information stored in the database, further determining whether there is any related preference information between the personal information of the user and the personal information of the other users.

2. The method of claim 1 , wherein the step of identifying the user in the viewing area is performed through a face detecting method.

3. The method of claim 1 , wherein the step of determining whether the personal information of the user is stored in the database comprises:

determining whether a degree of similarity between a first facial feature of the user and a second facial feature among each personal information stored in the database is greater than a predefined value;

when determining that the degree of similarity between the first facial feature of the user and the second facial feature among any of the personal information stored in the database is greater than the predefined value, determining the personal information of the user is stored in the database, and determining the user is a user in the database who has the second facial feature with a maximum degree of similarity to the first facial feature; and

when determining that the degree of similarity between the first facial feature of the user and the second facial feature among each of the personal information stored in the database is less than the predefined value, determining the personal information of the user is not stored in the database.

4. The method of claim 1 , wherein the step of determining whether there is any related preference information between the personal information of the user and the personal information of the other users comprises:

determining whether there is a first media file which has been played by the user and the other users simultaneously;

when determining there is a first media file which has been played by the user and the other users simultaneously, recommending media content related to the first media file, in order to generate the information related to the first media content recommendation; and

when determining there is no first media file which has been played by the user and the other users simultaneously, further determining whether there is a second media file which has been played by both the user and the other users.

5. The method of claim 4 , wherein the step of determining whether there is a second media file which has been played by both the user and the other users comprises:

when determining there is a second media file which has been played by both the user and the other users, recommending media content related to the second media file, in order to generate the information related to the first media content recommendation; and

when determining there is no second media file which has been played by both the user and the other users, further determining a utilizing priority of all users, and giving a higher weight to a third media file which has been played by a user who has a higher utilizing priority, in order to generate the information related to the first media content recommendation according to the weight.

6. The method of claim 5 , wherein the step of determining the utilizing priority of all users comprises determining the utilizing priority of all users according to a time of each user utilizing the media playing system.

7. The method of claim 5 , wherein the step of determining the utilizing priority of all users comprises determining the utilizing priority of all users according to a number of times or a frequency of each user playing media files in the media playing system.

8. The method of claim 1 , wherein when the personal information of the user is not stored in the database, generating information related to a second media content recommendation according to a universal feature and information related to the universal feature.

9. The method of claim 8 , wherein the step of generating the information related to the second media content recommendation according to the universal feature and the information related to the universal feature comprises:

classifying users in the viewing area whose personal information is not stored in the database into a plurality of user types according to the universal feature;

obtaining a specific user type among the plurality of user types having most users according to a classification result; and

generating the information related to the second media content recommendation according to specific feature information corresponding to the specific user type.

10. The method of claim 9 , wherein the universal feature comprises an ethnicity, a gender and an age of the user, and the plurality of user types comprises a combination of different ethnicities, different genders and different ages.

11. The method of claim 9 , wherein the step of generating the information related to the second media content recommendation according to the specific feature information corresponding to the specific user type comprises generating the information related to the second media content recommendation according to universal preference information of all users among the specific user type.

12. The method of claim 8 , wherein when the information related to the first media content recommendation and the information related to the second media content recommendation have a same media file, giving a higher weight to the same media file.

13. The method of claim 1 , further comprising playing a media file directly according to the information related to the first media content recommendation.

14. A method of recommending media content for a media playing system, the method comprising:

identifying a plurality of users in a viewing area, in order to generate an identifying result;

dividing the plurality of users into a first group and a second group according to the identifying result, wherein personal information of each user in the first group is stored in a database, and personal information of each user in the second group is not stored in the database; and

generating information related to a first media content recommendation according to the personal information of each user in the first group.

15. The method of claim 14 , wherein the step of identifying the plurality of users in the viewing area is performed through a face detecting method.

16. The method of claim 14 , wherein the step of dividing the plurality of users into the first group and the second group according to the identifying result comprises:

determining whether a degree of similarity between a first facial feature of each user among the plurality of users and a second facial feature among each personal information stored in the database is greater than a predefined value;

when determining that the degree of similarity between the first facial feature of the user and the second facial feature among any of the personal information stored in the database is greater than the predefined value, dividing the user into the first group, and determining the user is a user in the database who has the second facial feature with a maximum degree of similarity to the first facial feature; and

when determining that the degree of similarity between the first facial feature of the user and the second facial feature among each of the personal information stored in the database is less than the predefined value, dividing the user into the second group.

17. The method of claim 14 , wherein the step of generating the information related to the first media content recommendation according to the personal information of each user in the first group comprises:

determining whether there is only one user or whether there is a plurality of users in the first group;

when determining there is only one user in the first group, generating the information related to the first media content recommendation according to preference information among the personal information of the only one user; and

when determining there is a plurality of users in the first group, further determining whether there is any related preference information between the personal information of the plurality of users.

18. The method of claim 17 , wherein the step of determining whether there is any related preference information between the personal information of the plurality of users comprises:

determining whether there is a first media file which has been played by any of the plurality of users simultaneously;

when determining there is a first media file which has been played by more than one of the plurality of users simultaneously, recommending media content related to the first media file, in order to generate the information related to the first media content recommendation; and

when determining there is no first media file which has been played by more than one of the plurality of users simultaneously, further determining whether there is a second media file which has been played by any of the plurality of users in common.

19. The method of claim 18 , wherein the step of determining whether there is a second media file which has been played by any of the plurality of users in common comprises:

when determining there is a second media file which has been played by more than one of the plurality of users in common, recommending media content related to the second media file, in order to generate the information related to the first media content recommendation; and

when determining there is no second media file which has been played by more than one of the plurality of users in common, further determining a utilizing priority of the plurality of users, and giving a higher weight to a third media file which has been played by a user who has a higher utilizing priority, in order to generate the information related to the first media content recommendation according to the weight.

20. The method of claim 19 , wherein the step of determining the utilizing priority of the plurality of users comprises determining the utilizing priority of the plurality of users according to a time of each user utilizing the media playing system.

21. The method of claim 19 , wherein the step of determining the utilizing priority of the plurality of users comprises determining the utilizing priority of the plurality of users according to a number of times or a frequency of each user playing media files in the media playing system.

22. The method of claim 14 , further comprising generating information related to a second media content recommendation according to a universal feature of each user in the second group and information related to the universal feature.

23. The method of claim 22 , wherein the step of generating the information related to the second media content recommendation according to the universal feature of each user in the second group and the information related to the universal feature comprises:

classifying the users in the second group into a plurality of user types according to the universal feature;

obtaining a specific user type among the plurality of user types having most users according to a classification result; and

generating the information related to the second media content recommendation according to specific feature information corresponding to the specific user type.

24. The method of claim 22 , wherein the universal feature comprises an ethnicity, a gender and an age of the user, and the plurality of user types comprises a combination of different ethnicities, different genders and different ages.

25. The method of claim 23 , wherein the step of generating the information related to the second media content recommendation according to the specific feature information corresponding to the specific user type comprises generating the information related to the second media content recommendation according to universal preference information of all users among the specific user type.

26. The method of claim 22 , wherein when the information related to the first media content recommendation and the information related to the second media content recommendation have a same media file, giving a higher weight to the same media file.

27. The method of claim 14 , further comprising playing a media file directly according to the information related to the first media content recommendation.

28. A media playing system, for executing a method of recommending media content as stated in claim 1 , the media playing system comprising:

a database;

a sensing device, for identifying a user in a viewing area; and

a processing unit, for determining whether personal information of the user is stored in the database, and generating information related to a first media content recommendation according to the personal information when the personal information of the user is stored in the database.

29. A media playing system, for executing a method of recommending media content as stated in claim 14 , the media playing system comprising:

a database;

a sensing device, for identifying a plurality of users in a viewing area, in order to generate an identifying result; and

a processing unit, for dividing the plurality of users into a first group and a second group according to the identifying result, and generating information related to a first media content recommendation according to personal information of each user in the first group;

wherein the personal information of each user in the first group is stored in the database, and personal information of each user in the second group is not stored in the database.