1. Technical Field
The present disclosure relates to social networks, and particularly to a social network capable of recommending friends and a friend recommendation method adapted for the social network.
2. Description of Related Art
Online social networks, such as FACEBOOK, TWITTER, and YOUTUBE, have become extremely popular and are attracting millions of users. Such social networks, which allow different users to communicate, share information, and build virtual communities, can recommend friends to the users based on whether they have common friend. However, such friend recommendation method cannot recommend friends to the users based on the photos that the users uploaded to the social networks.
Therefore, what is needed is a means to solve the problem described above.
Many aspects of the present disclosure should be better understood with reference to the following drawings. The modules in the drawings are not necessarily drawn to scale, the emphasis instead being placed upon clearly illustrating the principles of the present disclosure. Moreover, in the drawings, like reference numerals designate corresponding portions throughout the views.
In the embodiment, the system 100 includes an analyzing module 101, a combining module 102, a matching module 103, and a recommending module 104.
The analyzing module 101 obtains all the images uploaded to the social network 1 by each user, and determines an image fingerprint of each obtained image. In the embodiment, the analyzing module 101 automatically obtains all the images uploaded to the social network 1 by one user each time the user uploads an image. In an alternative embodiment, the analyzing module 101 obtains all the images uploaded to the social network 1 by one user upon receiving a command input by the user. In detail, the analyzing module 101 determines the image fingerprint of each obtained image by a Message Digest Algorithm 5 (MD5) checksum.
In the embodiment, the analyzing module 101 identifies the human faces included in each obtained image, and determines a binary sequence corresponding to each identified human face. The binary sequence corresponding to one identified human face indicates the features of the corresponding human face. Such a binary sequence determination method is known in the art, such as the subject matter of EP Application Publication No. 0150001 A2, which is herein incorporated by reference. The analyzing module 101 further determines that a combination of the binary sequence corresponding to each identified human face in each obtained image is the image fingerprint of each obtained image.
The combining module 102 determines that a combination of the image fingerprints of all the images uploaded by each user is the image character of the images uploaded by the user.
Referring to
The matching module 103 compares the determined image character with the stored image character of each to-be-recommended friend, and determines a similarity value between the determined image character and each stored image character according to the comparison result. In the embodiment, the matching module 103 compares the binary sequences in the determined image character with the binary sequences in each stored image character, and calculates the number of the same binary sequences between the determined image character and each stored image character. The determined number between the determined image character and the stored image character of one to-be-recommended friend indicates how many same human faces are included in the images uploaded by the user and the to-be-recommended friend. Then, the matching module 103 determines the similarity value between the determined image character and each stored image character according to the calculated number.
The recommending module 104 determines to recommend which of the to-be-recommended friends to one user according to the determined similarity values. In the embodiment, the recommending module 104 determines at least one stored image character with a highest similarity value relative to the determined image character, and recommends the to-be-recommended friend corresponding to the determined stored image character by sending personal information of the to-be-recommended friend to the user. The personal information of the to-be-recommended friend includes the registered information, such as the user name for example. In an alternative embodiment, the recommending module 104 may determine which of the determined similarity value between the determined image character and the stored image character is greater than a preset similarity value, and recommend at least one to-be-recommended friend to the user according to the determined result.
In the embodiment, the system 100 further includes an updating module 105. The updating module 105 stores the determined image character of images uploaded by the user to the storage unit 10 when the recommending module 104 has determined to recommend which of the to-be-recommended friends to the user, thereby updating the stored image characters in the storage unit 10.
In step S31, the analyzing module 101 obtains all the images uploaded to the social network 1 by each user, and determines an image fingerprint of each obtained image.
In step S32, the combining module 102 determines that a combination of the image fingerprints of all the images uploaded by each user is the image character of the images uploaded by the user.
In step S33, the matching module 103 compares the determined image character with the stored image character of each to-be-recommended friend, and determines a similarity value between the determined image character and each stored image character according to the comparison result.
In step S34, the recommending module 104 determines to recommend which of the to-be-recommended friends to one user according to the determined similarity values.
It is believed that the present embodiments and their advantages will be understood from the foregoing description, and it will be apparent that various changes may be made thereto without departing from the spirit and scope of the disclosure or sacrificing all of its material advantages, the examples hereinbefore described merely being exemplary embodiments of the present disclosure.
Number | Date | Country | Kind |
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2013104574246 | Sep 2013 | CN | national |