User identity determining method, apparatus, and device

1. A user identity determining method, comprising:

acquiring target multidimensional feature information of a target user, wherein the target multidimensional feature information comprises at least two types of feature information in at least one of biometric feature information or non-biometric feature information;

comparing the target multidimensional feature information with multidimensional feature information of a plurality of designated users, respectively, to obtain a comparison result; and

determining an identity of the target user based on the comparison result,

wherein the comparing the target multidimensional feature information with multidimensional feature information of a plurality of designated users, respectively, to obtain a comparison result comprises:

determining a plurality of index features of the target user based on the target multidimensional feature information, wherein each of the plurality of index features of the target user is a feature uniquely identifying original feature information in the target multidimensional feature information and having a data amount less than that of the original feature information;

sorting the plurality of index features of the target user into a ranked sequence; and

comparing, after the sorting, the plurality of index features of the target user with a plurality of index features of the plurality of designated users, respectively, to determine a plurality of first users from the plurality of designated users to obtain the comparison result.

2. The method according to claim 1 , wherein the comparing the target multidimensional feature information with multidimensional feature information of a plurality of designated users, respectively, to obtain a comparison result further comprises:

comparing the target multidimensional feature information with the multidimensional feature information of the plurality of designated users, respectively, to obtain similarity values of the target user with respect to the plurality of designated users; and

determining the similarity values of the target user with respect to the plurality of designated users as the comparison result.

3. The method according to claim 2 , wherein the determining an identity of the target user based on the comparison result comprises:

determining an identity of a user corresponding to a largest similarity value which is greater than a preset threshold in the comparison result as the identity of the target user.

4. The method according to claim 1 , wherein the comparing the target multidimensional feature information with multidimensional feature information of a plurality of designated users, respectively, to obtain a comparison result further comprises:

comparing particular feature information in the target multidimensional feature information with particular feature information of the plurality of first users, respectively, for determining similarity values of the target user with respect to the plurality of first users; and

determining the similarity values of the target user with respect to the plurality of first users as the comparison result.

5. The method according to claim 4 , wherein the plurality of index features comprise at least one of: a single index feature for a same type of feature information, a composite index feature for at least two types of feature information occurring at a same time, or a composite index feature for feature information of different users occurring at a same time.

6. The method according to claim 4 , wherein

the biometric feature information comprises at least one of: face feature information, body feature information, gait feature information, cloth feature information, age feature information, or gender feature information; and

the non-biometric feature information comprises at least one of: user identification (ID) information, geographical location information, or time information,

wherein the user ID information comprises one or more of a user mobile phone number, a user identity number, and user mobile phone media access control (MAC) information.

7. The method according to claim 6 , wherein when the target multidimensional feature information comprises geographical location information of the target user, the determining a plurality of index features of the target user based on the target multidimensional feature information comprises:

determining a level 1 geographical location index feature of the target user based on the geographical location information of the target user;

determining the level 1 geographical location index feature and a level 2 geographical location index feature of the target user based on the geographical location information of the target user; or

determining the level 1 geographical location index feature, the level 2 geographical location index feature, and a level 3 geographical location index feature of the target user based on the geographical location information of the target user;

wherein the level 3 geographical location index feature is a subindex of the level 2 geographical location index, and the level 2 geographical location index is a subindex of the level 1 geographical location index.

8. The method according to claim 6 , wherein when the target multidimensional feature information comprises biometric feature information of the target user, the determining the plurality of index features of the target user based on the target multidimensional feature information comprises:

performing a principal component analysis (PCA) on the biometric feature information of the target user to obtain reduced-dimensionality features of the biometric feature information;

bucketizing the reduced-dimensionality features in a plurality of buckets representing the biometric feature information; and

determining IDs of the plurality of buckets as the plurality of index features of the target user.

9. The method according to claim 1 , wherein the comparing the target multidimensional feature information with multidimensional feature information of a plurality of designated users, respectively, to obtain a comparison result further comprises:

selecting a plurality of second users from the plurality of first users based on historical behavior data of the plurality of first users;

comparing particular feature information in the target multidimensional feature information with particular feature information of the plurality of second users, respectively, and determining similarity values of the target user with respect to the plurality of second users; and

determining the similarity values of the target user with respect to the plurality of second users as the comparison result.

10. A user identity determining apparatus, comprising:

a processor; and

a memory configured to store instructions, wherein the processor is configured to execute the instructions to:

acquire target multidimensional feature information of a target user, wherein the target multidimensional feature information comprises at least two types of feature information in at least one of biometric feature information or non-biometric feature information;

compare the target multidimensional feature information with multidimensional feature information of a plurality of designated users, respectively, to obtain a comparison result; and

determine an identity of the target user based on the comparison result,

wherein in comparing the target multidimensional feature information with multidimensional feature information of a plurality of designated users, respectively, to obtain a comparison result, the processor is further configured to execute the instructions to:

determine a plurality of index features of the target user based on the target multidimensional feature information, wherein each of the plurality of index features of the target user is a feature uniquely identifying original feature information in the target multidimensional feature information and having a data amount less than that of the original feature information;

sort the plurality of index features of the target user into a ranked sequence; and

compare, after the sorting, the plurality of index features of the target user with a plurality of index features of the plurality of designated users, respectively, to determine a plurality of first users from the plurality of designated users to obtain the comparison result.

11. The apparatus according to claim 10 , wherein the processor is further configured to execute the instructions to:

compare the target multidimensional feature information with the multidimensional feature information of the plurality of designated users, respectively, to obtain similarity values of the target user with respect to the plurality of designated users; and

determine the similarity values of the target user with respect to the plurality of designated users as the comparison result.

12. The apparatus according to claim 10 , wherein the processor is further configured to execute the instructions to:

compare particular feature information in the target multidimensional feature information with particular feature information of the plurality of first users, respectively, for determining similarity values of the target user with respect to the plurality of first users; and

determine the similarity values of the target user with respect to the plurality of first users as the comparison result.

13. The apparatus according to claim 12 , wherein the plurality of index features comprise at least one of: a single index feature for a same type of feature information, a composite index feature for at least two types of feature information occurring at a same time, or a composite index feature for feature information of different users occurring at a same time.

14. The apparatus according to claim 10 , wherein the processor is further configured to execute the instructions to:

select a plurality of second users from the plurality of first users based on historical behavior data of the plurality of first users;

compare particular feature information in the target multidimensional feature information with particular feature information of the plurality of second users, respectively, and determine similarity values of the target user with respect to the plurality of second users; and

determine the similarity values of the target user with respect to the plurality of second users as the comparison result.

15. A non-transitory computer-readable storage medium storing one or more instructions that, when executed by a processor of an electronic device, cause the electronic device to perform:

acquiring target multidimensional feature information of a target user, wherein the target multidimensional feature information comprises at least two types of feature information in at least one of biometric feature information or non-biometric feature information;

comparing the target multidimensional feature information with multidimensional feature information of a plurality of designated users, respectively, to obtain a comparison result; and

determining an identity of the target user based on the comparison result,

wherein the comparing the target multidimensional feature information with multidimensional feature information of a plurality of designated users, respectively, to obtain a comparison result comprises:

determining a plurality of index features of the target user based on the target multidimensional feature information, wherein each of the plurality of index features of the target user is a feature uniquely identifying original feature information in the target multidimensional feature information and having a data amount less than that of the original feature information;

sorting the plurality of index features of the target user into a ranked sequence; and

comparing, after the sorting, the plurality of index features of the target user with a plurality of index features of the plurality of designated users, respectively, to determine a plurality of first users from the plurality of designated users to obtain the comparison result.

16. The non-transitory computer-readable storage medium according to claim 15 , wherein the one or more instructions further cause the electronic device to perform:

comparing the target multidimensional feature information with the multidimensional feature information of the plurality of designated users, respectively, to obtain similarity values of the target user with respect to the plurality of designated users; and

determining the similarity values of the target user with respect to the plurality of designated users as the comparison result.

17. The non-transitory computer-readable storage medium according to claim 15 , wherein the one or more instructions further cause the electronic device to perform:

comparing particular feature information in the target multidimensional feature information with particular feature information of the plurality of first users, respectively, for determining similarity values of the target user with respect to the plurality of first users; and

determining the similarity values of the target user with respect to the plurality of first users as the comparison result.

18. The non-transitory computer-readable storage medium according to claim 17 , wherein the plurality of index features comprise at least one of: a single index feature for a same type of feature information, a composite index feature for at least two types of feature information occurring at a same time, or a composite index feature for feature information of different users occurring at a same time.

19. The non-transitory computer-readable storage medium according to claim 15 , wherein the one or more instructions further cause the electronic device to perform:

selecting a plurality of second users from the plurality of first users based on historical behavior data of the plurality of first users;

comparing particular feature information in the target multidimensional feature information with particular feature information of the plurality of second users, respectively, and determining similarity values of the target user with respect to the plurality of second users; and

determining the similarity values of the target user with respect to the plurality of second users as the comparison result.