CN109064217A - Method, apparatus and electronic equipment are determined based on the core body strategy of user gradation - Google Patents
Method, apparatus and electronic equipment are determined based on the core body strategy of user gradation Download PDFInfo
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Abstract
The embodiment of the present application discloses a kind of core body strategy based on user gradation and determines method, apparatus and electronic equipment, this method comprises: requesting based on the current identity verification for target user, obtains the biological attribute data of target user；Biological attribute data based on default Rating Model and the target user, determines the user gradation of the target user；Wherein, the default Rating Model is that the biological attribute data training based on sample of users obtains；The identity verification strategy that the determining user gradation with the target user matches.
Description
Technical field
This application involves field of computer technology more particularly to a kind of core body strategy based on user gradation determine method,
Device and electronic equipment.
Background technique
With the development of Internet technology and computer technology, the website that can be provided services to the user and application program
(Application, APP) is more and more.The network operator of these websites or APP in order to attract new user and maintenance old user, meeting
User is divided to different user gradations, and uses different migration efficiencies for the user of different user grade, to mention
User's stickiness is improved while rising user experience.
Currently, these websites or APP, are based primarily upon usage behavior data of the user in website or APP, user etc. is carried out
The division of grade.For example, the website of vending articles can the consumer records such as recharge amount based on user and spending amount, carry out user
The division of grade；The outputs content such as article that some forum meetings are delivered based on user or model quantity, carries out drawing for user gradation
Point.
But there is no very strong direct passes by the rightful holder itself of consumer record or output content and user account
System, for example, it is assumed that the rightful holder of a user account is natural person A, if natural person B has been filled greatly using the user account
The money of amount has delivered many models, still can not change the fact that the user account belongs to natural person A.Also, because
For the usage behavior data in the corresponding user's usage behavior data of the user account including natural person B, cause according to the user
There is deviation in the user gradation that the corresponding user's usage behavior data of account mark off, can not really, natural person is directly described
A。
Summary of the invention
The embodiment of the present application provides a kind of core body strategy based on user gradation and determines method, apparatus and electronic equipment,
On the basis of accuracy to improve the user gradation determined, so that the identity verification strategy determined is more appropriate.
In order to solve the above technical problems, the embodiment of the present application is achieved in that
In a first aspect, proposing a kind of core body strategy based on user gradation determines method, comprising:
It is requested based on the current identity verification for target user, obtains the biological attribute data of target user；
Biological attribute data based on default Rating Model and the target user determines the user etc. of the target user
Grade；Wherein, the default Rating Model is that the biological attribute data training based on sample of users obtains；
The identity verification strategy that the determining user gradation with the target user matches.
Second aspect proposes a kind of core body strategy determination apparatus based on user gradation, comprising:
First obtains module, for requesting based on the current identity verification for target user, obtains the life of target user
Object characteristic；
User gradation determining module, for the biological attribute data based on default Rating Model and the target user, really
The user gradation of the fixed target user；Wherein, the default Rating Model is the biological attribute data instruction based on sample of users
It gets；
Core body strategy determining module, the identity verification plan to match for the determining user gradation with the target user
Slightly.
The third aspect proposes a kind of electronic equipment, comprising:
Processor；And
It is arranged to the memory of storage computer executable instructions, the executable instruction makes the place when executed
It manages device and executes following operation:
It is requested based on the current identity verification for target user, obtains the biological attribute data of target user；
Biological attribute data based on default Rating Model and the target user determines the user etc. of the target user
Grade；Wherein, the default Rating Model is that the biological attribute data training based on sample of users obtains；
The identity verification strategy that the determining user gradation with the target user matches.
Fourth aspect proposes a kind of computer readable storage medium, the computer-readable recording medium storage one
Or multiple programs, one or more of programs are when the electronic equipment for being included multiple application programs executes, so that the electricity
Sub- equipment executes following operation:
It is requested based on the current identity verification for target user, obtains the biological attribute data of target user；
Biological attribute data based on default Rating Model and the target user determines the user etc. of the target user
Grade；Wherein, the default Rating Model is that the biological attribute data training based on sample of users obtains；
The identity verification strategy that the determining user gradation with the target user matches.
As can be seen from the technical scheme provided by the above embodiments of the present application, scheme provided by the embodiments of the present application at least have as
Lower a kind of technical effect: since the biological attribute data of target user can really, directly describe the account of target user
Therefore the owner determines the user gradation of target user based on the biological attribute data of target user, can be improved and determine
The accuracy of user gradation, so that the identity verification strategy that the user gradation based on target user is determined is more appropriate.
Detailed description of the invention
The drawings described herein are used to provide a further understanding of the present application, constitutes part of this application, this Shen
Illustrative embodiments and their description please are not constituted an undue limitation on the present application for explaining the application.In the accompanying drawings:
Fig. 1 is a kind of implementation process that method is determined based on the core body strategy of user gradation that this specification embodiment provides
Schematic diagram.
Fig. 2 is the schematic illustration that method is determined based on the core body strategy of user gradation that this specification embodiment provides；
Fig. 3 is that the core body strategy based on user gradation that this specification embodiment provides determines that the another of method realizes stream
Journey schematic diagram；
Fig. 4 is the structural schematic diagram for a kind of electronic equipment that this specification embodiment provides.
Fig. 5 is a kind of structural representation for the core body strategy determination apparatus based on user gradation that this specification embodiment provides
Figure.
Fig. 6 is that another structure for the core body strategy determination apparatus based on user gradation that this specification embodiment provides is shown
It is intended to.
Specific embodiment
To keep the purposes, technical schemes and advantages of the application clearer, below in conjunction with the application specific embodiment and
Technical scheme is clearly and completely described in corresponding attached drawing.Obviously, described embodiment is only the application one
Section Example, instead of all the embodiments.Based on the embodiment in the application, those of ordinary skill in the art are not doing
Every other embodiment obtained under the premise of creative work out, shall fall in the protection scope of this application.
To improve the accuracy of user gradation determined, so that it is determined that going out more appropriate identity verification strategy, this explanation
Book embodiment provides a kind of core body strategy based on user gradation and determines method.This specification embodiment provide based on user etc.
The core body strategy of grade determines that the executing subject of method includes but is not limited to that server, PC etc. can be configured as executing sheet
At least one of the terminal of this method that inventive embodiments provide.
Fig. 1 is the process that method is determined based on the core body strategy of user gradation that one embodiment of this specification provides
Figure.
As shown in Figure 1, being requested based on the current identity verification for target user at step 102, obtaining target user
Biological attribute data.
It should be noted that in the present specification, core body is the abbreviation of identity verification, correspondingly, identity when core body is requested
Verify the abbreviation of request.
Target user is the user of user gradation to be determined, identity verification strategy to be determined or identity to be confirmed, herein
Place, the quantity of target user can be one, is also possible to multiple.
Biological characteristic is that the biologic-organ (such as face) of human body or index (such as eye spacing etc.) are produced by corresponding model
One group of vector out, the vector be it is interpretable be also possible to it is unaccountable.For example face characteristic, some model algorithms calculate
Vector out be it is interpretable, feature for example can be described as the appearance of the eyes of some user, eyes in human face region
Accounting etc.；And the calculated biological characteristic of deep learning model algorithm for occupying mainstream at present be usually it is unaccountable to
Amount.Involved biological characteristic in this specification embodiment, either interpretable, it is also possible to unaccountable.
Biological attribute data, including collectable biological information of human body, such as face, iris, fingerprint, eyeprint, ear line and the heart
One of data such as electrograph are a variety of.And the quantity of these biological attribute datas can be it is multiple, for example, work as collectable people
When body biological information is face, collected biological attribute data can be multiple facial images in a period of time etc., with
This analogizes.
In one example, the biological attribute data obtained in step 102 includes: face characteristic data；Wherein, the mesh
Mark includes one of following parameters or a variety of in the feature vector of user: the target user's got in preset period of time
The history recognition of face of the quantity of facial image, the quality of the facial image of the target user and the target user are quasi-
True degree, etc..
It in practical applications, can be in advance by the biological attribute data of collected different user, according to the biological characteristic
The quality etc. of biological characteristic contained by the user identifier of the owner of biological characteristic contained by data and the biological attribute data
Corresponding storage is in the preset database, wherein user identifier, such as can be User ID, more specifically, when user is China
When the citizen of continent, User ID, which can be user, to identify (such as identification card number) with identity card.
Also, since the application such as website or APP often acquires user when verifying user identity (for example, when logging in or paying)
Biological characteristic, therefore, on this basis, as an example, above-mentioned steps 102 may include: to obtain from presetting database
Take the history biological attribute data of the target user, the history biological attribute data be in history to the target user into
It is collected when row identity verification.
Optionally, as another example, above-mentioned steps 102 can also include: obtain the target user work as previous existence
Object characteristic, the current biological characteristic are acquired when being the current identity verification request for receiving the target user
's.It can be appreciated that the user gradation that the history biological attribute data and current biological characteristic of combining target user are determined
This scheme can further improve the use determined due to considering the real-time biological feature of target user
The accuracy of family grade.
On the basis of another example, optionally, a kind of core body plan based on user gradation that this specification provides
Slightly determine that method can also include: to save the current biological characteristic to the presetting database, to described default
The user biological characteristic of the target user stored in database carries out real-time update, so that being based on following step 104
The user gradation of the target user determined also being capable of real-time update.
At step 104, the biological attribute data based on default Rating Model and the target user determines the target
The user gradation of user.
Wherein, the default Rating Model is that the biological attribute data training based on sample of users obtains.
User gradation can be to preferably manage user or in order to provide a user personalized service, press certain
Standard distinguishes different users.Alternatively, user gradation can be for quantifying in the embodiment that this illustrates offer
The biological characteristic number and/or non-biometric data of definition user and these biological attribute datas and/or non-biometric number
According to confidence level a standard, provide concise foundation for the operation of Related product.For example, can by a certain website or
The user group of APP is in turn divided into four diamond, platinum, gold and silver ranks from high to low.
In one example, above-mentioned steps 104 may include: the biology based on default Rating Model and the target user
Characteristic determines the grade scoring of the target user；Based on the grade scoring of the target user, determine that the target is used
The user gradation at family.
In more detail, the biological attribute data based on default Rating Model and the target user, determine described in
The grade scoring of target user, comprising: the biological attribute data based on the target user determines the feature of the target user
Vector；Based on the feature vector of the default Rating Model and the target user, the grade scoring of the target user is determined；
Wherein, the default Rating Model is that the feature vector training based on sample of users obtains.
In one example, the grade scoring based on the target user determines the user etc. of the target user
Grade, can specifically include: the grade scoring based on the target user determines the ranking of the target user；Based on the mesh
The ranking (specifically can be the ranking in all users) for marking user, determines the user gradation of the target user.For example, can be with
User gradation by ranking in preceding 5% target user is determined as diamond, by target user of the ranking between 5%-20%
User gradation is determined as gold, the user gradation of target user of the ranking between 20%-50% is determined as silver, by ranking
The user gradation of target user between 50%-100% is determined as bronze, etc..
In another example, the grade scoring based on the target user, determines the user of the target user
Grade can specifically include: numberical range and the numberical range pair where the grade scoring based on the target user
User gradation is answered, determines the user gradation of the target user.For example, target user by grade scoring in [95,100]
User gradation is determined as diamond, the user gradation of target user of the grade scoring in [80,95] is determined as gold, by grade
The user gradation of target user of the scoring in [50,80] is determined as silver, by target user of the grade scoring in [0,50]
User gradation be determined as bronze.
Certainly, in practical applications, the grade scoring based on the target user determines the user etc. of the target user
The mode of grade is not limited to above-mentioned two example.
Optionally, in another example, a kind of core body strategy determination side based on user gradation that this specification provides
Method can also include: to obtain the non-biometric data of the target user；Correspondingly, above-mentioned steps 104 can specifically include:
Biological attribute data and non-biometric data based on default Rating Model and the target user, determine the target user
User gradation.At this point, above-mentioned default Rating Model, is biological attribute data and non-biometric data based on sample of users
What training obtained, correspondingly, features described above vector includes: the vector sum characterization non-biometric data for characterizing biological attribute data
Feature vector.
Wherein, the non-biometric data of target user may include that the usage behavior data of target user and target are used
One of data such as the essential information at family are a variety of.For example, target is used when target user is the user of a shopping APP
The usage behavior data at family can be the consumer record data of target user, specifically such as average daily or monthly average consumption amount of money, target
The essential information data of user can be subscriber identity information, social networks etc..Wherein, social networks can be friend relation
Or concern relation generated because mutually paying close attention to etc..
It should be noted that in the embodiment that this specification provides both mesh can be carried out according only to biological attribute data
Biological attribute data and non-biometric data can also be combined together and carry out user gradation by the division for marking user gradation
It divides.It is appreciated that can make really when combining biological attribute data and non-biometric data carry out the division of user gradation
The user gradation made can more comprehensively, target user is more directly described.And in the biological attribute data according only to target user
Determine the example of target user's grade (the biological attribute data training that default Rating Model is also based on sample of users obtains)
In, on the one hand, can obtain the user gradation determined can really, directly describe the effect of the owner of target user；
On the other hand, since the biological attribute data of target user can be acquired from presetting database under off-line state, and it is pre-
If Rating Model be in advance it is trained, therefore, in the case where not accessing internet, so that it may realize user gradation draw
Point, this is not only simple and easy for website or APP, but also can be reduced flow consumption.
It is appreciated that when training obtains the default Rating Model, it specifically can be based on having marked out grade scoring
Sample of users, and marked the feature vector of the sample of users of grade scoring and be trained, final goal be obtain one can
With the Rating Model to be scored using the biological attribute data of user and/or non-biometric data user.It can hereafter tie
It closes Fig. 2 and default Rating Model is obtained to training, and carry out user gradation and identity verification strategy (referred to as using the Rating Model
Core body strategy) determine process be illustrated, it is as detailed below.
At step 106, the identity verification strategy to match with the user gradation of the target user is determined.
It is existing below to be illustrated two kinds of concrete scenes present in identity verification scene respectively in order to facilitate citing, one
It kind is 1:1 scene, i.e., user, which inputs account (such as cell-phone number) etc., can indicate the data of oneself identity, by system from database
Middle its correspondence biological characteristic that extracts keeps (such as facial image is kept on file) on file, then the biological characteristic that the user of system acquisition is current
(such as the facial image shot by camera) keeps on file to be compared with biological characteristic, if degree of closeness is greater than default threshold
Value, then it is assumed that identity verification passes through, and does not otherwise pass through；Another kind is 1:N scene, i.e., user inputs less data or do not input
Data, system provide one group of alternative biological characteristic and keep on file, by system that collected biological characteristic and the alternative biology of the group is special
The biological characteristic levied in keeping on file keeps on file successively to compare, and selects one immediate (such as Euclidean distance is shortest), therefrom with right
The identity of target user is verified.
In this way, working as target user so that target user carries out check-in or the 1:N scene waited into railway station on airport as an example
When for advanced level user, the biological characteristic of the user in the biological characteristic of target user and advanced level user's set can be kept on file to carry out
One by one compare be determined as specific identity verification strategy, with find with the immediate user of target user, realize target user's
Identity verification.It can be appreciated that by target user only with advanced level user set in user be compared, rather than with all users
It is compared, the value range of N can be reduced, so as to improve the speed of user identity verification.
For another example, enter the application scenarios of the 1:N in railway station by brush face for user, acquisition device is collecting user A
Facial image after, can be compared one by one with a collection of face stored in database, it is (false after finding immediate face B
If similarity be 80%), based on the corresponding user identifier of face B determine face B user gradation be it is advanced, then can be by phase
It is greater than 90% like degree to be determined as to require to use accordingly to improve safety with the matched identity verification strategy of advanced level user
After family A ajusts posture, the facial image of user A is obtained again, and the facial image obtained again and face B are compared, if
Similarity is greater than 90% and lets pass；Otherwise it determines identity verification failure, not lets pass.
It optionally, can also be by 3 before the cell-phone number of target user or rear 4 and user connect in 1:N scene
The wireless network (WiFi) or location based service (Location Based Service, LBS) (such as geography fence) entered
Mode further reduces the range of N, further to promote the speed of user identity verification.
For another example, the 1:1 scene that payment APP is logged in for target user can when determining target user is advanced level user
With by higher comparison threshold value be determined as with the matched core body strategy of advanced level user, to improve payment safety.
In addition to check-in described in above-mentioned example, the application scenarios such as enter the station and log in, the embodiment of this specification Fig. 1 offer
Can also be applied to gate inhibition, on-line payment etc. needs the scene for carrying out identity verification and other needs to be selected according to user gradation
Select the scene (for example, preferential activity etc. on line) of migration efficiency.
A kind of core body strategy based on user gradation that embodiment shown in FIG. 1 provides determines method, due to biological characteristic
Data can really, directly describe the owner of the account of user, therefore, be determined based on the biological attribute data of target user
The accuracy for the user gradation determined can be improved in the user gradation of target user, so that the use based on target user
The identity verification strategy that family grade is determined is more appropriate, this also improves user's stickiness while promoting user experience.
The process of default Rating Model is obtained to training below with reference to Fig. 2, and is commented using the default Rating Model
The process divided is illustrated.
As shown in Fig. 2, in modeled segments 200:
Step 201, sampling is first carried out.
Specifically from the biological attribute data library 301 and non-biometric database 302 in storage section 300, respectively
Using user identifier as major key, extraction had marked some users as sample of users, while mixing the sample with the biological characteristic number at family
It is extracted according to non-biometric data.It wherein, may include face characteristic data, iris in biological attribute data library 301
Characteristic, eyeprint characteristic and fingerprint characteristic data etc., may include: in non-biometric database 302 behavioral data,
Social networks, consumer record and output content etc., the form for executing the data structure that step 201 sampling obtains can be such that
[
{ User ID, biological attribute data: { human face data collection: [human face data 1, human face data 2 ... ...], finger print data
Collection: [finger print data 1, finger print data 2 ... ...] ... ... },
Non-biometric data: { identity information: [name, native place, birthday ... ...], social networks: [...] ... ... }
... ...]
Execute step 203, selected characteristic.
Based on specifically biological attribute data and the non-biometric data of obtained sample of users being sampled by step 201
Calculate the feature vector of sample of users.
For example, for the face characteristic data acquisition system got, can be calculated from the feature that following feature is constituted to
Amount: in default historical period (such as nearly three months, nearly half a year or it is 1 year nearly in) the face picture quantity of sample of users, sample uses
The quality best result of the face picture at family, minimum point, average mark, standard deviation and sample of users face core body compare score value
Best result, minimum point, average mark and standard deviation etc..
Wherein, face core body compares score value, when can be using face characteristic comparison verification user identity, collected people
The similarity degree of face feature and the face characteristic prestored.
For the other biological characteristic set got, can extract and feature as face characteristic data class, tool
Body characteristics can determine that this specification is not listed one by one according to the characteristics of the biological attribute data.
For the non-biometric data got, such as the identity information of sample of users, sample can be extracted
Whether the identity information of user complete or degree of perfection, and whether with the features such as the comparison result of preset trust data；Again
Such as, for the consumer record of sample of users, features such as the average daily amount of consumption, etc. can be extracted, and so on.
All features that said extracted goes out are integrated, the feature vector of sample of users is finally obtained.
Execute step 205, training.
The feature vector for being specifically based on sample of users can train to obtain default Rating Model 303.It herein can be using prison
Superintend and direct formula modeling method (essence is a polytypic model training process), evidence weight (Weight of Evidence, WOE)
The methods of scorecard or cluster are modeled, and final goal is to obtain the biological attribute data and Fei Sheng that can use user
The Rating Model that object characteristic scores to user, namely above-mentioned default Rating Model 303 is obtained, in practical applications,
It needs to store default Rating Model 303, to apply the model in actual production environment.
Certainly, the trained method for obtaining above-mentioned default Rating Model can be not limited to above-mentioned several, can use other machines
Device learning method, or even determine several attributes artificially to formulate a Rating Model, for example, being preset when face picture quantity is greater than
Quantity (such as 20), and every quality is all that the user of " good " can be divided into advanced level user (such as diamond user).
Execute step 207, statistical distribution.
Specifically the grade scoring distribution of statistical sample user, the grade scoring finally obtained based on user determine user etc.
The rule of grade, specific rule can be defined according to actual needs.
As it was noted above, as an example, ranking can be determined as boring in the user gradation of preceding 5% target user
The user gradation of target user of the ranking between 5%-20% is determined as gold, by ranking between 20%-50% by stone
The user gradation of target user is determined as silver, and the user gradation of target user of the ranking between 50%-100% is determined as
Bronze, etc.；As another example, the user gradation of target user of the grade scoring in [95,100] can be determined as
The user gradation of target user of the grade scoring in [80,95] is determined as gold, by grade scoring in [50,80] by diamond
The user gradation of interior target user is determined as silver, and the user gradation of target user of the grade scoring in [0,50] is determined
For bronze.
It is the same with default Rating Model, the user gradation determined can also be determined that rule saves, so as in reality
Using determination rule in the production environment on border.
In short, with reference to Fig. 2 it is found that can train to obtain default scoring mould by several steps in modeled segments 200
Type, and determine that user gradation determines rule, and the respective stored space stored into storage section 300.
With continued reference to Fig. 2 it is found that in application obscure portions 400:
At step 401, it can receive the identity verification request of target user, mesh can be carried in identity verification request
Mark the current biological characteristic of user；Optionally, at step 401, current biological characteristic can also be saved to life
In object property data base 301.
At step 403, it can be calculated with the history biological attribute data and current biological characteristic of combining target user
The feature vector of target user；Certainly, at step 403, it can also be based only upon the history biological attribute data of target user, counted
Calculate the feature vector of target user；Alternatively, optionally, removed in step 403, it can also be by the history biological characteristic number of target user
It is combined together according to non-biometric data, calculates the feature vector of target user.
At step 405, the feature vector being calculated in step 403 can be inputted to default Rating Model, obtain mesh
Mark the grade scoring of user.
Optionally, in step 405, sequence comparison for convenience, can also be in default Rating Model to target user
Grade scoring be normalized.
At step 407, rule can be determined based on grade scoring combination user gradation calculated in step 405, really
Set the goal the user gradation of user.
Finally, can determine to close according to different application scenarios based on the user gradation determined at step 409
Suitable user identity verifies strategy.Certainly, based on the user gradation determined, the business game of other business can also be determined,
This specification is without limitation, here, only verifies this scene with user identity and illustrates.
Likewise, in the embodiment shown in Figure 2, since biological attribute data really, directly can describe user's
Therefore the owner of account determines the user gradation of target user based on the biological attribute data of target user, can be improved really
The accuracy for the user gradation made, so that the identity verification strategy that the user gradation based on target user is determined is more proper
When.
Optionally, as shown in figure 3, in another embodiment, a kind of core based on user gradation that this specification provides
Body strategy determines method, can also include the following steps:
Step 108 is based on the identity verification strategy, carries out identity verification to the target user.
The example in step 106 is continued to use, the 1:N scene for carrying out check-in on airport with target user or waiting into railway station
For, it, can be by the user's in the biological characteristic of target user and advanced level user's set when target user is advanced level user
Biological characteristic keeps on file compare one by one to be determined as specific identity verification strategy, to find and the immediate use of target user
The identity verification of target user is realized at family.It can be appreciated that target user is only compared with the user in advanced level user's set
It is right, rather than be compared with all users, the value range of N can be reduced, so as to improve the speed of user identity verification
Degree reduces false recognition rate.
For another example, enter the application scenarios of the 1:N in railway station by brush face for user, acquisition device is collecting user A
Facial image after, can be compared one by one with a collection of face stored in database, it is (false after finding immediate face B
If similarity be 80%), based on the corresponding user identifier of face B determine face B user gradation be it is advanced, then can be by phase
It is greater than 90% like degree to be determined as to require to use accordingly to improve safety with the matched identity verification strategy of advanced level user
After family A ajusts posture, the facial image of user A is obtained again, and the facial image obtained again and face B are compared, if
Similarity is greater than 90% and lets pass；Otherwise it determines identity verification failure, not lets pass.
For another example, the 1:1 scene that payment APP is logged in for target user can when determining target user is advanced level user
With by higher comparison threshold value be determined as with the matched core body strategy of advanced level user, to improve payment safety.
In addition to check-in described in above-mentioned example, the application scenarios such as enter the station and log in, the embodiment of this specification Fig. 3 offer
Can also be applied to gate inhibition, on-line payment etc. needs the scene for carrying out identity verification and other needs to be selected according to user gradation
Select the scene (for example, preferential activity etc. on line) of migration efficiency.
A kind of core body strategy based on user gradation that embodiment shown in Fig. 3 provides determines method, due to biological characteristic
Data can really, directly describe the owner of the account of user, therefore, be determined based on the biological attribute data of target user
The accuracy for the user gradation determined can be improved in the user gradation of target user, so that the user etc. based on target user
The identity verification strategy that grade is determined is more appropriate, so that being based on the identity verification strategy, carries out body to the target user
When part is verified, raising can be obtained and verify speed, raising safety or reduction false recognition rate and other effects.
Fig. 4 is the structural schematic diagram for the electronic equipment that one embodiment of this specification provides.Referring to FIG. 4, in hardware
Level, the electronic equipment include processor, optionally further comprising internal bus, network interface, memory.Wherein, memory can
It can include memory, such as high-speed random access memory (Random-Access Memory, RAM), it is also possible to further include non-easy
The property lost memory (non-volatile memory), for example, at least 1 magnetic disk storage etc..Certainly, which is also possible to
Including hardware required for other business.
Processor, network interface and memory can be connected with each other by internal bus, which can be ISA
(Industry Standard Architecture, industry standard architecture) bus, PCI (Peripheral
Component Interconnect, Peripheral Component Interconnect standard) bus or EISA (Extended Industry Standard
Architecture, expanding the industrial standard structure) bus etc..The bus can be divided into address bus, data/address bus, control always
Line etc..Only to be indicated with a four-headed arrow in Fig. 4, it is not intended that an only bus or a type of convenient for indicating
Bus.
Memory, for storing program.Specifically, program may include program code, and said program code includes calculating
Machine operational order.Memory may include memory and nonvolatile memory, and provide instruction and data to processor.
Processor is from the then operation into memory of corresponding computer program is read in nonvolatile memory, in logical layer
The core body strategy determination apparatus based on user gradation is formed on face.Processor executes the program that memory is stored, and specifically uses
The operation below executing:
It is requested based on the current identity verification for target user, obtains the biological attribute data of target user；
Biological attribute data based on default Rating Model and the target user determines the user etc. of the target user
Grade；Wherein, the default Rating Model is that the biological attribute data training based on sample of users obtains；
The identity verification strategy that the determining user gradation with the target user matches.
The core body strategy based on user gradation disclosed in the above-mentioned embodiment illustrated in fig. 1 such as this specification determines that method can answer
It is realized in processor, or by processor.Processor may be a kind of IC chip, the processing energy with signal
Power.During realization, each step of the above method can pass through the integrated logic circuit or software of the hardware in processor
The instruction of form is completed.Above-mentioned processor can be general processor, including central processing unit (Central Processing
Unit, CPU), network processing unit (Network Processor, NP) etc.；It can also be digital signal processor (Digital
Signal Processor, DSP), specific integrated circuit (Application Specific Integrated Circuit,
ASIC), field programmable gate array (Field-Programmable Gate Array, FPGA) or other programmable logic
Device, discrete gate or transistor logic, discrete hardware components.It may be implemented or execute this specification one or more
Disclosed each method, step and logic diagram in embodiment.General processor can be microprocessor or the processor
It can be any conventional processor etc..The step of method in conjunction with disclosed in this specification one or more embodiment, can be straight
Connect and be presented as that hardware decoding processor executes completion, or in decoding processor hardware and software module combination executed
At.Software module can be located at random access memory, and flash memory, read-only memory, programmable read only memory or electrically-erasable can
In the storage medium of this fields such as programmable memory, register maturation.The storage medium is located at memory, and processor reads storage
Information in device, in conjunction with the step of its hardware completion above method.
The core body strategy based on user gradation that the electronic equipment can also carry out Fig. 1 determines method, and this specification is herein not
It repeats again.
Certainly, other than software realization mode, other implementations are not precluded in the electronic equipment of this specification, such as
Logical device or the mode of software and hardware combining etc., that is to say, that the executing subject of following process flow is not limited to each
Logic unit is also possible to hardware or logical device.
This specification embodiment also proposed a kind of computer readable storage medium, the computer-readable recording medium storage
One or more programs, the one or more program include instruction, and the instruction is when by the portable electric including multiple application programs
When sub- equipment executes, the method that the portable electronic device can be made to execute embodiment illustrated in fig. 1, and be specifically used for executing following
Operation:
It is requested based on the current identity verification for target user, obtains the biological attribute data of target user；
Biological attribute data based on default Rating Model and the target user determines the user etc. of the target user
Grade；Wherein, the default Rating Model is that the biological attribute data training based on sample of users obtains；
The identity verification strategy that the determining user gradation with the target user matches.
Fig. 5 is the structural schematic diagram for the core body strategy determination apparatus 500 based on user gradation that this specification provides.It please join
Fig. 5 is examined, in a kind of Software Implementation, the core body strategy determination apparatus 500 based on user gradation can include: first obtains mould
Block 501, user gradation determining module 502 and core body strategy determining module 503.
First obtains module 501, for requesting based on the current identity verification for target user, obtains target user's
Biological attribute data.
Optionally, as an example, described first module 501 is obtained, can be used for from presetting database described in acquisition
The history biological attribute data of target user, the history biological attribute data are to carry out identity to the target user in history
It is collected when verification.
Optionally, as another example, described first module 501 is obtained, can be used for obtaining working as the target user
Preceding biological attribute data, the current biological characteristic are to receive the current identity verification request when institute of the target user
Acquisition.
Optionally, as another example, device 500 can also include: memory module, for the current biological is special
Sign data are saved to the presetting database.
Optionally, as another example, above-mentioned biological attribute data include: face, iris, fingerprint, eyeprint, ear line and
One of ECG data is a variety of, and more specifically, the biological attribute data includes: face characteristic data；Wherein, institute
State includes one of following parameters or a variety of in the feature vector of target user: the target got in preset period of time is used
The history face of the quantity of the facial image at family, the quality of the facial image of the target user and the target user are known
Other order of accuarcy.
User gradation determining module 502, for the biological attribute data based on default Rating Model and the target user,
Determine the grade scoring of the target user；Wherein, the default Rating Model is the biological attribute data based on sample of users
What training obtained.
Optionally, in one example, user gradation determining module 502 can be used for based on default Rating Model and described
The biological attribute data of target user determines the grade scoring of the target user；Based on the grade scoring of the target user,
Determine the user gradation of the target user.
More specifically, in one example, user gradation determining module 502 can be used for based on the target user's
Biological attribute data determines the feature vector of the target user；Based on the default Rating Model and the target user
Feature vector determines the grade scoring of the target user；Wherein, the default Rating Model is the feature based on sample of users
Vector training obtains.
More specifically, in another example, user gradation determining module 502 can be used for based on the target user
Grade scoring, determine the ranking of the target user；Based on the ranking of the target user, the use of the target user is determined
Family grade.
Optionally, in another example, device 500 can also include: the second acquisition module, for obtaining the target
The non-biometric data of user.Wherein, the grade scoring determining module is specifically used for based on default Rating Model and described
The biological attribute data and non-biometric data of target user, determines the grade scoring of the target user, at this point, described pre-
If Rating Model is that the biological attribute data and the training of non-biometric data based on sample of users obtain.
Core body strategy determining module 503, the identity verification to match for the determining user gradation with the target user
Strategy.
Core body strategy determination apparatus shown in fig. 5 based on user gradation, since biological attribute data can be true, direct
Ground describes the owner of the account of user, therefore, the user etc. of target user is determined based on the biological attribute data of target user
Grade, can be improved the accuracy for the user gradation determined, so that the body that the user gradation based on target user is determined
It is more appropriate that part verifies strategy.
As shown in fig. 6, in another embodiment, a kind of core body strategy based on user gradation that this specification provides is true
Determine device 500, can also include: identity verification module 504.
Identity verification module 504 carries out identity verification to the target user for being based on the identity verification strategy.
A kind of core body strategy determination apparatus based on user gradation that embodiment shown in fig. 6 provides, due to biological characteristic
Data can really, directly describe the owner of the account of user, therefore, be determined based on the biological attribute data of target user
The accuracy for the user gradation determined can be improved in the user gradation of target user, so that the user etc. based on target user
The identity verification strategy that grade is determined is more appropriate, so that being based on the identity verification strategy, carries out body to the target user
When part is verified, raising can be obtained and verify speed, raising safety or reduction false recognition rate and other effects.
The method that core body strategy determination apparatus 500 based on user gradation can be realized the embodiment of the method for Fig. 1, specifically may be used
Method is determined with reference to the core body strategy based on user gradation of embodiment illustrated in fig. 1, is repeated no more.
In short, being not intended to limit the protection of this specification the foregoing is merely the preferred embodiment of this specification
Range.With within principle, made any modification, changes equivalent replacement all spirit in this specification one or more embodiment
Into etc., it should be included within the protection scope of this specification one or more embodiment.
System, device, module or the unit that above-described embodiment illustrates can specifically realize by computer chip or entity,
Or it is realized by the product with certain function.It is a kind of typically to realize that equipment is computer.Specifically, computer for example may be used
Think personal computer, laptop computer, cellular phone, camera phone, smart phone, personal digital assistant, media play
It is any in device, navigation equipment, electronic mail equipment, game console, tablet computer, wearable device or these equipment
The combination of equipment.
Computer-readable medium includes permanent and non-permanent, removable and non-removable media can be by any method
Or technology come realize information store.Information can be computer readable instructions, data structure, the module of program or other data.
The example of the storage medium of computer includes, but are not limited to phase change memory (PRAM), static random access memory (SRAM), moves
State random access memory (DRAM), other kinds of random access memory (RAM), read-only memory (ROM), electric erasable
Programmable read only memory (EEPROM), flash memory or other memory techniques, read-only disc read only memory (CD-ROM) (CD-ROM),
Digital versatile disc (DVD) or other optical storage, magnetic cassettes, tape magnetic disk storage or other magnetic storage devices
Or any other non-transmission medium, can be used for storage can be accessed by a computing device information.As defined in this article, it calculates
Machine readable medium does not include temporary computer readable media (transitory media), such as the data-signal and carrier wave of modulation.
It should also be noted that, the terms "include", "comprise" or its any other variant are intended to nonexcludability
It include so that the process, method, commodity or the equipment that include a series of elements not only include those elements, but also to wrap
Include other elements that are not explicitly listed, or further include for this process, method, commodity or equipment intrinsic want
Element.When not limiting more, the element that is limited by sentence "including a ...", it is not excluded that in the mistake including the element
There is also other identical elements in journey, method, commodity or equipment.
All the embodiments in this specification are described in a progressive manner, same and similar portion between each embodiment
Dividing may refer to each other, and each embodiment focuses on the differences from other embodiments.Especially for system reality
For applying example, since it is substantially similar to the method embodiment, so being described relatively simple, related place is referring to embodiment of the method
Part explanation.
Claims (13)
1. a kind of core body strategy based on user gradation determines method, comprising:
It is requested based on the current identity verification for target user, obtains the biological attribute data of target user；
Biological attribute data based on default Rating Model and the target user, determines the user gradation of the target user；
Wherein, the default Rating Model is that the biological attribute data training based on sample of users obtains；
The identity verification strategy that the determining user gradation with the target user matches.
2. according to the method described in claim 1, the biological characteristic number based on default Rating Model and the target user
According to determining the user gradation of the target user, comprising:
Biological attribute data based on default Rating Model and the target user, determines the grade scoring of the target user；
Based on the grade scoring of the target user, the user gradation of the target user is determined.
3. according to the method described in claim 2, the biological characteristic number based on default Rating Model and the target user
According to determining the grade scoring of the target user, comprising:
Based on the biological attribute data of the target user, the feature vector of the target user is determined；
Based on the feature vector of the default Rating Model and the target user, the grade scoring of the target user is determined；
Wherein, the default Rating Model is that the feature vector training based on sample of users obtains.
4. according to the method described in claim 3, the biological attribute data includes: face characteristic data；
Wherein, include one of following parameters or a variety of in the feature vector of the target user:
The quantity of the facial image of the target user got in preset period of time,
The quality of the facial image of the target user, and
The history recognition of face order of accuarcy of the target user.
5. according to the method described in claim 2, the grade scoring based on the target user, determines the target user
User gradation, comprising:
Based on the grade scoring of the target user, the ranking of the target user is determined；
Based on the ranking of the target user, the user gradation of the target user is determined.
6. according to the method described in claim 1, the characteristic for obtaining target user, comprising:
The history biological attribute data of the target user is obtained from presetting database, the history biological attribute data is to go through
It is collected when in history to target user progress identity verification.
7. according to the method described in claim 6, the characteristic for obtaining target user, further includes:
Obtain the current biological characteristic of the target user, the current biological characteristic is to receive described to work as predecessor
Part is verified collected when request.
8. according to the method described in claim 7, the method also includes:
The current biological characteristic is saved to the presetting database.
9. method according to claim 1-8, the method also includes:
Obtain the non-biometric data of the target user；
Wherein, the biological attribute data based on default Rating Model and the target user, determines the target user's
Grade scoring, comprising:
Biological attribute data and non-biometric data based on default Rating Model and the target user, determine the target
The grade scoring of user, the default Rating Model are biological attribute data and non-biometric data instruction based on sample of users
It gets.
10. method according to claim 1-8, the method also includes:
Based on the identity verification strategy, identity verification is carried out to the target user.
11. a kind of core body strategy determination apparatus based on user gradation, comprising:
First obtains module, and for being requested based on the current identity verification for target user, the biology for obtaining target user is special
Levy data；
User gradation determining module determines institute for the biological attribute data based on default Rating Model and the target user
State the user gradation of target user；Wherein, the default Rating Model is that the biological attribute data based on sample of users is trained
It arrives；
Core body strategy determining module, the identity verification strategy to match for the determining user gradation with the target user.
12. a kind of electronic equipment, comprising:
Processor；And
It is arranged to the memory of storage computer executable instructions, the executable instruction makes the processor when executed
Execute following operation:
It is requested based on the current identity verification for target user, obtains the biological attribute data of target user；
Biological attribute data based on default Rating Model and the target user, determines the user gradation of the target user；
Wherein, the default Rating Model is that the biological attribute data training based on sample of users obtains；
The identity verification strategy that the determining user gradation with the target user matches.
13. a kind of computer readable storage medium, the computer-readable recording medium storage one or more program, described one
A or multiple programs are when the electronic equipment for being included multiple application programs executes, so that the electronic equipment executes following behaviour
Make:
It is requested based on the current identity verification for target user, obtains the biological attribute data of target user；
Biological attribute data based on default Rating Model and the target user, determines the user gradation of the target user；
Wherein, the default Rating Model is that the biological attribute data training based on sample of users obtains；
The identity verification strategy that the determining user gradation with the target user matches.
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