Occupational identity verification method and system

Abstract

The occupational identity authentication method and system provided in this specification, after receiving a occupational identity authentication request, the occupational identity authentication request includes a candidate occupational identity of a target user to be verified and a verification scenario corresponding to the target user, selects at least one verification process from the candidate verification process based on the verification scenario to obtain a target verification method corresponding to the candidate occupational identity, and uses the target verification method to verify the candidate occupational identity of the target user, and outputs a verification result; this scheme can improve the verification efficiency of occupational identities.

Description

Technical Field

[0001] This specification relates to the field of data processing, and in particular to a method and system for professional identity verification. Background Art

[0002] In recent years, with the rapid development of Internet technology, marketing methods have become more and more diverse. For example, businesses provide benefits corresponding to specific professions for marketing. In this type of marketing method, it is often necessary to verify the user's professional identity. Existing professional identity verification methods can often be verified by manual verification. For example, for student identities, official platforms such as China Higher Education Student Information and Career Center can be used for verification, and so on.

[0003] During the research and practice of the prior art, the inventors of the present application found that the existing identity authentication methods are often relatively simple, and are more prone to the risk of verification failure in different verification scenarios. Moreover, the efficiency of manual verification is too low. In addition, not every profession has an official certification platform, which makes the categories of professions that can be verified relatively limited. Therefore, the verification efficiency of professional identity authentication is low.

[0004] Therefore, there is a need to provide a professional identity verification method and system with higher verification efficiency. Summary of the invention

[0005] This specification provides a method and system for professional identity verification with higher verification efficiency.

[0006] In a first aspect, the present specification provides a method for professional identity authentication, comprising: receiving a professional identity authentication request, the professional identity authentication request including a candidate professional identity of a target user to be verified and a verification scenario corresponding to the target user; based on the verification scenario, selecting at least one verification process from the candidate verification process to obtain a target verification method corresponding to the candidate professional identity; and verifying the candidate professional identity of the target user using the target verification method, and outputting a verification result.

[0007] In some embodiments, based on the verification scenario, at least one verification process is selected from the candidate verification processes to obtain a target verification method corresponding to the candidate professional identity, including: based on the verification scenario, determining a target verification accuracy corresponding to the candidate professional identity of the target user; based on the target verification accuracy, selecting at least one verification process from the candidate verification processes; and combining the at least one verification process to obtain a target verification method corresponding to the candidate professional identity.

[0008] In some embodiments, selecting at least one verification process from the candidate verification processes based on the target verification accuracy includes: obtaining a verification accuracy range corresponding to each verification process in the candidate verification processes; matching the target verification accuracy with the verification accuracy range; and selecting at least one verification process from the candidate verification processes based on the matching result.

[0009] In some embodiments, the candidate verification process includes at least one of official verification, big data cross-validation, visual model verification, and user commitment self-verification.

[0010] In some embodiments, the verification accuracies corresponding to the official verification, the big data cross-validation, the visual model verification, and the user commitment self-validation respectively decrease in sequence.

[0011] In some embodiments, the official verification is performed for the candidate occupation identity authentication of the target user, including: obtaining the identity information of the target user and sending the identity information to a occupational certificate authentication server; receiving the occupational certificate information of the target user returned by the occupational certificate authentication server; and inputting the occupational certificate information into the occupational map to obtain the verification result of the candidate occupation identity of the target user.

[0012] In some embodiments, the big data cross-validation is performed for the candidate career identity verification of the target user, including: obtaining user attribute information of the target user, and extracting target user data of multiple dimensions from the user attribute information; inputting the target user data of the multiple dimensions into the career map respectively to obtain verification information corresponding to the target user data of each dimension; and cross-validating the candidate career identity of the target user based on the verification information to obtain a verification result of the candidate career identity of the target user.

[0013] In some embodiments, the target user data includes at least one of the target user's location information, user portrait, social security information, social information, transaction information, and tax information.

[0014] In some embodiments, the visual model verification is performed for the candidate occupation identity verification of the target user, including: obtaining the occupation authentication image of the target user and performing image verification on the occupation authentication image; when the occupation authentication image verification passes, performing image recognition on the occupation authentication image; and inputting the recognition result of the occupation authentication image into the occupational map to obtain the verification result of the candidate occupation identity of the target user.

[0015] In some embodiments, performing image recognition on the occupational authentication image includes: performing text detection on the occupational authentication image; when the occupational authentication image includes text, identifying text content in the occupational authentication image; and determining the image authentication type of the occupational authentication image based on the text content, and using the image authentication type as the recognition result of the occupational authentication image.

[0016] In some embodiments, it also includes: when the occupational authentication image does not include the text, extracting image features of the occupational authentication image; and determining the image content of the occupational authentication image based on the extracted image features, and using the image content as the recognition result of the occupational authentication image.

[0017] In some embodiments, the user commitment self-certification is performed for the candidate occupation identity verification of the target user, including: obtaining user commitment information of the target user for the candidate occupation identity, linking the user commitment information with the credit information of the target user; and determining that the candidate occupation identity verification of the target user is passed based on the user commitment information, and taking the passed verification as the verification result.

[0018] In some embodiments, obtaining the user commitment information of the target user for the candidate professional identity includes: obtaining the credit information of the target user; and when the credit information meets a preset credit condition, obtaining the user commitment information of the target user for the candidate professional identity.

[0019] In some embodiments, after determining the verification result of the candidate professional identity of the target user based on the user commitment information, it also includes: when it is detected that the candidate professional identity authentication of the target user fails or the target user has risky behavior corresponding to the candidate professional identity, adjusting the credit information of the target user.

[0020] In some embodiments, the adjusting the credit information of the target user includes: determining an adjustment method for the credit information based on the user commitment information; and adjusting the credit information of the target user based on the adjustment method to impose credit punishment on the target user.

[0021] In some embodiments, the execution order of at least one verification process in the target verification method includes executing the verification process in order from large to small according to the verification accuracy of the verification process, and when the currently executed verification process does not output a verification result, executing the next verification process.

[0022] In some embodiments, the use of the target verification method to verify the candidate career identity of the target user includes: based on the execution order, executing at least one verification process in the target verification method to verify the candidate career identity of the target user.

[0023] In some embodiments, the verification result is associated with the professional rights and interests corresponding to the candidate professional identity of the target user, and the professional rights and interests include at least one authority corresponding to the candidate professional identity.

[0024] In a second aspect, the present specification also provides a professional identity authentication system, comprising: at least one storage medium storing at least one instruction set for performing professional identity authentication; and at least one processor communicatively connected to the at least one storage medium, wherein, when the professional identity authentication system is running, the at least one processor reads the at least one instruction set and executes the professional identity authentication method described in the first aspect of this specification according to the instructions of the at least one instruction set.

[0025] It can be seen from the above technical scheme that the occupational identity authentication method and system provided in this specification, after receiving a occupational identity authentication request, the occupational identity authentication request includes a candidate occupational identity of a target user to be verified and a verification scenario corresponding to the target user, and based on the verification scenario, selects at least one verification process in the candidate verification process to obtain a target verification method corresponding to the candidate occupational identity, and uses the target verification method to verify the candidate occupational identity of the target user, and outputs the verification result; since the scheme does not require manual review, the target verification method corresponding to the candidate occupational identity can be dynamically constructed based on the verification scenario, so that different verification methods can be used in different verification scenarios, thereby improving the success rate and accuracy of identity authentication, and there is no restriction on the occupational identities that can be verified, therefore, the verification efficiency of occupational identities can be improved.

[0026] Other features of the identity verification method and system provided by this specification will be partially listed in the following description. Based on the description, the contents introduced by the following figures and examples will be obvious to those of ordinary skill in the art. The creative aspects of the professional identity verification method and system provided by this specification can be fully explained by practicing or using the methods, devices and combinations described in the following detailed examples. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] In order to more clearly illustrate the technical solutions in the embodiments of this specification, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this specification. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0028] Figure 1 A schematic diagram of an application scenario of a professional identity verification system provided according to an embodiment of this specification is shown;

[0029] Figure 2 A hardware structure diagram of a computing device provided according to an embodiment of this specification is shown;

[0030] Figure 3 A flow chart of a method for professional identity verification provided according to an embodiment of this specification is shown;

[0031] Figure 4 A schematic diagram of the structure of a data intelligent identity authentication framework provided according to an embodiment of this specification is shown;

[0032] Figure 5 A schematic diagram of a product flow of professional identity verification provided according to an embodiment of this specification is shown; and

[0033] Figure 6 A schematic diagram of a framework of a professional identity verification product provided according to an embodiment of this specification is shown. DETAILED DESCRIPTION

[0034] The following description provides specific application scenarios and requirements of this specification, with the purpose of enabling those skilled in the art to make and use the contents of this specification. Various local modifications to the disclosed embodiments will be apparent to those skilled in the art, and the general principles defined herein may be applied to other embodiments and applications without departing from the spirit and scope of this specification. Therefore, this specification is not limited to the embodiments shown, but to the widest scope consistent with the claims.

[0035] The terms used herein are only used for the purpose of describing specific example embodiments and are not restrictive. For example, unless the context clearly indicates otherwise, as used herein, the singular forms "a", "an" and "the" may also include plural forms. When used in this specification, the terms "include", "comprise" and / or "contain" mean that the associated integers, steps, operations, elements and / or components exist, but do not exclude the existence of one or more other features, integers, steps, operations, elements, components and / or groups or that other features, integers, steps, operations, elements, components and / or groups may be added in the system / method.

[0036] In view of the following description, these and other features of the present specification, as well as the operation and function of the related elements of the structure, and the economy of the combination and manufacture of the parts can be significantly improved. Reference is made to the accompanying drawings, all of which form a part of this specification. However, it should be clearly understood that the drawings are for illustration and description purposes only and are not intended to limit the scope of this specification. It should also be understood that the drawings are not drawn to scale.

[0037] The flowcharts used in this specification illustrate the operations implemented by the system according to some embodiments in this specification. It should be clearly understood that the operations of the flowcharts may not be implemented in sequence. On the contrary, the operations may be implemented in reverse order or simultaneously. In addition, one or more other operations may be added to the flowchart. One or more operations may be removed from the flowchart.

[0038] For the convenience of description, this manual will explain the terms that will appear in the following description as follows:

[0039] Data intelligence: A technical means, mainly through big data analysis, occupational knowledge graph (hereinafter referred to as occupational graph) and official data sources, multiple data channels are combined into a data intelligence model as a technical guarantee for occupational identity identification. The occupational graph may include a knowledge graph related to occupational identity (occupational information), through which the user's occupational identity can be determined.

[0040] Occupational identity: It can be understood as an identity related to an occupation in the usual sense, for example, it can include doctors, teachers, engineers, lawyers, electricians, welders or cleaners, etc.

[0041] Occupational identity verification: Verify the user's specific occupational identity. While ensuring that the occupational identity is authentic and reliable, the user can obtain corresponding occupational benefits or privileges, etc.

[0042] Before describing the specific embodiments of this specification, the application scenarios of this specification are first introduced as follows:

[0043] The occupational identity verification method provided in this specification can be applied in any occupational identity verification scenario. For example, in an occupational access verification scenario, the occupational identity verification method of this specification can be used to verify the occupational identity of a user who needs to be verified. Alternatively, in an occupational marketing scenario, the occupational identity verification method of this specification can be used to verify the candidate occupational identity of a user who needs to be verified sent by a merchant, and the verification result can be sent to the merchant so that when the user's occupational identity verification is passed, the user can be granted specific rights and interests corresponding to the occupational identity. Alternatively, it can also be applied in any occupational identity verification scenario, which will not be described one by one here.

[0044] Those skilled in the art should understand that the occupational identity verification method and system described in this specification applied to other usage scenarios are also within the protection scope of this specification.

[0045] Figure 1 The following is a schematic diagram of an application scenario of a professional identity verification system 001 provided according to an embodiment of the present specification. The professional identity verification system 001 (hereinafter referred to as system 001) can be applied to professional identity verification in any scenario, such as professional identity verification in a professional access verification scenario, professional identity verification in a professional marketing scenario, etc. Figure 1 As shown, system 001 may include a target user 100 , a client 200 , a server 300 , and a network 400 .

[0046] The target user 100 may be a user that triggers verification of the candidate occupational identity of the target user. The target user 100 may perform an operation of occupational identity verification on the client 200 .

[0047] The client 200 may be a device for verifying the candidate professional identity of the target user in response to the professional identity verification operation of the target user 100. In some embodiments, the professional identity verification method may be executed on the client 200. At this time, the client 200 may store data or instructions for executing the professional identity verification method described in this specification, and may execute or be used to execute the data or instructions. In some embodiments, the client 200 may include a hardware device with a data information processing function and a necessary program required to drive the hardware device to work. Figure 1As shown, the client 200 can be connected to the server 300 for communication. In some embodiments, the server 300 can be connected to multiple clients 200 for communication. In some embodiments, the client 200 can interact with the server 300 through the network 400 to receive or send messages, etc. In some embodiments, the client 200 may include a mobile device, a tablet computer, a laptop computer, a built-in device of a motor vehicle, or the like, or any combination thereof. In some embodiments, the mobile device may include a smart home device, a smart mobile device, a virtual reality device, an augmented reality device, or the like, or any combination thereof. In some embodiments, the smart home device may include a smart TV, a desktop computer, etc., or any combination thereof. In some embodiments, the smart mobile device may include a smart phone, a personal digital assistant, a gaming device, a navigation device, etc., or any combination thereof. In some embodiments, the virtual reality device or the augmented reality device may include a virtual reality helmet, virtual reality glasses, a virtual reality patch, an augmented reality helmet, augmented reality glasses, an augmented reality patch, or the like, or any combination thereof. For example, the virtual reality device or the augmented reality device may include Google Glass, a head-mounted display, VR, etc. In some embodiments, the built-in device in the motor vehicle may include an onboard computer, an onboard TV, etc. In some embodiments, the client 200 may include an image acquisition device for acquiring user data of the target user. In some embodiments, the image acquisition device may be a two-dimensional image acquisition device (such as an RGB camera), or may be a two-dimensional image acquisition device (such as an RGB camera) and a depth image acquisition device (such as a 3D structured light camera, a laser detector, etc.). In some embodiments, the client 200 may be a device with positioning technology for locating the position of the client 200.

[0048] In some embodiments, the client 200 may be installed with one or more application programs (APPs). The APP can provide the target user 110 with the ability and interface to interact with the outside world through the network 400. The APP includes but is not limited to: web browser APP programs, search APP programs, chat APP programs, shopping APP programs, video APP programs, financial management APP programs, instant messaging tools, email clients, social platform software, etc. In some embodiments, a target APP may be installed on the client 200. The target APP can collect user data of the target user for the client 200. In some embodiments, the target object 100 can also trigger a professional identity authentication request through the target APP. The target APP can respond to the professional identity authentication request and execute the professional identity authentication method described in this specification. The professional identity authentication method will be described in detail in the following content.

[0049] The server 300 may be a server that provides various services, such as a background server that provides professional identity authentication support for the target users collected on the client 200. In some embodiments, the professional identity authentication method may be executed on the server 300. At this time, the server 300 may store data or instructions for executing the professional identity authentication method described in this specification, and may execute or be used to execute the data or instructions. In some embodiments, the server 300 may include a hardware device with a data information processing function and a necessary program required to drive the hardware device to work. The server 300 may be connected to multiple clients 200 for communication and receive data sent by the client 200.

[0050] The network 400 is used to provide a medium for communication connection between the client 200 and the server 300. The network 400 can facilitate the exchange of information or data. Figure 1 As shown, the client 200 and the server 300 can be connected to the network 400 and transmit information or data to each other through the network 400. In some embodiments, the network 400 can be any type of wired or wireless network, or a combination thereof. For example, the network 400 can include a cable network, a wired network, an optical fiber network, a telecommunications network, an intranet, the Internet, a local area network (LAN), a wide area network (WAN), a wireless local area network (WLAN), a metropolitan area network (MAN), a wide area network (WAN), a public switched telephone network (PSTN), a Bluetooth TM Network, ZigBee TM Network, near field communication (NFC) network or similar network. In some embodiments, network 400 may include one or more network access points. For example, network 400 may include a wired or wireless network access point, such as a base station or an Internet exchange point, through which one or more components of client 200 and server 300 can connect to network 400 to exchange data or information.

[0051] It should be understood that Figure 1 The number of the client 200, server 300 and network 400 in the embodiment is only for illustration. According to the implementation requirements, there may be any number of the client 200, server 300 and network 400.

[0052] It should be noted that the occupational identity authentication method may be completely executed on the client 200 , may be completely executed on the server 300 , or may be partially executed on the client 200 and partially executed on the server 300 .

[0053] Figure 2The hardware structure diagram of a computing device 600 provided according to an embodiment of the present specification is shown. The computing device 600 can execute the occupational identity authentication method described in the present specification. The occupational identity authentication method is introduced in other parts of the present specification. When the occupational identity authentication method is executed on the client 200, the computing device 600 can be the client 200. When the occupational identity authentication method is executed on the server 300, the computing device 600 can be the server 300. When the occupational identity authentication method can be partially executed on the client 200 and partially executed on the server 300, the computing device 600 can be the client 200 and the server 300.

[0054] like Figure 2 As shown, the computing device 600 may include at least one storage medium 630 and at least one processor 620. In some embodiments, the computing device 600 may further include a communication port 650 and an internal communication bus 610. Meanwhile, the computing device 600 may further include an I / O component 660.

[0055] The internal communication bus 610 may connect various system components, including the storage medium 630 , the processor 620 , and the communication port 650 .

[0056] I / O components 660 support input / output between computing device 600 and other components.

[0057] The communication port 650 is used for data communication between the computing device 600 and the outside world. For example, the communication port 650 can be used for data communication between the computing device 600 and the network 400. The communication port 650 can be a wired communication port or a wireless communication port.

[0058] The storage medium 630 may include a data storage device. The data storage device may be a non-temporary storage medium or a temporary storage medium. For example, the data storage device may include one or more of a disk 632, a read-only storage medium (ROM) 634, or a random access storage medium (RAM) 636. The storage medium 630 also includes at least one instruction set stored in the data storage device. The instruction is a computer program code, and the computer program code may include a program, a routine, an object, a component, a data structure, a process, a module, etc. for executing the occupational identity authentication method provided in this specification.

[0059] At least one processor 620 can be connected to at least one storage medium 630 and a communication port 650 through an internal communication bus 610. At least one processor 620 is used to execute the at least one instruction set mentioned above. When the computing device 600 is running, at least one processor 620 reads the at least one instruction set and executes the occupational identity verification method provided in this specification according to the instructions of the at least one instruction set. The processor 620 can execute all the steps included in the occupational identity verification method. The processor 620 can be in the form of one or more processors. In some embodiments, the processor 620 can include one or more hardware processors, such as a microcontroller, a microprocessor, a reduced instruction set computer (RISC), an application-specific integrated circuit (ASIC), an application-specific instruction set processor (ASIP), a central processing unit (CPU), a graphics processing unit (GPU), a physical processing unit (PPU), a microcontroller unit, a digital signal processor (DSP), a field programmable gate array (FPGA), an advanced RISC machine (ARM), a programmable logic device (PLD), any circuit or processor capable of performing one or more functions, etc., or any combination thereof. For illustration purposes only, only one processor 620 is described in the computing device 600 in this specification. However, it should be noted that the computing device 600 in this specification may also include multiple processors, and therefore, the operations and / or method steps disclosed in this specification may be performed by one processor as described in this specification, or may be performed jointly by multiple processors. For example, if the processor 620 of the computing device 600 in this specification performs step A and step B, it should be understood that step A and step B may also be performed jointly or separately by two different processors 620 (for example, the first processor performs step A, the second processor performs step B, or the first and second processors perform steps A and B together).

[0060] Figure 3 1 shows a flowchart of a method P100 for professional identity authentication provided according to an embodiment of the present specification. As before, the computing device 600 can execute the method P100 for professional identity authentication of the present specification. Specifically, the processor 620 can read the instruction set stored in its local storage medium, and then execute the method P100 for professional identity authentication of the present specification according to the provisions of the instruction set. Figure 3 As shown, method P100 may include:

[0061] S110: Receive a professional identity verification request.

[0062] Among them, the occupational identity verification request is a request for verifying the candidate occupational identity of the target user triggered by the service provider (merchant) or the target user who needs to be verified. The occupational identity verification request includes the candidate occupational identity of the target user who needs to be verified and the verification scenario corresponding to the target user. The target user may be a user interacting with the service provider (merchant). The candidate occupational identity may be the occupational identity that needs to be verified. It should be noted that the candidate occupational identity may include one or more occupational identities. The verification scenario may be a scenario where occupational identity verification is required. For example, the merchant is an air ticket service provider, and the air ticket service provider launches a marketing campaign for doctors (for example, doctors enjoy specific discounts when purchasing air tickets, etc.). The target user may be a consumer who participates in the marketing campaign. At this time, the candidate occupational identity may be a doctor, and the verification scenario may be a scenario where the air ticket service provider needs to verify whether the consumer's occupational identity is a doctor.

[0063] There are multiple ways to receive a professional identity verification request, which can be as follows:

[0064] For example, the processor 620 may receive a professional identity verification request sent by the service provider through a terminal or server, or may receive a professional identity verification request triggered and generated at a terminal corresponding to the target user after the target user participates in a professional marketing activity of the service provider, and so on.

[0065] S120: Based on the verification scenario, at least one verification process is selected from the candidate verification processes to obtain a target verification method corresponding to the candidate professional identity.

[0066] Among them, the verification process can be a process for verifying the professional identity. It should be noted that each verification process can independently realize the verification of the professional identity, that is, each verification process can be an independent professional identity authentication method, but the verification accuracy of each verification process is different. The candidate verification process may include at least one of official verification, big data cross-verification, visual model verification and user commitment self-verification. The official verification can be obtained through the official data query platform or the official verification platform to obtain data for verification. For example, the verification of student identity can be verified by querying the information of the China Higher Education Student Information and Career Center, etc. The big data cross-verification can be cross-verified through multiple data of the target user. The visual model verification can be used to verify the candidate professional identity of the target user through visual recognition methods such as text recognition or image recognition. For example, the professional certificate provided by the target user (for example, teacher's certificate, lawyer's certificate, electrician's certificate, graduation certificate, etc.) can be identified by OCR (optical character recognition). Based on the recognition result, the candidate professional identity of the target user is verified. The user's self-commitment can be a commitment by the user to the professional identity that needs to be verified, and the target user's own professional identity is committed as a candidate professional identity. The commitment here can be a credit commitment, thereby indirectly completing the verification of the candidate professional identity of the target user. The credit commitment can be a user's commitment linked to the user's credit information. If fraud or risky behavior occurs, it will be linked to the user's information level (credit punishment methods such as lowering the credit level). In addition, it should be noted that the verification accuracy corresponding to the official verification, big data cross-validation, visual model verification and user commitment self-verification in the four verification processes decreases in turn, that is to say, the verification accuracy of the official verification is the highest, and the verification accuracy of the user's commitment self-verification is the lowest. The current verification accuracy of the four verification processes can include the range of 80%-100%, or it can be within other accuracy ranges. The specific execution process of the four verification processes can be described in detail below.

[0067] The target verification method may be a verification method corresponding to the verification scenario. The verification method may be understood as a method for verifying the candidate occupation identity of the target user by combining one or more verification processes. Therefore, the target verification method may include one or more verification processes.

[0068] Among them, based on the verification scenario, there are multiple methods for selecting at least one verification process from the candidate verification processes to obtain the target verification method corresponding to the candidate professional identity, which can be specifically as follows:

[0069] For example, processor 620 can determine the target verification accuracy corresponding to the candidate professional identity of the target user based on the verification scenario, select at least one verification process from the candidate verification process based on the target verification accuracy, and combine at least one verification process to obtain the target verification method corresponding to the candidate professional identity.

[0070] Among them, the target verification accuracy can be the verification accuracy required by the merchant or service provider in the current verification scenario. The verification accuracy of different verification scenarios can be different. For example, taking the verification scenario as a graduate student admission verification as an example, it is necessary to verify whether the user is a student (undergraduate). At this time, the verification accuracy needs to be particularly accurate (the verification accuracy requirement is close to 100%). Taking the verification scenario as a power bank rental, the merchant launches a discount activity for a takeaway rider to rent a power bank as an example. At this time, it is necessary to verify whether the user is a takeaway rider, but the verification accuracy at this time does not need to be the same as the accuracy required by the graduate student admission verification scenario. Based on the verification scenario, there can be many ways to determine the target verification accuracy corresponding to the candidate professional identity of the target user. For example, the processor 620 can select the verification accuracy corresponding to the verification scenario from the preset verification accuracy set to obtain the target verification accuracy, or, based on the verification scenario, determine the verification level of the candidate professional identity of the target user, and select the verification accuracy corresponding to the verification level from the preset verification accuracy set to obtain the target verification accuracy, and so on.

[0071] After determining the target verification accuracy corresponding to the candidate occupational identity of the target user, the processor 620 can select at least one verification process from the candidate verification processes based on the target verification accuracy. There are many ways to select at least one verification process from the candidate verification processes. For example, the processor 620 can obtain the current verification accuracy corresponding to each verification process in the candidate verification process, match the target verification accuracy with the current verification accuracy, and select at least one verification process from the candidate verification process based on the matching result.

[0072] Among them, the current verification accuracy can be a verification accuracy range, and the verification accuracy range can be an accuracy interval when the verification process performs professional identity verification, for example, it can be 85%-90%, or any other interval. There can be multiple ways to match the target verification accuracy with the current verification accuracy. For example, the processor 620 can compare the target verification accuracy with the verification accuracy range of the current verification accuracy. The verification accuracy range that includes the target verification accuracy can be considered to be successfully matched with the target verification accuracy. For example, taking the target verification accuracy as 85% as an example, the verification accuracy range can be considered to be a successful match with the target verification accuracy. Alternatively, when the minimum value of the verification accuracy range is greater than or equal to the target verification accuracy, it can be determined that the current verification accuracy corresponding to the verification accuracy range is successfully matched with the target verification accuracy. For example, taking the target verification accuracy as 85% as an example, when the minimum value of the verification accuracy range is greater than or equal to 85%, the current verification accuracy corresponding to the verification accuracy range can be successfully matched with the target verification accuracy.

[0073] In some embodiments, the current verification accuracy can also be a predicted verification accuracy value or accuracy probability. Taking the current verification accuracy as 85% as an example, when the target verification accuracy is less than or equal to 85%, it can be determined that the current verification accuracy successfully matches the target verification accuracy.

[0074] After matching the target verification accuracy with the current verification accuracy, the processor 620 may select at least one verification process corresponding to the current verification accuracy that successfully matches the target verification accuracy from the candidate verification processes.

[0075] After selecting at least one verification process from the candidate verification processes, the processor 620 may combine the at least one verification process to obtain a target verification method corresponding to the candidate occupation identity. The combination here may be combining at least one verification process in an execution order to obtain a target verification method.

[0076] Among them, the execution order of at least one verification process in the target verification method includes executing in sequence from large to small according to the accuracy of the verification process, and when the currently executed verification process does not output the verification result, the next verification process is executed. For example, taking the target verification method including official verification, big data cross-validation, visual model verification and user commitment self-verification as an example, the official verification is performed first. When the official verification does not output the verification result, the big data cross-validation is continued. When the big data cross-validation does not output the verification result, the visual model verification is continued. When the visual model verification does not output the verification result, the user commitment self-verification is continued, thereby completing the entire target verification method. Once a verification process outputs a verification result, the next verification process of the verification process will stop executing. The specific process of the processor 620 executing each verification process for the candidate occupation identity authentication of the target user will be described in detail below:

[0077] (1) Official Verification

[0078] For example, for the target user's candidate occupation identity authentication, the process of processor 620 performing official verification may include obtaining the target user's identity information, sending the identity information to a career certificate authentication server, receiving the target user's career certificate information returned by the career certificate authentication server, and inputting the career certificate information into the career map to obtain a verification result of the target user's candidate occupation identity.

[0079] The identity information may be information representing the identity of the target user, for example, may include the identity identifier, ID, or other information that may represent the identity of the target user, and so on.

[0080] Among them, the professional certificate authentication server can be understood as a server or platform that officially provides professional certificates for user authentication. For example, taking the user's identity information as the student ID, the professional certificate authentication server can be the official server or platform corresponding to the China Higher Education Student Information and Career Center.

[0081] Among them, the professional certificate information can be the information of the officially certified certificate obtained by the target user, for example, it can include a teacher qualification certificate, a degree certificate, a graduation certificate, an XXX engineer certificate, etc. There can be multiple ways to input the professional certificate information into the professional map to obtain the verification result of the candidate professional identity of the target user. For example, the processor 620 can input the professional certificate information into the professional map, and when the target professional identity of the target user outputted by the professional map is obtained, the target professional identity is compared with the candidate professional identity. When the target professional identity is the same as the candidate professional identity, the verification result is that the candidate professional identity of the target user has passed the verification. When the target professional identity is different from the candidate professional identity, the verification result is that the candidate professional identity of the target user has failed the verification. When the target professional identity of the target user outputted by the professional map is not obtained, it is determined that the official verification method has not output a verification result.

[0082] (2) Big Data Cross-Validation

[0083] For example, for the candidate career identity verification of the target user, the process of the processor 620 performing big data cross-validation may include obtaining the user attribute information of the target user, and extracting target user data of multiple dimensions from the user attribute information, and outputting the target user data of multiple dimensions to the career map respectively to obtain verification information corresponding to the target user data of each dimension, and cross-validating the candidate career identity of the target user based on the verification information to obtain a verification result of the candidate career identity of the target user.

[0084] The target user data includes at least one of the target user's location information, user portrait, social security information, social information, transaction information and tax information.

[0085] Among them, the verification information may include the target occupational identity of the target user corresponding to each dimension of the occupational map output. Based on the verification information, there may be multiple ways to cross-verify the candidate occupational identities of the target user. For example, the processor 620 may extract the target occupational identity of the target user corresponding to each dimension in the verification information, and compare the target occupational identity with the candidate occupational identity, obtain the target number of target occupational identities that are the same as the candidate occupational identity, and when the target number exceeds a preset number threshold or the ratio between the target number and the total number of target occupational identities exceeds a preset ratio, determine that the verification result is passed, otherwise the verification result is failed; or, the target occupational identity may be classified, and based on the number of each type of target occupational identity, the target occupational identity with the largest number is selected from the target occupational identities as the current occupational identity, and the current occupational verification identity is compared with the candidate occupational identity, and when the current occupational verification identity is the same as the candidate occupational identity, determine that the verification result is passed, otherwise the verification result is failed, and so on.

[0086] (3) Visual model verification

[0087] For example, for the candidate occupation identity verification of the target user, the process of the processor 620 performing visual model verification may include obtaining the target user's occupational authentication image, and performing image verification on the occupational authentication image. After the occupational authentication image verification passes, image recognition is performed on the occupational authentication image, and the recognition result of the occupational authentication image is input into the occupational map to obtain the verification result of the candidate occupation identity of the target user.

[0088] The occupational authentication image may be an image used by the target user for occupational authentication, for example, it may include images or videos of various occupational certificates (e.g., journalist certificate, nurse certificate, or tour guide certificate, etc.), and may also include videos or images related to the target user's work environment or work, etc. The processor 620 performs image verification on the occupational authentication image mainly to perform anti-fraud verification on the occupational authentication image, and the anti-fraud verification is mainly used to verify whether the occupational authentication image is modified, forged, or subjected to various fraudulent acts.

[0089] When the occupational authentication image passes the verification, the processor 620 can identify the occupational authentication image. The processor 620 can identify the occupational authentication image in a variety of ways, for example, the processor 620 can perform text detection on the occupational authentication image, identify the text content in the occupational authentication image when the occupational authentication image contains text, and determine the image authentication type of the occupational authentication image based on the text content, and use the image authentication type as the recognition result of the occupational authentication image; or, when the occupational authentication image does not include text, perform image feature extraction on the occupational authentication image, and determine the image content of the occupational authentication image based on the extracted image features, and use the image content as the recognition result of the occupational authentication image.

[0090] Among them, when the occupational certification image contains text, it means that the occupational certification image may be a occupational certificate. For this type of occupational certificate, it is necessary to use OCR technology to identify the text content in the occupational certification image and use the text content as the recognition result of the occupational certification image; when the occupational certification image does not contain text, it means that the occupational certification certificate may be the target user's working environment or work-related images. For this type of occupational certification image, it is necessary to identify the image content in the occupational certification image, which may be the working environment, work content or work-related content of the XXX unit, and these image contents may be used as the recognition result of the occupational certification image.

[0091] After performing image recognition on the occupational authentication image, the processor 620 can input the recognition result of the occupational authentication image into the occupational map, thereby obtaining the verification result of the candidate occupational identity of the target user. The method of determining the verification result of the candidate occupational identity of the target user through the occupational map is described above in detail and will not be repeated here.

[0092] (4) User promises to prove themselves

[0093] For example, for the candidate occupation identity verification of the target user, the process of the processor 620 performing visual model verification may include obtaining the user commitment information of the target user regarding the candidate occupation identity, and based on the user commitment information, determining that the candidate occupation identity verification of the target user has passed, and taking the passed verification as the verification result.

[0094] The user commitment information is linked to the target user's credit information. The so-called linkage can be understood as after the target user submits the user commitment information, once the target user has fraudulent or risky behavior, the target user will be subject to credit punishment. The specific punishment method may include lowering the target user's credit level or credit score, etc. The processor 620 may obtain the target user's user commitment information for the candidate professional identity in a variety of ways. For example, the processor 620 may obtain the target user's credit information, and when the credit information meets the preset credit conditions, obtain the target user's user commitment information for the candidate professional identity.

[0095] Among them, credit information can be understood as information for evaluating the credit of the target user, for example, it can include personal credit information or other information for evaluating credit determined by trading platforms based on big data, etc. There are many ways for the processor 620 to obtain the credit information of the target user. For example, the processor 620 can obtain the credit information of the target user from the official credit platform and use the credit information as the credit information of the target user, or it can also determine the credit information of the target user based on the transaction information of the target user in the business system or other information that can evaluate the credit of the target user, etc.

[0096] After obtaining the credit information of the target user, the processor 620 can obtain the user commitment information of the target user for the candidate professional identity when the credit information meets the preset credit condition. The preset credit condition can be a pre-set credit condition, for example, taking the information as a credit level as an example, the credit condition can be that the credit level reaches a preset credit level, or taking the credit information as a credit score as an example, the credit condition can be that the credit score reaches a preset credit score, and so on.

[0097] After acquiring the user commitment information of the target user regarding the candidate occupation identity, the processor 620 can determine that the candidate occupation identity verification of the target user has been passed, and take the verification pass as the verification result.

[0098] In some embodiments, after determining the verification result of the target user's candidate professional identity based on the user's commitment information, the processor 620 may also adjust the target user's credit information. For example, when the processor 620 detects that the target user's candidate professional identity authentication fails or the target user has risky behaviors corresponding to the candidate professional identity, the processor 620 adjusts the target user's credit information.

[0099] After the processor 620 determines that the candidate professional identity verification of the target user has been passed based on the user commitment information, it outputs a single verification result, and then, it will periodically or irregularly adopt at least one of the other verification processes to continue to verify the candidate professional identity of the target user. In addition to continuing to verify the candidate professional identity of the target user, it will also perform risk detection on the target user's interactive behavior or transaction behavior. When it is detected that the candidate professional identity verification of the target user has not been passed or the target user has risky behaviors corresponding to the candidate professional identity, the credit information of the target user is adjusted.

[0100] Among them, there are many ways for the processor 620 to adjust the credit information of the target user. For example, the processor 620 can determine the adjustment method of the credit information based on the user's commitment information, and adjust the credit information of the target user based on the adjustment method to impose credit punishment on the target user.

[0101] The adjustment method may be an adjustment method for the credit information of the target user. Taking the credit information as a credit score as an example, the adjustment method here can be understood as the adjustment range or adjustment value of the credit adjustment, for example, it may include a decrease of 5 points or an increase of 5 points, etc. The adjustment range or adjustment value may be determined based on the risk level or frequency of the risk behavior, may be determined based on the frequency of verification failures, may be preset based on actual applications, etc.

[0102] After determining the adjustment method of the credit information, the processor 620 can adjust the credit information of the target user based on the adjustment method to impose credit punishment on the target user. The credit punishment can be a punishment on the target user in terms of user credit. There can be multiple ways of credit punishment, such as lowering the credit level / rating, lowering the credit score, or adding punishment information to the credit information, etc. The processor 620 can adjust the credit information of the target user based on the adjustment method in multiple ways. For example, taking the credit information as the credit score and the adjustment method as reducing 5 points as an example, the processor 620 can reduce the credit score of the target user by 5 points based on the adjustment method, thereby implementing credit punishment on the target user, or taking the credit information as the credit level, the higher the credit level, the higher the credit of the target user, and the adjustment method as reducing one credit level as an example, the processor 620 can reduce the credit level of the target user by one credit level based on the adjustment method, thereby implementing credit punishment on the target user.

[0103] It should be noted that the four verification processes together constitute the data intelligent identity authentication framework, which can be specifically described as follows: Figure 4 As shown, in the scenario of professional identity verification, model verification (verification) or official channel verification (verification) can be dynamically selected according to the actual situation. The official verification process can support more than 6,800 official verification certificates, thereby realizing multi-scenario and multi-precision professional identity verification. Moreover, visual model verification and big data cross-verification can be used to ensure that the professional identity of the target user can still be accurately identified when the official channel is unavailable. The visual model verification accumulates more than 20 types of visual verification certificate templates, and the comparison and identification are carried out in the form of information forms. In addition, the user's self-commitment verification process can be used to combine professional identity verification with credit evaluation. The user can initiate the commitment on his own initiative, and the credit guarantee is provided for risky behaviors and fraudulent behaviors, so as to realize more diversified verification of professional identity, thereby improving the user's professional identity verification efficiency.

[0104] S130: Verify the candidate occupational identity of the target user using a target verification method, and output the verification result.

[0105] There are many ways to verify the candidate occupation identity of the target user by using the target verification method, which can be as follows:

[0106] For example, the processor 620 may execute at least one verification process in the target verification method based on the execution order to verify the candidate occupation identity of the target user.

[0107] Among them, the execution order includes executing in order from large to small according to the verification accuracy of the verification process, and when the currently executed verification process does not output the verification result, the next verification process is executed. Taking the target verification method including official verification, big data cross-validation, visual model verification and user commitment self-verification as an example, the processor 620 can verify the candidate professional identity of the target user in a variety of ways based on the execution order. For example, the processor 620 uses the official verification process to verify the candidate professional identity of the target user. If the official verification process outputs the verification result, the execution of the remaining three verification processes can be stopped. If the official verification process does not output the verification result, the big data cross-validation process can be continued. If the big data cross-validation process outputs the verification result, the execution of the remaining two verification processes can be stopped. If the big data cross-validation process does not output the verification result, the visual model verification process can be continued. If the visual model verification process outputs the verification result, the execution of the remaining one verification process can be stopped. If the visual model does not output the verification result, the user commitment self-verification process can be continued to obtain the verification result of the candidate professional identity of the target user. The verification result here may include verification passed and verification failed. The verification passed means that the target user's professional identity is a candidate professional identity, and the verification failed means that the target user's professional identity is not a candidate professional identity.

[0108] It should be noted that the target verification method may include at least one verification process. When the target verification method includes multiple verification processes, the processor 620 may also execute multiple verification processes simultaneously. For example, when the target verification method includes both official verification and big data cross-verification, the processor 620 may also execute these two processes simultaneously, and based on the results output by these two processes, comprehensively judge the verification result of the candidate professional identity of the target user. If these two verification processes do not output the verification results or the verification fails, the remaining verification processes may continue to be executed.

[0109] After verifying the candidate professional identity of the target user, the processor 620 can output the verification result of the candidate professional identity of the target user. The verification result is associated with the professional rights and interests corresponding to the candidate professional identity of the target user, and the professional rights and interests include at least one authority corresponding to the candidate professional identity. For example, a merchant launches a marketing campaign, and doctors can enjoy discounts when buying air tickets. At this time, the professional rights and interests can be the authority to enjoy discounts on air tickets, etc. There are many ways to output the verification result. For example, the processor 620 can directly output the verification result to the merchant corresponding to the triggering professional identity authentication request, so that the merchant can grant the target user the professional rights and interests corresponding to the candidate professional identity based on the verification result, or the verification result can be output to the target user so that the target user can show the verification result to the merchant, so that the merchant can grant the target user the professional rights and interests corresponding to the candidate professional identity based on the verification result, or the verification result can be output to a third-party verification platform, and the verification result is sent to the target user and the merchant through the third-party verification platform, so that the target user can enjoy the professional rights and interests corresponding to the candidate professional identity in the merchant based on the verification result, etc.

[0110] Among them, in the identity authentication scenario, the overall process of professional identity authentication may include: the cooperative merchant (cooperator) provides specific professional identity rights and interests, and connects to the professional identity authentication platform (product); after the partner user performs the partner's applet or app, the professional identity authentication is performed, and the processor 620 of the professional identity authentication platform can evoke the verification module (at least one verification process) of the professional identity authentication product, and perform identity authentication through the verification module. Taking the verification module as an example, the verification module can include official verification, big data cross-verification, visual model verification and user commitment self-verification, and the official verification and big data cross-verification can be performed simultaneously, the processor 620 can comprehensively judge the credibility of the professional identity through the big data cross-verification model and the official channel verification, and use the visual model verification for supplementary verification for users whose identities cannot be determined. In addition, the user's credit commitment can be attached. If fraud or risky behavior occurs, it will be linked to the credit level of the user's credit, etc., so as to obtain the verification result. Through this solution, the verification capability of 6000+ professional identities can be realized, and professional verification can be dynamically added. In addition, incremental user data can be effectively collected in a legal and compliant manner, and the big data cross-verification capability can be further improved, thereby improving the accuracy and efficiency of identity authentication, etc.

[0111] Among them, taking the identity authentication scenario as the verification scenario of the medical card (professional rights) in which the ticket service provider (merchant) provides exclusive identity services for medical staff, the target verification method is official verification, big data cross-verification, visual model verification and user commitment self-verification, and official verification and big data cross-verification can be performed at the same time. For example, the product process for verifying the user's medical (hospital, nurse or hospital staff) identity can be as follows Figure 5 As shown, after the user enters the mini program or APP of the merchant through the user terminal, the application for the Zunyi Card is triggered. The processor 620 performs risk detection on the user status. When the user status detection fails, the user terminal displays a schematic diagram of the closing page, and the processor 620 stops the identity authentication process. When the user status detection passes, the user terminal can display the authorization page. When the user triggers the authorization operation, the processor 620 performs official verification and big data cross-verification to comprehensively judge the identity credibility of the user as a medical staff, and determines the verification result based on the identity credibility. When the verification passes, the user terminal can display the application page for the successful application of the Zunyi Card. When the verification fails, the user terminal can display the identity information supplement page, which can include a waiver verification control and an information supplement control. In response to the user's triggering operation on the information supplement control, the user terminal can display the content upload page, and the user terminal uploads the supplemented identity information through the content upload page. The processor 620 performs supplementary verification of the user's medical identity through visual model verification and / or user commitment self-certification. When the verification is passed, the user terminal can display the application page for the successful application of the Zunyi Card. Otherwise, the user terminal can display the application page for the failed application.

[0112] In some embodiments, the professional identity authentication system constructed based on the professional identity authentication method can also be regarded as a professional identity authentication product. The framework of the professional identity authentication product can be as follows: Figure 6 As shown, it can specifically include four parts: business name, core value, core gameplay and core barriers, which can be specifically as follows:

[0113] (1) Business name: Occupational identity verification;

[0114] (2) Core value: It can be described from three dimensions. For users, verifying their professional identity can bring them exclusive benefits and enhance their sense of professional honor. For merchants (partners), it can achieve precision marketing and high output at low cost, which can not only enhance their social value but also their reputation. For identity authentication platforms (servers), it can achieve product commercialization of the underlying identity authentication data, increase user perception of identity authentication-related businesses, and allow users to enjoy professional benefits more conveniently, etc.

[0115] (3) Core gameplay: Verify your professional identity with one click and enjoy exclusive benefits immediately;

[0116] (4) Core barriers: Linked with user credit information to ensure the accuracy of information filled in. Existing data can be verified with one click. As the number of scenarios increases, identity verification can achieve a positive cycle. In addition, the verification results are fed back in real time through the algorithm model, with zero manual review costs.

[0117] To summarize, the occupational identity authentication method P100 and system 001 provided in this specification, after receiving a occupational identity authentication request, the occupational identity authentication request includes a candidate occupational identity of a target user to be verified and a verification scenario corresponding to the target user, and based on the verification scenario, selects at least one verification process in the candidate verification process to obtain a target verification method corresponding to the candidate occupational identity, and uses the target verification method to verify the candidate occupational identity of the target user, and outputs a verification result; since the scheme does not require manual review, the target verification method corresponding to the candidate occupational identity can be dynamically constructed based on the verification scenario, so that different verification methods can be used in different verification scenarios, thereby improving the success rate and accuracy of identity authentication, and there is no restriction on the occupational identities that can be verified, therefore, the verification efficiency of the occupational identities can be improved.

[0118] On the other hand, the present specification provides a non-transitory storage medium storing at least one set of executable instructions for performing occupational identity authentication. When the executable instructions are executed by a processor, the executable instructions instruct the processor to implement the steps of the occupational identity authentication method P100 described in the present specification. In some possible implementations, various aspects of the present specification can also be implemented in the form of a program product, which includes a program code. When the program product is run on a computing device 600, the program code is used to enable the computing device 600 to perform the steps of the occupational identity authentication method P100 described in the present specification. The program product for implementing the above method can use a portable compact disk read-only memory (CD-ROM) to include program code and can be run on the computing device 600. However, the program product of the present specification is not limited to this. In the present specification, the readable storage medium can be any tangible medium containing or storing a program, which can be used by or in combination with an instruction execution system. The program product can use any combination of one or more readable media. The readable medium can be a readable signal medium or a readable storage medium. The readable storage medium can be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples of readable storage media include: an electrical connection with one or more conductors, a portable disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. The computer-readable storage medium may include a data signal propagated in a baseband or as part of a carrier wave, wherein a readable program code is carried. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the above. The readable storage medium may also be any readable medium other than a readable storage medium, which may send, propagate, or transmit a program for use by or in conjunction with an instruction execution system, device, or device. The program code contained on the readable storage medium may be transmitted using any suitable medium, including but not limited to wireless, wired, optical cable, RF, etc., or any suitable combination of the above. Program code for performing the operations of the present specification may be written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Java, C++, etc., and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the computing device 600, partially on the computing device 600, as a stand-alone software package, partially on the computing device 600 and partially on a remote computing device, or entirely on a remote computing device.

[0119] The above is a description of a specific embodiment of the present specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recorded in the claims can be performed in an order different from that in the embodiments and still achieve the desired results. In addition, the processes depicted in the drawings do not necessarily require a specific order or a continuous order to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0120] In summary, after reading this detailed disclosure, those skilled in the art will appreciate that the foregoing detailed disclosure may be presented only by way of example and may not be limiting. Although not explicitly stated herein, those skilled in the art will appreciate that this specification requires various reasonable changes, improvements and modifications to the embodiments. These changes, improvements and modifications are intended to be proposed by this specification and are within the spirit and scope of the exemplary embodiments of this specification.

[0121] In addition, certain terms in this specification have been used to describe embodiments of this specification. For example, "one embodiment", "an embodiment" and / or "some embodiments" mean that a particular feature, structure or characteristic described in conjunction with the embodiment may be included in at least one embodiment of this specification. Therefore, it can be emphasized and should be understood that two or more references to "an embodiment" or "one embodiment" or "an alternative embodiment" in various parts of this specification do not necessarily refer to the same embodiment. In addition, specific features, structures or characteristics may be appropriately combined in one or more embodiments of this specification.

[0122] It should be understood that in the foregoing description of the embodiments of this specification, in order to help understand a feature and for the purpose of simplifying this specification, this specification combines various features in a single embodiment, figure or its description. However, this does not mean that the combination of these features is necessary. When reading this specification, it is entirely possible for a person skilled in the art to mark out some of the devices as separate embodiments. In other words, the embodiments in this specification can also be understood as the integration of multiple secondary embodiments. This is also true when the content of each secondary embodiment is less than all the features of a single aforementioned disclosed embodiment.

[0123] Each patent, patent application, patent application publication, and other material, such as articles, books, specifications, publications, documents, articles, etc., cited herein may be incorporated herein by reference in its entirety for all purposes, except for any prosecution document history related thereto, any equivalent that may be inconsistent or conflicting with this document, or any equivalent prosecution document history that may have a limiting effect on the broadest scope of the claims now or later associated with this document. For example, if there is any inconsistency or conflict between the description, definition, and / or use of a term associated with any of the incorporated materials and the term, description, definition, and / or use associated with this document, the term in this document shall control.

[0124] Finally, it should be understood that the embodiments of the application disclosed herein are explanations of the principles of the embodiments of this specification. Other modified embodiments are also within the scope of this specification. Therefore, the embodiments disclosed in this specification are only used as examples and not as limitations. Those skilled in the art can adopt alternative configurations according to the embodiments in this specification to implement the applications in this specification. Therefore, the embodiments of this specification are not limited to the embodiments accurately described in the application.

Claims

1. A method for professional identity verification, comprising: Receive a professional identity authentication request, the professional identity authentication request including a candidate professional identity of a target user to be verified and a verification scenario corresponding to a target activity in which the target user participates; the verification scenario is a scenario in which a user of the candidate professional identity is treated specially; the verification scenario is related to the activity content of the target activity, and is a scenario in which the content of the activity has requirements on the credibility of the candidate professional identity of the target user and verification is required; Dynamically determining a target verification accuracy corresponding to the candidate occupational identity of the target user based on the different verification scenarios, selecting at least one verification process from the candidate verification processes based on the target verification accuracy to obtain a target verification method corresponding to the candidate occupational identity, the candidate verification process comprising at least one of official verification, big data cross-validation, visual model verification, and user commitment self-validation, and the verification accuracies corresponding to the official verification, the big data cross-validation, the visual model verification, and the user commitment self-validation, respectively, decrease in sequence; and The target verification method is used to verify the candidate occupation identity of the target user, and the verification result is output.

2. The occupation identity verification method according to claim 1, wherein: The method is applied to a marketing scenario, and the professional identity is one or more professional identities specifically targeted by a marketing activity in the marketing scenario.

3. The occupation identity verification method according to claim 1, wherein: There are multiple verification processes selected, and the target verification method corresponding to the candidate occupation identity includes: The selected multiple verification processes are combined to obtain a target verification method corresponding to the candidate occupational identity.

4. The occupation identity verification method according to claim 1, wherein: The selecting at least one verification process from candidate verification processes based on the target verification accuracy includes: Obtaining the current verification accuracy corresponding to each verification process in the candidate verification process; matching the target verification accuracy with the current verification accuracy; and Based on the matching result, at least one verification process is selected from the candidate verification processes.

5. The occupation identity verification method according to claim 1, wherein: The official verification is performed for the candidate occupation identity verification of the target user, including: Obtaining the identity information of the target user, and sending the identity information to a professional certificate authentication server; receiving the target user's professional certificate information returned by the professional certificate authentication server; and The occupational certificate information is input into the occupational graph to obtain the verification result of the candidate occupational identity of the target user.

6. The occupation identity verification method according to claim 1, wherein: The big data cross-validation is performed for the candidate occupation identity verification of the target user, including: Acquire user attribute information of the target user, and extract target user data of multiple dimensions from the user attribute information; Inputting the target user data of the multiple dimensions into the career graph respectively to obtain verification information corresponding to the target user data of each dimension; and Based on the verification information, the candidate occupational identities of the target user are cross-verified to obtain a verification result of the candidate occupational identities of the target user.

7. The occupation identity verification method according to claim 6, wherein: The target user data includes at least one of the target user's location information, user portrait, social security information, social information, transaction information and tax information.

8. The occupation identity verification method according to claim 1, wherein: The visual model verification is performed for the candidate occupation identity verification of the target user, including: Acquire the occupational authentication image of the target user, and perform image verification on the occupational authentication image; When the occupational authentication image passes the verification, performing image recognition on the occupational authentication image; and The recognition result of the occupational authentication image is input into the occupational map to obtain the verification result of the candidate occupational identity of the target user.

9. The occupation identity verification method according to claim 8, wherein: The performing image recognition on the occupation certification image includes: Performing text detection on the occupation certification image; When the occupation authentication image includes text, identifying text content in the occupation authentication image; and Based on the text content, an image authentication type of the occupation authentication image is determined, and the image authentication type is used as a recognition result of the occupation authentication image.

10. The occupation identity verification method according to claim 9, wherein: Also includes: When the occupation certification image does not include the text, performing image feature extraction on the occupation certification image; as well as Based on the extracted image features, the image content of the occupation authentication image is determined, and the image content is used as the recognition result of the occupation authentication image.

11. The occupation identity verification method according to claim 1, wherein: For the candidate occupation identity verification of the target user, the user's self-certification of commitment is performed, including: Acquiring user commitment information of the target user for the candidate professional identity, wherein the user commitment information is linked to the credit information of the target user; and Based on the user commitment information, it is determined that the candidate occupation identity authentication of the target user has passed, and the passed authentication is used as the authentication result.

12. The occupation identity verification method according to claim 11, wherein: The obtaining of the user commitment information of the target user for the candidate professional identity includes: Obtaining credit information of the target user; and When the credit information meets the preset credit condition, user commitment information of the target user for the candidate professional identity is obtained.

13. The occupation identity verification method according to claim 11, wherein: After determining the verification result of the candidate occupation identity of the target user based on the user commitment information, the method further includes: When it is detected that the candidate occupation identity verification of the target user fails or the target user has risky behaviors corresponding to the candidate occupation identity, the credit information of the target user is adjusted.

14. The occupation identity verification method according to claim 13, wherein: The adjusting the credit information of the target user includes: Determining an adjustment method for the credit information based on the user commitment information; and Based on the adjustment method, the credit information of the target user is adjusted to impose credit punishment on the target user.

15. The occupation identity verification method according to claim 1, wherein: The execution order of at least one verification process in the target verification method includes executing the verification process in order from large to small according to the verification accuracy of the verification process, and when the currently executed verification process does not output a verification result, executing the next verification process.

16. The occupation identity verification method according to claim 15, wherein: The adopting the target verification method to verify the candidate occupation identity of the target user includes: Based on the execution order, at least one verification process in the target verification method is executed to verify the candidate occupation identity of the target user.

17. The occupation identity verification method according to claim 1, wherein: The verification result is associated with the professional rights and interests corresponding to the candidate professional identity of the target user, and the professional rights and interests include at least one authority corresponding to the candidate professional identity.

18. A professional identity verification system, comprising: at least one storage medium storing at least one instruction set for performing occupational identity verification; as well as at least one processor, in communication with the at least one storage medium, Wherein, when the professional identity authentication system is running, the at least one processor reads the at least one instruction set and executes the professional identity authentication method described in any one of claims 1-17 according to the instructions of the at least one instruction set.

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