A population data label generation method and device based on grassroots governance and a medium

Abstract

The application discloses a population data label generation method and device based on basic-level governance, and a medium, the method comprising: receiving a population data label generation request uploaded by a basic-level governance system to obtain population data; determining a business system interface to be called according to a pre-set label generation condition; determining whether the population data has a unique identity identifier of a user; if yes, calling the business system interface to iterate the unique identity identifier in the business system; when the iteration is completed, determining corresponding business data of the user in the business system; and generating a user label corresponding to the population data according to the label generation condition, the population data and the business data. The unique identity identifier can be used as a medium to call the business system interface through the label generation condition, so that the business data is compared with the label generation condition, and the user label is automatically generated when the label generation condition is met, thereby improving the population data label generation efficiency and accuracy.

Description

Technical Field

[0001] This application relates to the field of data governance technology, and in particular to a method, device and medium for generating population data labels based on grassroots governance. Background Technology

[0002] Grassroots governance is the cornerstone of national governance. Coordinating the governance of towns, streets, villages, and communities is a fundamental project for realizing the modernization of the national governance system and governance capacity.

[0003] Because population data involves multiple business scenarios in grassroots governance, population data management has always been a pain point and a challenge in grassroots governance work. Grassroots governance staff are responsible for collecting population data, sorting out and reporting ledgers, and other tasks distributed by multiple vertical departments. Due to the different work requirements of relevant departments for communities and the different information collected, there are many types of population data involved, such as type A information, type B information, type C information, etc.

[0004] Currently, due to the lack of refined data management, grassroots governance staff repeatedly conduct surveys to collect relevant population information and manually label the population data. This results in high pressure on grassroots governance staff and problems such as unclear population figures, untimely updates, and inaccurate data, leading to low efficiency and low accuracy in generating population data labels for grassroots governance. Summary of the Invention

[0005] This application provides a method, device, and medium for generating population data tags based on grassroots governance, which addresses the problems of low efficiency and low accuracy in generating population data tags for grassroots governance.

[0006] The embodiments of this application adopt the following technical solutions:

[0007] On one hand, this application provides a method for generating population data tags based on grassroots governance. The method includes: receiving a population data tag generation request uploaded by a grassroots governance system; parsing the population data tag generation request to obtain population data; determining the business system interface to be called based on pre-set tag generation conditions; determining whether the population data contains a unique identifier for the user; if so, calling the business system interface to iterate through the unique identifier in the business system; upon completion of the iteration, determining the business data corresponding to the user in the business system; and generating a user tag corresponding to the population data based on the tag generation conditions, the population data, and the business data.

[0008] In one example, generating user tags corresponding to the population data based on pre-set tag generation conditions, the population data, and the business data specifically includes: determining whether the business data meets the tag generation conditions; if so, matching the business data with the population data; if the match is successful, generating tags corresponding to the tag generation conditions; and generating user tags corresponding to the population data based on the tags corresponding to the tag generation conditions.

[0009] In one example, generating user tags corresponding to the population data based on the tags corresponding to the tag generation conditions specifically includes: if there are multiple tag generation conditions, then each tag generation condition has a corresponding tag; converting multiple tags into statement tags according to a pre-set tag statement generation rule; determining the statement tags as user tags corresponding to the population data; if there is only one tag generation condition, then determining the tag corresponding to the tag generation condition as the user tag corresponding to the population data.

[0010] In one example, the method further includes: if the business data fails to match the population data, determining whether the population data contains a field corresponding to the business data; if so, generating a population data error message and feeding the population data error message back to the grassroots governance system to confirm whether to update the mismatched data in the population data; after updating the mismatched data in the population data, updating the status of the business data failing to match the population data to a matching status.

[0011] In one example, the method further includes: if the population data does not contain a field corresponding to the business data, generating a population data missing prompt message, and feeding the population data missing prompt message back to the grassroots governance system to confirm whether to complete the missing data in the population data; after completing the missing data in the population data, updating the status of the business data and the population data from a failed match to a successful match.

[0012] In one example, determining whether the business data meets the tag generation conditions specifically includes: identifying multiple condition fields in the tag generation conditions; determining whether the field corresponding to the business data has a matching relationship with one or more condition fields; if yes, then determining that the business data meets the tag generation conditions; if no, then determining that the business data does not meet the tag generation conditions.

[0013] In one example, the method further includes: if the business data does not meet the tag generation conditions, generating verification notification information for the tag generation conditions and sending the verification notification information to a tag generation condition verification terminal to verify whether the tag generation conditions need to be updated; if it is confirmed that the tag generation conditions need to be updated, updating the state of the business data not meeting the tag generation conditions to the state of the business data meeting the tag generation conditions; if it is confirmed that the tag generation conditions do not need to be updated, then no longer generating the tag corresponding to the tag generation conditions.

[0014] In one example, the method further includes: if the population data does not contain a unique identifier for the user, then searching the fields of the population data in a pre-built identifier mapping table to determine whether the population data contains an identifier-related field; if so, then determining whether the identifier-related field is found in the grassroots governance database; if so, determining the unique identifier for the user based on the identifier-related field; if not, generating an identifier missing notification and feeding the identifier missing notification back to the grassroots governance system.

[0015] On the other hand, this application provides a population data tag generation device based on grassroots governance, including: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, the instructions being executed by the at least one processor to enable the at least one processor to: receive a population data tag generation request uploaded by a grassroots governance system; parse the population data tag generation request to obtain population data; determine the business system interface to be called according to preset tag generation conditions; determine whether the population data contains a unique identifier for a user; if so, call the business system interface to traverse the unique identifier in the business system; upon completion of the traversal, determine the business data corresponding to the user in the business system; and generate a user tag corresponding to the population data according to the tag generation conditions, the population data, and the business data.

[0016] On the other hand, embodiments of this application provide a non-volatile computer storage medium for generating population data tags based on grassroots governance, storing computer-executable instructions. These computer-executable instructions are configured to: receive a population data tag generation request uploaded by a grassroots governance system; parse the population data tag generation request to obtain population data; determine the business system interface to be called based on pre-set tag generation conditions; determine whether the population data contains a unique identifier for the user; if so, call the business system interface to iterate through the unique identifier in the business system; upon completion of the iteration, determine the business data corresponding to the user in the business system; and generate a user tag corresponding to the population data based on the tag generation conditions, the population data, and the business data.

[0017] The above-described technical solutions adopted in the embodiments of this application can achieve the following beneficial effects:

[0018] Using unique identity identifiers as a medium, the system calls business system interfaces through tag generation conditions, comparing business data with the tag generation conditions. When the conditions are met, user tags are automatically generated, thereby improving the efficiency and accuracy of population data tag generation. By channeling business data from relevant business systems to the grassroots governance system, the system can address the issue of inaccurate and untimely access to various information within the jurisdiction by grassroots workers, enabling refined management of grassroots population data, supporting various business scenarios in grassroots governance, and enhancing the proactive service capabilities of the grassroots. Attached Figure Description

[0019] To more clearly illustrate the technical solution of this application, some embodiments of this application will be described in detail below with reference to the accompanying drawings, in which:

[0020] Figure 1 A flowchart illustrating a population data tag generation method based on grassroots governance, provided for an embodiment of this application;

[0021] Figure 2 This is a schematic diagram of a population data tag generation device based on grassroots governance, provided in an embodiment of this application. Detailed Implementation

[0022] To make the objectives, technical solutions, and advantages of this application clearer, the technical solutions of this application will be clearly and completely described below in conjunction with specific embodiments and corresponding drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of them. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0023] Some embodiments of this application will now be described in detail with reference to the accompanying drawings.

[0024] Figure 1 This is a flowchart illustrating a population data tag generation method based on grassroots governance, provided as an embodiment of this application. Certain input parameters or intermediate results in this process can be manually adjusted to help improve accuracy.

[0025] The analysis method involved in the embodiments of this application can be implemented by a terminal device or a server, and this application does not impose any special limitations on it. For ease of understanding and description, the following embodiments are all described in detail using a server as an example.

[0026] It should be noted that the server can be a single device or a system composed of multiple devices, i.e., a distributed server. This application does not make any specific limitations on this.

[0027] Figure 1 The process may include the following steps:

[0028] S101: Receive a population data tag generation request uploaded by the grassroots governance system, parse the population data tag generation request, and obtain population data.

[0029] It should be noted that population data can be obtained through collection by grassroots workers.

[0030] S102: Determine the business system interface to be called based on the pre-set tag generation conditions.

[0031] For example, a business system may include system A, system B, system C, etc., or it may include an electronic certificate system, a comprehensive social management system (including population names and ID cards), etc.

[0032] When constructing tag generation conditions, first create a business category for the tag, and then create tags under that business category, such as tag x, tag y, etc. Set the tag name, usage permissions, etc., including public, specified jurisdiction, and visible only to the user. Then, set the tag generation conditions according to business requirements; for example, the tag generation conditions for tag x need to include data x1, x2, and x3.

[0033] S103: Determine whether the population data contains a unique identifier for the user.

[0034] Among them, the user's unique identifier refers to the user's ID card.

[0035] In the embodiments of this application, if the population data does not contain a unique identifier for the user, then it is necessary to infer from the population data whether the unique identifier for the user can be inferred. If it cannot be inferred, then S104-S106 will not be executed.

[0036] Specifically, in a pre-built identity mapping table, fields of the population data are retrieved to determine whether the population data contains identity-related fields. It should be noted that the identity mapping table includes the mapping relationship between identity fields and identity-related fields. For example, identity-related fields may include name and contact information.

[0037] If so, then check the grassroots governance database to see if the identity-related field is found. In other words, the user may have previously registered personal information, which is stored in the grassroots governance database.

[0038] If so, determine the user's unique identifier based on the identity identifier associated fields.

[0039] In other words, a user's unique identifier can be retrieved through the identity identifier association field. It should be noted that if multiple different records are found when querying the identity identifier association field...

[0040] For example, if a search by name returns two different records, and other identity identifier fields are available, the search can be further refined using those fields. For instance, filtering by contact information can help determine which specific record the current population data belongs to.

[0041] If there are no other identity-related fields, two different records will be sent to the grassroots governance system for grassroots governance staff to confirm.

[0042] If not, a missing identity notification message will be generated and fed back to the grassroots governance system.

[0043] S104: If so, call the business system interface to iterate through the unique identity identifier in the business system.

[0044] S105: Upon completion of the traversal, determine the business data corresponding to the user in the business system.

[0045] For example, if the business system is managed by D, then the business data includes d1, d2, d3, etc.

[0046] S106: Generate user tags corresponding to the population data based on the tag generation conditions, the population data, and the business data.

[0047] In some embodiments of this application, the business data may or may not meet the tag generation conditions.

[0048] It should be noted that when determining whether business data meets the tag generation conditions, firstly, the multiple condition fields in the tag generation conditions are identified. Then, it is determined whether the fields corresponding to the business data match one or more condition fields. For example, the business data fields corresponding to the E management system need to match the condition fields e1, e2, and e3 simultaneously.

[0049] Then, if yes, it is determined that the business data meets the tag generation conditions. If no, it is determined that the business data does not meet the tag generation conditions.

[0050] Therefore, if the business data does not meet the tag generation conditions, in order to avoid errors in the tag generation conditions, such as the tag generation conditions being missing a condition field that can prove that the user belongs to the tag, the business data may include the missing condition field, but the judgment result is that the business data does not meet the tag generation conditions and the tag corresponding to the tag generation conditions cannot be generated.

[0051] Specifically, it is necessary to generate a verification notification message for the label generation conditions and send the verification notification message to the label generation condition verification terminal to verify whether the label generation conditions need to be updated.

[0052] When it is confirmed that the tag generation conditions need to be updated, the status of business data that does not meet the tag generation conditions will be updated to the status that the business data meets the tag generation conditions. The need for an update indicates that the grassroots governance staff, when setting the tag generation conditions, were missing a conditional field that could prove that the user belongs to that tag.

[0053] If it is confirmed that the tag generation conditions do not need to be updated, then the tags corresponding to the tag generation conditions will no longer be generated.

[0054] Based on this, if the business data meets the tag generation conditions, the business data will be matched with the population data.

[0055] It should be noted that when business data meets the label generation conditions, it means that the fields in the business data meet the condition fields for label generation. This is because population data fields may also include fields from business data. However, since population data is collected by grassroots governance staff based on information filled in by users, errors in input by staff into the system or user input can lead to errors in population data fields. Therefore, the business data from the business system should be considered the most accurate. Furthermore, incomplete or missing data may also occur. Therefore, by matching business data with population data, erroneous and missing data in the population data can be automatically identified.

[0056] In some embodiments of this application, if a match is successful, a tag corresponding to the tag generation condition is generated, and user tags corresponding to the population data are generated based on the tag corresponding to the tag generation condition.

[0057] A successful match is determined when all fields of the business data can be matched successfully in the population data.

[0058] It should be noted that population data may have multiple labels simultaneously. Therefore, population data is matched with multiple label generation conditions to determine the multiple labels corresponding to the population data.

[0059] Specifically, if there are multiple tag generation conditions, then each tag generation condition corresponds to a separate tag. Then, according to pre-defined tag statement generation rules, the multiple tags are converted into statement tags. Finally, the statement tags are determined as user tags corresponding to the population data.

[0060] The tag statement generation rules can be obtained by setting rules based on Chinese logical expression rules.

[0061] Understandably, using sentence tags can help grassroots governance staff understand a user's multiple tags more intuitively.

[0062] It should be noted that if there is only one tag generation condition, the tag corresponding to the tag generation condition will be determined as the user tag corresponding to the population data.

[0063] In some embodiments of this application, there is a possibility that business data and population data may fail to match. This means that not all fields in the business data can be matched with the population data. For example, business data fields a and b: field a can find a matching data, but field b cannot. In this case, it indicates that the population data may not contain a field corresponding to field b, or it may contain a corresponding field, but the field data is incorrect.

[0064] Based on this, if the business data fails to match the population data, it is determined whether the population data contains the field corresponding to the business data.

[0065] If so, an error message about the population data is generated and fed back to the grassroots governance system to confirm whether the mismatched data in the population data should be updated.

[0066] After updating the mismatched data in the population data, the status of the business data failing to match the population data is updated to a status of successful match.

[0067] Conversely, if the population data does not contain fields corresponding to the business data, a population data missing prompt message is generated and fed back to the grassroots governance system to confirm whether the missing data in the population data should be supplemented.

[0068] After completing the missing data in the population data, the status of the business data failing to match the population data is updated to a successful match status.

[0069] It should be noted that some tags can be determined without calling the business system, instead by constructing tag generation conditions with business logic.

[0070] For example, if we determine whether someone is elderly based on their age, and age can be determined using a unique identity identifier, then the conditions for generating the label can be set using calculation logic rules. For instance, if there is an ID card number, the age can be calculated based on the ID card number. If there is no ID card number, then we need to check with the grassroots governance database. If we cannot find an identity identifier associated field, and if the population data includes birth date data, then we can calculate the age based on the birth date. If the age is greater than or equal to 60, then the person is considered elderly. Since the birth date data in the population data is not guaranteed to be accurate, we need to confirm with the grassroots governance staff whether to generate an elderly label.

[0071] It should be noted that, although the embodiments in this application are based on... Figure 1 Steps S101 to S106 will be described sequentially, but this does not mean that steps S101 to S106 must be performed in a strict order. The reason this embodiment follows this order is... Figure 1 The order in which steps S101 to S106 are described is provided to facilitate understanding of the technical solutions of the embodiments of this application by those skilled in the art. In other words, in the embodiments of this application, the order of steps S101 to S106 can be appropriately adjusted according to actual needs.

[0072] pass Figure 1 This method uses a unique identity identifier as a medium and calls the business system interface through tag generation conditions. It compares business data with the tag generation conditions and automatically generates user tags when the conditions are met. This improves the efficiency and accuracy of population data tag generation. By sinking business data from relevant business systems to the grassroots governance system, it can solve the problem of inaccurate and untimely information grasped by grassroots workers in their jurisdiction, realize refined management of grassroots population data, support various business scenarios of grassroots governance, and enhance the proactive service capabilities of the grassroots.

[0073] Based on the same idea, some embodiments of this application also provide devices and non-volatile computer storage media corresponding to the above methods.

[0074] Figure 2 A schematic diagram of a population data tag generation device based on grassroots governance provided in this application embodiment includes:

[0075] At least one processor; and,

[0076] A memory communicatively connected to the at least one processor; wherein,

[0077] The memory stores instructions that can be executed by the at least one processor, the instructions being executed by the at least one processor to enable the at least one processor to:

[0078] Receive a population data tag generation request uploaded by the grassroots governance system, parse the population data tag generation request, and obtain the population data;

[0079] Based on the pre-defined tag generation conditions, determine the business system interface to be called;

[0080] Determine whether the population data contains a unique identifier for the user;

[0081] If so, the business system interface is invoked to iterate through the unique identity identifier in the business system;

[0082] Upon completion of the traversal, the corresponding business data of the user in the business system is determined;

[0083] Based on the tag generation conditions, the population data, and the business data, user tags corresponding to the population data are generated.

[0084] Some embodiments of this application provide a non-volatile computer storage medium for generating population data tags based on grassroots governance, storing computer-executable instructions, wherein the computer-executable instructions are configured as follows:

[0085] Receive a population data tag generation request uploaded by the grassroots governance system, parse the population data tag generation request, and obtain the population data;

[0086] Based on the pre-defined tag generation conditions, determine the business system interface to be called;

[0087] Determine whether the population data contains a unique identifier for the user;

[0088] If so, the business system interface is invoked to iterate through the unique identity identifier in the business system;

[0089] Upon completion of the traversal, the corresponding business data of the user in the business system is determined;

[0090] Based on the tag generation conditions, the population data, and the business data, user tags corresponding to the population data are generated.

[0091] The various embodiments in this application are described in a progressive manner. Similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments. In particular, the device and medium embodiments are basically similar to the method embodiments, so the description is relatively simple; relevant parts can be referred to the description of the method embodiments.

[0092] The devices and media provided in this application are one-to-one with the methods. Therefore, the devices and media also have similar beneficial technical effects as their corresponding methods. Since the beneficial technical effects of the methods have been described in detail above, the beneficial technical effects of the devices and media will not be repeated here.

[0093] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0094] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0095] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0096] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0097] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0098] Memory may include non-persistent storage in computer-readable media, such as random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM. Memory is an example of computer-readable media.

[0099] Computer-readable media includes both permanent and non-permanent, removable and non-removable media that can store information using any method or technology. Information can be computer-readable instructions, data structures, modules of programs, or other data. Examples of computer storage media include, but are not limited to, phase-change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technologies, CD-ROM, digital versatile optical disc (DVD) or other optical storage, magnetic tape, magnetic magnetic disk storage or other magnetic storage devices, or any other non-transferable medium that can be used to store information accessible by a computing device. As defined herein, computer-readable media does not include transient computer-readable media, such as modulated data signals and carrier waves.

[0100] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0101] The above description is merely an embodiment of this application and is not intended to limit this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the technical principles of this application should fall within the protection scope of this application.

Claims

1. A method for generating population data tags based on grassroots governance, characterized in that, The method includes: Receive a population data tag generation request uploaded by the grassroots governance system, parse the population data tag generation request, and obtain the population data; Based on the pre-defined tag generation conditions, determine the business system interface to be called; Determine whether the population data contains a unique identifier for the user; If so, the business system interface is invoked to iterate through the unique identity identifier in the business system; Upon completion of the traversal, the corresponding business data of the user in the business system is determined; Based on the tag generation conditions, the population data, and the business data, user tags corresponding to the population data are generated; The step of generating user tags corresponding to the population data based on pre-set tag generation conditions, the population data, and the business data specifically includes: Determine whether the business data meets the tag generation conditions; If so, the business data will be matched with the population data; If a match is found, the tag corresponding to the tag generation condition is generated; Generate user tags corresponding to the population data based on the tags corresponding to the tag generation conditions; The step of generating user tags corresponding to the population data based on the tags corresponding to the tag generation conditions specifically includes: If there are multiple tag generation conditions, then there are tags corresponding to each tag generation condition; Based on pre-defined tag statement generation rules, multiple tags are converted into statement tags; The statement tag is determined as the user tag corresponding to the population data; If the tag generation condition is a single condition, then the tag corresponding to the tag generation condition is determined as the user tag corresponding to the population data; The step of determining whether the business data meets the tag generation conditions specifically includes: Determine multiple condition fields in the label generation conditions; Determine whether the field corresponding to the business data matches one or more condition fields; If so, then the business data is determined to meet the tag generation conditions; If not, then it is determined that the business data does not meet the tag generation conditions; If the business data does not meet the tag generation conditions, a verification notification message for the tag generation conditions is generated and sent to the tag generation condition verification terminal to verify whether the tag generation conditions need to be updated. When it is confirmed that the tag generation conditions need to be updated, the state of the business data not meeting the tag generation conditions is updated to the state of the business data meeting the tag generation conditions; If it is confirmed that the tag generation conditions do not need to be updated, then the tags corresponding to the tag generation conditions will no longer be generated.

2. The method according to claim 1, characterized in that, The method further includes: If the business data fails to match the population data, then determine whether the population data contains a field corresponding to the business data; If so, a population data error message is generated and fed back to the grassroots governance system to confirm whether the mismatched data in the population data should be updated. After updating the mismatched data in the population data, the status of the business data failing to match the population data is updated to a status of successful match.

3. The method according to claim 2, characterized in that, The method further includes: If the population data does not contain the field corresponding to the business data, a population data missing prompt message is generated and fed back to the grassroots governance system to confirm whether the missing data in the population data should be supplemented. After completing the missing data in the population data, the status of the business data failing to match the population data is updated to a status of successful matching.

4. The method according to claim 1, characterized in that, The method further includes: If the population data does not contain a unique identifier for the user, then the fields of the population data are searched in the pre-built identity mapping table to determine whether the population data contains an identity-related field. If so, then determine whether the identity identifier associated field is retrieved in the grassroots governance database; If so, determine the user's unique identifier based on the identity identifier association field; If not, an identity verification missing notification is generated and fed back to the grassroots governance system.

5. A population data tag generation device based on grassroots governance, characterized in that, include: At least one processor; as well as, A memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor, which, when executed by the at least one processor, enables the at least one processor to: perform the population data tag generation method based on grassroots governance as described in any one of claims 1-4.

6. A non-volatile computer storage medium for generating population data tags based on grassroots governance, storing computer-executable instructions, characterized in that, The computer-executable instructions are configured to execute the population data tag generation method based on grassroots governance as described in any one of claims 1-4.

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