Method, device and equipment for processing ledger data of security supervision object

Abstract

The invention discloses a processing method, device and equipment for machine account data of a safety supervision object, and relates to the technical field of computers. The method comprises the following steps: acquiring standing book data to be processed of a security supervision object; in response to determining that missing data exists in the machine account data, utilizing a multi-level data restoration rule to restore the missing data so as to obtain machine account data subjected to restoration processing; based on the machine account data subjected to the repair processing, determining an error confidence coefficient of the machine account data subjected to the repair processing by utilizing a preset address error correction algorithm; and on the basis of a preset updating condition and the error confidence coefficient, updating the repaired standing book data to obtain target standing book data of the security supervision object.

Description

Technical Field

[0001] This application relates to the field of computer technologies, specifically to the fields of big data technologies and emergency safety management technologies, and particularly relates to a method, device, and equipment for processing ledger data of safety supervision objects. Background Art

[0002] In the field of emergency management, enterprise work safety and fire hazard investigation and treatment are important links in ensuring public safety. To smoothly carry out enterprise work safety and fire hazard investigation and treatment, it is necessary to clearly understand the basic information of safety supervision objects, that is, ledger data, and build comprehensive systems such as emergency management command and dispatch systems and work safety platforms based on the ledger data. The ledger data of these safety supervision objects can be used by upstream emergency systems, such as administrative law enforcement, to improve the efficiency of emergency law enforcement and effectively prevent and solve safety problems.

[0003] Currently, in comprehensive systems such as emergency management command and dispatch systems and work safety platforms, generally, a safety supervision object database is built through data collection and manual entry, or ledger data of safety supervision objects is extracted from a data warehouse with the help of specialized data governance tools and teams. Summary of the Invention

[0004] This application provides a method, device, and equipment for processing ledger data of safety supervision objects, which can solve the problems of poor accuracy and timeliness in the collection of ledger data. The technical solutions are as follows: In a first aspect, a method for processing ledger data of safety supervision objects is provided. The method includes: Obtaining the to-be-processed ledger data of safety supervision objects; In response to determining that there is missing data in the ledger data, using multi-level data repair rules to repair the missing data to obtain repaired ledger data; Based on the repaired ledger data, using a preset address error correction algorithm to determine the error confidence level of the repaired ledger data; Based on a preset update condition and the error confidence level, performing an update process on the repaired ledger data to obtain the target ledger data of the safety supervision objects.

[0005] In a possible implementation manner, the obtaining the to-be-processed ledger data of safety supervision objects includes: Obtaining the initial ledger data of the safety supervision objects from multiple data platforms; the initial ledger data includes safety supervision object identifiers; Based on the safety supervision object identifiers, performing a fusion process on the initial ledger data of multiple data platforms to obtain the to-be-processed ledger data.

[0006] In a possible implementation, the missing data includes missing venue address data. In response to determining that there is missing data in the ledger data, the missing data is repaired using multi-level data repair rules to obtain repaired ledger data, including: In response to determining that there is missing venue address data in the ledger data, the missing venue address data is sent to the first repair level management terminal to obtain a first repair result of the first repair level management terminal; In response to determining that the first repair result is a repair failure, the missing venue address data is sent to the second repair level management terminal to obtain a second repair result of the second repair level management terminal; In response to determining that the second repair result is a repair failure, the missing venue address data is sent to the third repair level management terminal to obtain a third repair result of the third repair level management terminal; In response to determining that the third repair result is a successful repair, the repaired ledger data is obtained.

[0007] In a possible implementation, based on the repaired ledger data, a preset address error correction algorithm is used to determine the error confidence level of the repaired ledger data, including: Obtain the address data in the repaired ledger data; Perform word segmentation processing on the address data to obtain word segmentation text data at the geographical level; Based on the word segmentation text data, using a preset address error correction algorithm, calculate the error confidence level of the repaired ledger data.

[0008] In a possible implementation, based on the word segmentation text data, using a preset address error correction algorithm, calculate the error confidence level of the repaired ledger data, including: Obtain the municipal-level text data and district / street-level text data in the word segmentation text data; Based on a preset address corpus, the municipal-level text data, and the district / street-level text data, calculate the municipal-level error confidence level corresponding to the municipal-level text data and the district / street-level error confidence level corresponding to the district / street-level text data, respectively; Based on the municipal-level error confidence level or the district / street-level error confidence level, obtain the address anomaly confidence level; Input the word segmentation text data into a pre-trained address semantic model to obtain the semantic anomaly confidence level; Use location-based services to perform verification processing on the word segmentation text data to obtain the spatio-temporal anomaly confidence level; Based on the address anomaly confidence level, semantic anomaly confidence level, and spatio-temporal anomaly confidence level, calculate the error confidence level of the ledger data for the repair process.

[0009] In one possible implementation, the updating process of the ledger data for the repair process based on the preset update condition and the error confidence level to obtain the target ledger data of the safety supervision object includes: In response to the error confidence level satisfying the preset update condition, obtain the safety supervision object identifier in the ledger data for the repair process; Based on the safety supervision object identifier, update the address data of the safety supervision object until the error confidence level does not satisfy the preset update condition; Based on the ledger data corresponding to the error confidence level that does not satisfy the preset update condition, obtain the target ledger data of the safety supervision object.

[0010] In a second aspect, a processing device for the ledger data of a safety supervision object is provided. The device includes: An acquisition unit for acquiring the ledger data to be processed of a safety supervision object; A repair unit for, in response to determining that there is missing data in the ledger data, using multi-level data repair rules to perform repair processing on the missing data to obtain the ledger data after repair processing; A determination unit for, based on the ledger data after repair processing, using a preset address error correction algorithm to determine the error confidence level of the ledger data after repair processing; An acquisition unit for, based on a preset update condition and the error confidence level, performing an update process on the ledger data after repair processing to obtain the target ledger data of the safety supervision object.

[0011] In a third aspect, a computer-readable storage medium is provided. At least one instruction is stored in the storage medium, and the at least one instruction is loaded and executed by a processor to implement the methods in the above-mentioned aspect and any possible implementation.

[0012] In a fourth aspect, an electronic device is provided, 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, and the instructions are executed by the at least one processor to enable the at least one processor to execute the methods in the above-mentioned aspect and any possible implementation.

[0013] In a fifth aspect, a computer program product is provided, including a computer program which, when executed by a processor, implements the methods of the above-described aspect and any possible implementation manners.

[0014] The beneficial effects of the technical solutions provided in this application at least include: As can be seen from the above technical solutions, in the embodiments of this application, the to-be-processed ledger data of a safety supervision object can be obtained, and then in response to determining that there is missing data in the ledger data, multi-level data repair rules can be used to repair the missing data to obtain repaired ledger data. Based on the repaired ledger data, a preset address error correction algorithm can be used to determine the error confidence level of the repaired ledger data. Based on a preset update condition and the error confidence level, the repaired ledger data can be updated to obtain the target ledger data of the safety supervision object. Since the missing data in the obtained to-be-processed ledger data can be supplemented and repaired according to the repair rules, the integrity of the collected ledger data is ensured, and by detecting the accuracy of the address data in the repaired ledger data, the reliability and accuracy of the ledger data of the safety supervision object are improved.

[0015] It should be understood that the content described in this part is not intended to identify the key or important features of the embodiments of this application, nor is it used to limit the scope of this application. Other features of this application will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the technical solutions in the embodiments of this application, the drawings required for description in the embodiments will be briefly introduced below. Obviously, the drawings in the following description are only some embodiments of this application, and for those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0017] Figure 1 is a flowchart of a method for processing ledger data provided by an embodiment of this application; Figure 2 is a flowchart of a method for processing ledger data provided by another embodiment of this application; Figure 3 is a flowchart of the review and repair of missing data in a method for processing ledger data provided by another embodiment of this application; Figure 4 is a block diagram of a device for processing ledger data provided by an embodiment of this application; Figure 5 is a block diagram of an electronic device for implementing the method for processing ledger data in the embodiments of this application. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0018] The exemplary embodiments of the present application will be described below in conjunction with the accompanying drawings. Various details of the embodiments of the present application are included to facilitate understanding, and they should be considered merely exemplary. Therefore, those of ordinary skill in the art should recognize that various changes and modifications can be made to the embodiments described herein without departing from the scope and spirit of the present application. Similarly, for the sake of clarity and conciseness, descriptions of well-known functions and structures are omitted in the following description.

[0019] Obviously, the described embodiments are some but not all of the embodiments of the present application. All other embodiments obtained by those of ordinary skill in the art based on the embodiments in the present application without creative efforts fall within the scope of protection of the present application.

[0020] It should be noted that the terminal devices involved in the embodiments of the present application may include, but are not limited to, intelligent devices such as mobile phones, personal digital assistants (PDAs), wireless handheld devices, and tablet computers (Tablet Computers); display devices may include, but are not limited to, devices with display functions such as personal computers and televisions.

[0021] In addition, the term "and / or" in this article is merely a description of the association relationship between associated objects, indicating that three relationships may exist. For example, A and / or B may represent: A exists alone, A and B exist simultaneously, and B exists alone. In addition, the character " / " in this article generally represents an "or" relationship between the associated objects before and after.

[0022] In the field of emergency management, enterprise work safety and fire hazard investigation and management are important links in ensuring public safety. In order to smoothly carry out enterprise work safety and fire hazard investigation and management, it is necessary to clearly understand all the basic data of the safety supervision objects, that is, the ledger data. Using this information, a safety supervision object database can be constructed to ensure the accuracy, timeliness, and standardization of this information, which can be used by upstream emergency systems such as administrative law enforcement, improving the efficiency of emergency law enforcement and effectively preventing and solving safety problems.

[0023] In comprehensive systems such as emergency management command and dispatch systems and work safety platforms, a safety supervision object database is generally constructed through data collection and manual entry, or by means of specialized data governance tools and teams, extracting all the basic data of these safety supervision objects from the data warehouse according to certain rules.

[0024] However, in the solutions of the related art, on the one hand, the data collection and entry efficiency is low, making it difficult to meet the needs of large-scale emergency management. On the other hand, there is a lack of an effective data governance mechanism, making it difficult to efficiently extract and integrate the data of supervised objects from the data warehouse, which affects the decision-making efficiency and accuracy of the upstream emergency system. In general emergency and safety supervised object collection systems, it is necessary to develop a special data management system or data warehouse to set rules and clean and process the upstream data source parties. Often, the system will be designed to be relatively complex, with high operation and maintenance costs, and is relatively independent of the actual emergency business system, making it difficult to integrate. On the other hand, there is a lack of an effective verification and feedback mechanism for the address information in the ledger data, making it difficult to be discovered and corrected in a timely manner. Since some ledger data, such as address, street, district where located, legal person's phone number, etc., change frequently, the upstream data source parties cannot fully guarantee the accuracy and timeliness of these data. When actually empowering the business system, some data inconsistency problems will still arise.

[0025] Therefore, there is an urgent need for a method for processing ledger data of supervised objects for safety, which can effectively collect the ledger data of supervised objects for safety and ensure the reliability and accuracy of the collected ledger data.

[0026] Please refer to Figure 1 , which shows a schematic flowchart of a method for processing ledger data of supervised objects for safety provided by an embodiment of the present application. The method for processing ledger data of supervised objects for safety may specifically include: Step 101, obtain the to-be-processed ledger data of the supervised object for safety.

[0027] Step 102, in response to determining that there is missing data in the ledger data, use multi-level data repair rules to repair the missing data to obtain the repaired ledger data.

[0028] Step 103, based on the repaired ledger data, use a preset address error correction algorithm to determine the error confidence level of the repaired ledger data.

[0029] Step 104, based on a preset update condition and the error confidence level, perform an update process on the repaired ledger data to obtain the target ledger data of the supervised object for safety.

[0030] It should be noted that the ledger data of the supervised object for safety can be the basic information of the supervised object for safety collected from each emergency management committee office, each industry unit, the big data center, and the basic platform in real time or at regular intervals. Based on the ledger data of the supervised object for safety, a ledger database of the supervised object for safety and a ledger data management platform of the supervised object for safety can be constructed.

[0031] It should be noted that the ledger data of safety supervision objects can serve emergency operations, such as the emergency safety hazard investigation business system. The emergency safety hazard investigation business system can use the ledger data. At the same time, during the investigation process, the ledger data with existing problems can be corrected, and the corrected ledger data can be directly fed back and updated and stored in the safety supervision object ledger database.

[0032] It should be noted that part or all of the execution subjects of steps 101 to 104 can be an application located on a local terminal, or can also be a functional unit such as a plug-in or software development kit (SDK) set in the application located on the local terminal, or can also be a processing engine in a network-side server, or can also be a distributed system on the network side. For example, the ledger data platform processing engine or distributed system of safety supervision objects on the network side, etc. This embodiment does not make special limitations on this.

[0033] It can be understood that the application can be a native app installed on the local terminal, or can also be a web app of a browser on the local terminal. This embodiment does not make limitations on this.

[0034] In this way, by obtaining the to-be-processed ledger data of safety supervision objects, and then in response to determining that there is missing data in the ledger data, using multi-level data repair rules to repair the missing data to obtain the repaired ledger data. Based on the repaired ledger data, using a preset address error correction algorithm to determine the error confidence level of the repaired ledger data. Based on the preset update conditions and the error confidence level, update the repaired ledger data to obtain the target ledger data of the safety supervision object. Since the missing data in the initially obtained ledger data can be supplemented and repaired according to the repair rules, the integrity of the collected ledger data is ensured, and by detecting the accuracy of the address data in the repaired ledger data, the reliability and accuracy of the ledger data of safety supervision objects are improved.

[0035] Optionally, in a possible implementation manner of this embodiment, in step 101, the initial ledger data of the safety supervision object can be specifically obtained from multiple data platforms; the initial ledger data includes the safety supervision object identifier, and then based on the safety supervision object identifier, the initial ledger data of multiple data platforms can be fused to obtain the to-be-processed ledger data.

[0036] In this implementation manner, the multiple data platforms can include a big data center, an emergency department system, and other industry department systems. In addition, the initial ledger data actively submitted by safety supervision objects can also be obtained.

[0037] In this implementation manner, the safety supervision object identifier may be an enterprise credit code. The safety supervision object identifier may also be a code defined by the ledger data platform for the safety supervision object.

[0038] In a specific implementation process of this implementation manner, data cleaning processing, verification processing, and conversion processing may be performed on the initial ledger data after fusion processing to obtain the ledger data to be processed.

[0039] In this way, by preprocessing the multi-source initial ledger data collected, while ensuring the accuracy of the ledger data, the data processing volume of subsequent data repair and update processing can also be reduced.

[0040] Optionally, in a possible implementation manner of this embodiment, the missing data may include missing venue address data. In step 102, specifically, in response to determining that there is missing venue address data in the ledger data, the missing venue address data may be sent to the first repair level management terminal to obtain the first repair result of the first repair level management terminal. In response to determining that the first repair result is a repair failure, the missing venue address data may be sent to the second repair level management terminal to obtain the second repair result of the second repair level management terminal. In response to determining that the second repair result is a repair failure, the missing venue address data may be sent to the third repair level management terminal to obtain the third repair result of the third repair level management terminal. In response to determining that the third repair result is a repair success, the ledger data after repair processing is obtained.

[0041] In this implementation manner, the missing venue address data may include partial missing data, complete missing data, and unupdated venue address data.

[0042] In this implementation manner, the first repair level management terminal may be a sub-district level management terminal. The second repair level management terminal may be a district level management terminal, and the third repair level management terminal may be a competent industry department.

[0043] In a specific implementation process of this implementation manner, after obtaining the ledger data after repair processing, the ledger data may be stored in the ledger database.

[0044] In a specific implementation process of this implementation manner, the first repair level management terminal, the second repair level management terminal, and the third repair level management terminal may respectively also review the partial missing data and the unupdated venue address data and perform corresponding repair processing.

[0045] It should be noted that the specific implementation process provided in this implementation manner can be combined with various specific implementation processes provided in the foregoing implementation manner to implement the method for processing ledger data in this embodiment. For a detailed description, reference can be made to the relevant content in the foregoing implementation manner, which will not be elaborated here.

[0046] Optionally, in a possible implementation manner of this embodiment, in step 103, the address data in the ledger data of the repair process can be specifically obtained, and then the address data can be segmented to obtain the segmented text data at the geographical level. Based on the segmented text data, using a preset address error correction algorithm, the error confidence of the ledger data of the repair process is calculated.

[0047] In a specific implementation process of this implementation manner, first, the municipal-level text data and district / street-level text data in the segmented text data can be obtained. Secondly, based on a preset address corpus and the municipal-level text data and district / street-level text data, the municipal-level error confidence corresponding to the municipal-level text data and the district / street-level error confidence corresponding to the district / street-level text data can be calculated respectively. Thirdly, based on the municipal-level error confidence or the district / street-level error confidence, the address anomaly confidence can be obtained. Thirdly, the segmented text data is input into a pre-trained address semantic model to obtain the semantic anomaly confidence. Thirdly, the segmented text data can be verified using a location-based service to obtain the spatio-temporal anomaly confidence. Thirdly, based on the address anomaly confidence, semantic anomaly confidence, and spatio-temporal anomaly confidence, the error confidence of the ledger data of the repair process is calculated.

[0048] In this implementation manner, the preset address corpus can be a standard address library.

[0049] In one case of this specific implementation process, the error confidence of the ledger data of the repair process can be calculated based on the address anomaly confidence, the proportion coefficient of the address anomaly confidence, the semantic anomaly confidence, the proportion coefficient of the semantic anomaly confidence, the proportion coefficient of the spatio-temporal anomaly confidence, and the spatio-temporal anomaly confidence.

[0050] In this way, by detecting the address data in the ledger data, the ledger data with address errors can be determined, further improving the accuracy of the ledger data.

[0051] It should be noted that the specific implementation process provided in this implementation manner can be combined with various specific implementation processes provided in the foregoing implementation manner to implement the method for processing ledger data in this embodiment. For a detailed description, reference can be made to the relevant content in the foregoing implementation manner, which will not be elaborated here.

[0052] Optionally, in a possible implementation manner of this embodiment, in step 104, specifically, in response to the error confidence level satisfying the preset update condition, obtain the safety supervision object identifier in the ledger data of the repair process, and then, based on the safety supervision object identifier, update the address data of the safety supervision object until the error confidence level does not satisfy the preset update condition, and obtain the target ledger data of the safety supervision object based on the ledger data corresponding to the error confidence level that does not satisfy the preset update condition.

[0053] In this implementation manner, the preset update condition may be that the error confidence level reaches a preset threshold. This preset threshold may be determined according to actual data detection requirements.

[0054] In a specific implementation process of this implementation manner, based on the safety supervision object identifier, output an address data error prompt message, and in response to the operation of the reviewer to update the address information, update and obtain the address data of the safety supervision object.

[0055] In this way, by correcting the incorrect address data in the ledger data, the accuracy of the ledger data is further improved.

[0056] It should be noted that the specific implementation process provided in this implementation manner can be combined with the multiple specific implementation processes provided in the foregoing implementation manner to implement the processing method of the ledger data in this embodiment. For a detailed description, refer to the relevant content in the foregoing implementation manner, and details are not described herein again.

[0057] To better understand the method of this embodiment of the present application, the method of this embodiment of the present application will be described below in conjunction with the accompanying drawings and specific application scenarios.

[0058] Figure 2 is a schematic flowchart of a processing method for ledger data of a safety supervision object provided in another embodiment of the present application, as Figure 2 shown. The processing method for ledger data of the safety supervision object can be applied to a ledger data platform for safety supervision objects, and specifically includes the following steps:

[0059] Step 201: Obtain the initial ledger data of the safety supervision object from multiple data platforms, where the initial ledger data includes the safety supervision object identifier.

[0060] In this embodiment, the ledger data of the safety supervision object may include the basic ledger data of the object, the site ledger data of the object, and other associated ledger data, etc.

[0061] Optionally, the security supervision object may be an enterprise, etc. The basic ledger data of the object may include but is not limited to the enterprise organization code, enterprise organization type, legal person name, legal person phone number, economic type, business status, business term, tax status, registered address, industry category, regulatory department, etc.

[0062] Optionally, the venue ledger data of the object may include, but is not limited to, the venue name, the code of the district where the venue is located, the name of the district where the venue is located, the code of the street where the venue is located, the name of the street where the venue is located, the community where the venue is located, the venue address, the venue person in charge, the venue area, the number of employees in the venue, and information on related companies.

[0063] Here, the associated enterprise information may be information stored as redundancy, and may include enterprise name, enterprise credit code, enterprise registration address, enterprise legal person telephone number, industry category to which the enterprise belongs, etc.

[0064] In this embodiment, the ledger data of the security supervision object can be obtained from the big data center, the emergency department system, other industry department systems, and the enterprise itself.

[0065] Exemplarily, on the one hand, the basic data of the safety supervision object can be synchronized from the big data center to obtain the ledger data of the safety supervision object. For example, the big data center can collect basic data such as enterprises and individual industrial and commercial households from various market industry departments. These basic data are generally identified by organization codes and standard enterprise credit codes, and the data volume is large and updated frequently. On the other hand, historical enterprise information related to production safety can be imported from the emergency department system. On the other hand, special license data of enterprises related to production safety can be directly obtained from industry departments. On the other hand, relevant ledger data can also be obtained by enterprise personnel entering and updating enterprise ledger data on the ledger data platform. Here, for some enterprises that are not market regulated and do not have enterprise credit codes, enterprise-related codes can be generated by the ledger data platform.

[0066] Step 202: Based on the security supervision object identifier, the initial ledger data of multiple data platforms are integrated to obtain the ledger data to be processed.

[0067] In this embodiment, the security supervision object identifier can be an enterprise credit code or a custom code of the ledger data platform.

[0068] Here, the basic data of the security supervision objects from various data sources can be unified and integrated based on the enterprise credit code or custom code to obtain the ledger data of the security supervision objects. The ledger data of the security supervision objects from all data sources can be updated and operated according to the enterprise credit code. The enterprise credit code of each security supervision object can be used as the unique identifier of the security supervision object.

[0069] In this embodiment, the update priority of each data source can also be set. When synchronously collecting data, the data with higher priority can cover the data with lower priority, solving the problem of duplicate data. Here, the more original the data source, the higher the priority.

[0070] In this embodiment, when obtaining batch ledger data, the interface synchronization method can be used to collect incremental and full data. When the data source is very large and the query is slow, it can also be customized to support paging and segmented submission.

[0071] In this embodiment, the collected initial ledger data may be pre-processed by data cleaning, verification, conversion, etc.

[0072] In this embodiment, the data source may include a primary data source and a secondary data source. When the data of some fields of the primary data source are not first-hand data sources, the data of these fields can be obtained from other secondary data sources in real time when the initial ledger data is cleansed.

[0073] Exemplarily, the synchronization master data source is a big data center. When the tax data in the ledger data of the security supervision object is incomplete or not real-time, the relevant tax data of the security supervision object can be synchronized in real time from the tax department's system.

[0074] In this embodiment, the ledger data of the safety supervision object can be updated according to a preset period, and the redundant data in the location ledger data of the safety supervision object can be updated, thereby improving the response speed of the ledger data platform.

[0075] It is understandable that since the initial ledger data of the safety supervision object can come from multiple data sources, the ledger data structure can only retain the basic field information required for emergency hazard investigation.

[0076] Step 203: Determine whether there is any missing data in the ledger data.

[0077] Step 204: In response to determining that there is missing data in the ledger data, the missing data is repaired using multi-level data repair rules to obtain repaired ledger data.

[0078] In this embodiment, before the ledger data is stored in the ledger database, the missing data in the ledger data can be repaired. Here, multiple repair level management terminals can be determined based on the street, district, and industry competent department to which the security supervision object belongs. Multiple repair level management terminals can repair and review the missing data, and the ledger data after repair and review can be stored in the ledger database.

[0079] Preferably, the missing data may include missing venue address data. Here, the missing venue address data may include partial missing data, complete missing data, and un-updated data.

[0080] Preferably, the repair level management terminal may include a first repair level management terminal, a second repair level management terminal, and a third repair level management terminal. The first repair level management terminal may be a street-level management terminal. The second repair level management terminal may be a district-level management terminal, and the third repair level management terminal may be an industry competent department.

[0081] In this embodiment, Figure 3 is a schematic flow chart of missing data review and repair in the method for processing ledger data provided by another embodiment of this application, as Figure 3 shown. When starting to obtain ledger data, processing of adding / modifying / restoring ledger data can be performed. The missing venue address data in the ledger data can be sent to the first repair level management terminal for the administrator of the first repair level management terminal to perform review and repair processing on the missing venue address data. If successful, it can be stored in the database. If failed, the missing venue address data can be sent to the second repair level management terminal for the administrator of the second repair level management terminal to perform review and repair processing on the missing venue address data. If successful, it can be stored in the database. If failed, the missing venue address data can be sent to the third repair level management terminal. If successful, it can be stored in the database. If failed, it will be temporarily stored. The processing flow ends after storage in the database.

[0082] It can be understood that in the actual application scenario, the update frequency of the basic ledger data of the object is relatively low. The update frequency of the venue ledger data of the object is relatively high. For example, the registered address of an enterprise may be one and usually changes less frequently, while the business venue addresses of an enterprise may be multiple and usually change more frequently. Therefore, there may be missing or un-updated venue ledger data of the object. Generally, the local administrative department of the enterprise and its competent unit can timely learn about the changes in the venue ledger data of the object. Therefore, the missing data can be repaired and reviewed by multiple-level management departments.

[0083] Moreover, for some venue ledger fields, the enterprise cannot provide them accurately. For example, information such as the address, street, community, and competent unit of the business venue ledger. Here, by taking the local department of the enterprise as the execution subject for the repair and review of the missing ledger data, the burden on the enterprise can be reduced while ensuring the stability and reliability of the venue ledger data.

[0084] In this embodiment, the storage of the site ledger data of the safety supervision objects can be repaired and audited by the management terminals at all levels of the sub-district, district, and the competent department of the industry to which they belong based on the above-mentioned audit process. Moreover, on the basis of setting multi-level audits, the emergency safety suspicious site ledgers are mainly audited in terms of business, and the site ledgers with relatively high certainty are quickly released.

[0085] In this embodiment, when deleting the ledger data, that is, when performing the ledger data out-of-library processing, multi-level audits can also be set. On this basis, the out-of-library of the site ledger with obvious errors is mainly audited, and the ledgers without obvious major changes are carefully deleted.

[0086] In addition, in this embodiment, for the storage and out-of-library of any site ledger data, logs are recorded. Through the logs, it can be traced to ensure that the updates are controllable and the changes are traceable, and the data cannot be arbitrarily tampered with through integrated permissions.

[0087] Step 205: Obtain the address data in the repaired ledger data.

[0088] In this embodiment, the address data may include, but is not limited to, the registered address data and the site address data.

[0089] It can be understood that in emergency safety management, it is necessary to quickly locate the safety supervision objects so that emergency safety management personnel can conduct on-site safety inspections and remote safety monitoring. The validity and accuracy of the address data of the safety supervision objects are crucial. Here, the address data of the ledger data stored in the ledger database is further detected to ensure the accuracy of the address data.

[0090] Step 206: Perform word segmentation on the address data to obtain the word segmentation text data at the geographical level.

[0091] Step 207: Based on the word segmentation text data, use a preset address error correction algorithm to calculate the error confidence of the repaired ledger data.

[0092] In this embodiment, first, use a word segmentation tool to divide the address data into word segmentation text data at the four geographical levels of standard city, district, street, and community. Secondly, perform address structure verification processing, semantic similarity analysis processing, and spatio-temporal rationality analysis processing on the word segmentation text data respectively to obtain the address anomaly confidence, semantic anomaly confidence, and spatio-temporal anomaly confidence. Finally, combine the address anomaly confidence, semantic anomaly confidence, and spatio-temporal anomaly confidence to calculate the final error confidence.

[0093] Preferably, the word segmentation tool can be the Python jieba toolkit. The exact word segmentation mode of the word segmentation tool can be used to divide the address text description into structured word segmentation text data of city, district, street, and community, obtaining city-level text data, district / street-level text data, and community-level text data.

[0094] Preferably, the city-level text data and the district / street-level text data are respectively matched with a preset address corpus to obtain the city-level error confidence corresponding to the city-level text data and the district / street-level error confidence corresponding to the district / street-level text data. The preset address corpus can be a standard address library.

[0095] Exemplarily, if the city-level address data is not matched in the preset address corpus, the city-level error confidence of 0.7 is directly obtained. If the city-level address data can be matched and the district / street address data is not matched, the district / street-level error confidence of 0.6 is obtained. Further, the city-level error confidence or the district / street-level error confidence can be used as the address anomaly confidence. The address anomaly confidence can be denoted as .

[0096] Preferably, first, the word segmentation text data can be input into a pre-trained address language model (Address-BERT), and the output is the semantic similarity. The value range of the semantic similarity is [0, 1], and this semantic similarity can represent the maximum semantic similarity between the word segmentation text data and the standard address library. Second, the semantic anomaly confidence can be obtained by subtracting the semantic similarity from 1, which can be denoted as .

[0097] Here, a preset vector database can also be used to calculate the semantic similarity between the word segmentation text data and the standard address library, and then subtract the semantic similarity from 1 to obtain the semantic anomaly confidence.

[0098] Preferably, first, the location-based service (LBS) can be used to verify whether the address corresponding to the word segmentation text data exists, and the spatio-temporal anomaly confidence can be directly obtained .

[0099] Here, the location-based service (LBS) can also be used to verify whether the address corresponding to the word segmentation text data exists and obtain the spatial anomaly confidence. Then, the time verification rule can be used to automatically check the rationality of the time of the word segmentation text data and obtain the time anomaly confidence. For example, in the word segmentation text data of "Pudong New Area, Shanghai (abolished in 2023)", 2024 is included, and the time anomaly confidence of this word segmentation text is 0.7. Finally, based on the spatial anomaly confidence or the time anomaly confidence, the spatio-temporal anomaly confidence is obtained.

[0100] Preferably, the finally obtained error confidence , can be shown by the following formula: Wherein, is the address anomaly confidence, is the semantic anomaly confidence, is the spatio-temporal anomaly confidence, are the proportion coefficients of the three confidences respectively, and satisfy . Here, the specific value of can be adjusted according to the actual evaluation requirements.

[0101] Step 208, based on the preset update condition and the error confidence, update the ledger data of the repair process to obtain the target ledger data of the safety supervision object.

[0102] In this embodiment, the preset update condition may be that the error confidence reaches a preset threshold. The preset threshold may be determined according to the actual data detection requirements.

[0103] It can be understood that after the ledger data is stored in the database, by batch-checking the address data in the ledger data, the data with high error confidence is found and the prompt reference information is output, further ensuring the reliability of the ledger data.

[0104] In this embodiment, here, for the address data whose error confidence reaches the preset threshold, based on the safety supervision object identifier, the candidate address data of the safety supervision object can be updated again, and the newly obtained candidate address data is input into the preset address recognition model to identify the final address data.

[0105] In this embodiment, by adopting the technical solution in this embodiment, through multi-source batch data collection of the ledger, record retention for ledger data update, and quality inspection after the ledger data is stored in the database, the accuracy and timeliness of the ledger data of the safety supervision object in the emergency field are improved.

[0106] In addition, by adopting the technical solution in this embodiment, through real-time docking of multi-source data, batch collection of the basic information of the safety supervision object, and data fusion, the comprehensiveness and timeliness of the collected ledger data are ensured.

[0107] In addition, by adopting the technical solution in this embodiment, through introducing multi-level repair and review processes during the ledger data collection and update process, and recording each change of the ledger data, the traceability and accuracy of the data change are ensured.

[0108] In addition, by adopting the technical solution in this embodiment, the quality inspection of the ledger data after warehousing can be carried out by adopting the intelligent error correction technology for address data, identifying and correcting the error address field information, and further improving the accuracy of the ledger data.

[0109] Figure 4 Fig. shows a structural block diagram of a processing device for ledger data of a safety supervision object provided by an embodiment of the present application, as Figure 4 shown. The processing device 400 for the ledger data of the safety supervision object in this embodiment may include an acquisition unit 401, a repair unit 402, a determination unit 403, and an acquisition unit 404. Among them, the acquisition unit 401 is used to acquire the to-be-processed ledger data of the safety supervision object; the repair unit 402 is used to, in response to determining that there is missing data in the ledger data, use a multi-level data repair rule to repair the missing data to obtain the repaired ledger data; the determination unit 403 is used to, based on the repaired ledger data, use a preset address error correction algorithm to determine the error confidence level of the repaired ledger data; the acquisition unit 404 is used to, based on a preset update condition and the error confidence level, perform an update process on the repaired ledger data to obtain the target ledger data of the safety supervision object.

[0110] It should be noted that part or all of the processing device for the ledger data of the safety supervision object in this embodiment may be an application located on the local terminal, or may also be a functional unit such as a plug-in or a software development kit (SDK) set in the application located on the local terminal, or may also be a processing engine located in the network-side server, or may also be a distributed system located on the network side. For example, the processing engine or the distributed system in the ledger data platform of the safety supervision object on the network side, etc. This embodiment does not make a special limitation on this.

[0111] It can be understood that the application may be a native application installed on the local terminal, or may also be a web application of a browser on the local terminal. This embodiment does not limit this.

[0112] Optionally, in a possible implementation manner of this embodiment, the acquisition unit 401 is used to acquire the initial ledger data of the safety supervision object from multiple data platforms; the initial ledger data includes a safety supervision object identifier; based on the safety supervision object identifier, the initial ledger data of multiple data platforms is fused to obtain the to-be-processed ledger data.

[0113] Optionally, in a possible implementation of this embodiment, the missing data includes missing venue address data. The repair unit 402 is configured to, in response to determining that there is missing venue address data in the ledger data, send the missing venue address data to the first-level repair management terminal to obtain a first repair result from the first-level repair management terminal; in response to determining that the first repair result is a repair failure, send the missing venue address data to the second-level repair management terminal to obtain a second repair result from the second-level repair management terminal; in response to determining that the second repair result is a repair failure, send the missing venue address data to the third-level repair management terminal to obtain a third repair result from the third-level repair management terminal; and in response to determining that the third repair result is a successful repair, obtain the ledger data after repair processing.

[0114] Optionally, in a possible implementation of this embodiment, the determination unit 403 is configured to obtain address data in the ledger data after repair processing; perform word segmentation on the address data to obtain word-segmented text data at the geographical level; and based on the word-segmented text data, use a preset address error correction algorithm to calculate the error confidence level of the ledger data after repair processing.

[0115] Optionally, in a possible implementation of this embodiment, the determination unit 403 is configured to obtain municipal-level text data and district / street-level text data in the word-segmented text data; respectively calculate a municipal-level error confidence level corresponding to the municipal-level text data and a district / street-level error confidence level corresponding to the district / street-level text data based on a preset address corpus, the municipal-level text data, and the district / street-level text data; obtain an address anomaly confidence level based on the municipal-level error confidence level or the district / street-level error confidence level; input the word-segmented text data into a pre-trained address semantic model to obtain a semantic anomaly confidence level; use location-based services to perform verification processing on the word-segmented text data to obtain a spatio-temporal anomaly confidence level; and calculate the error confidence level of the ledger data after repair processing based on the address anomaly confidence level, the semantic anomaly confidence level, and the spatio-temporal anomaly confidence level.

[0116] Optionally, in a possible implementation of this embodiment, the obtaining unit 404 is configured to, in response to the error confidence level satisfying the preset update condition, obtain a safety supervision object identifier in the ledger data after repair processing; update the address data of the safety supervision object based on the safety supervision object identifier until the error confidence level does not satisfy the preset update condition; and obtain the target ledger data of the safety supervision object based on the ledger data corresponding to the error confidence level that does not satisfy the preset update condition.

[0117] In this embodiment, the acquisition unit can acquire the ledger data to be processed of the safety supervision object. Then, in response to determining that there is missing data in the ledger data, the repair unit can use multi-level data repair rules to repair the missing data to obtain the repaired ledger data. The determination unit can determine the error confidence level of the repaired ledger data by using a preset address error correction algorithm based on the repaired ledger data. The acquisition unit can update the repaired ledger data based on a preset update condition and the error confidence level to obtain the target ledger data of the safety supervision object. Since the missing data in the acquired ledger data can be supplemented and repaired according to the repair rules, the integrity of the collected ledger data is ensured, and the reliability and accuracy of the ledger data of the safety supervision object are improved by detecting the accuracy of the address data in the repaired ledger data.

[0118] In the technical solution of the present application, the processing of the user's personal information involved, such as the collection, storage, use, processing, transmission, provision, and disclosure of the user's images and attribute data, etc., all comply with the provisions of relevant laws and regulations and do not violate public order and good customs.

[0119] According to the embodiments of the present application, the present application also provides an electronic device, a readable storage medium, and a computer program product.

[0120] Figure 5 FIG. shows a schematic block diagram of an exemplary electronic device 500 that can be used to implement the embodiments of the present application. The electronic device is intended to represent various forms of digital computers, such as, a laptop computer, a desktop computer, a workbench, a personal digital assistant, a server, a blade server, a mainframe computer, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as, a personal digital processor, a cellular phone, a smart phone, a wearable device, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present application described and / or claimed herein.

[0121] As Figure 5 shown, the electronic device 500 includes a computing unit 501, which can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 502 or the computer program loaded from the storage unit 508 into the random access memory (RAM) 503. In the RAM 503, various programs and data required for the operation of the electronic device 500 can also be stored. The computing unit 501, the ROM 502, and the RAM 503 are connected to each other through a bus 504. The input / output (I / O) interface 505 is also connected to the bus 504.

[0122] Multiple components in the electronic device 500 are connected to the I / O interface 505, including: an input unit 506, such as a keyboard, a mouse, etc.; an output unit 507, such as various types of displays, speakers, etc.; a storage unit 508, such as a magnetic disk, an optical disc, etc.; and a communication unit 509, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 509 allows the electronic device 500 to exchange information / data with other devices via a computer network such as the Internet and / or various telecommunication networks.

[0123] The computing unit 501 can be various general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of the computing unit 501 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. The computing unit 501 executes the various methods and processes described above, such as the method for processing ledger data. For example, in some embodiments, the method for processing ledger data can be implemented as a computer software program, which is tangibly contained in a machine-readable medium, such as the storage unit 508. In some embodiments, part or all of the computer program can be loaded and / or installed onto the electronic device 500 via the ROM 502 and / or the communication unit 509. When the computer program is loaded into the RAM 503 and executed by the computing unit 501, one or more steps of the method for processing ledger data described above can be executed. Alternatively, in other embodiments, the computing unit 501 can be configured to execute the method for processing ledger data in any other suitable manner (e.g., by means of firmware).

[0124] The various embodiments of the systems and technologies described above in this document can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SOCs), complex programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments can include: being implemented in one or more computer programs, which can be executed and / or interpreted on a programmable system including at least one programmable processor, the programmable processor can be a special or general-purpose programmable processor, can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit the data and instructions to the storage system, the at least one input device, and the at least one output device.

[0125] The program code for implementing the methods of the present application can be written in any combination of one or more programming languages. These program codes can be provided to a processor or controller of a general-purpose computer, a special-purpose computer, or other programmable data processing devices, such that when the program codes are executed by the processor or controller, the functions / operations specified in the flowcharts and / or block diagrams are implemented. The program codes can be executed entirely on the machine, partially on the machine, executed partially on the machine and partially on a remote machine as an independent software package, or executed entirely on a remote machine or server.

[0126] In the context of the present application, a machine-readable medium can be a tangible medium that can contain or store a program for use by or in connection with an instruction execution system, apparatus, or device. A machine-readable medium can be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium can include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination of the foregoing. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, 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 disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0127] In order to provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or a trackball) through which the user can provide input to the computer. Other kinds of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and the input from the user can be received in any form (including acoustic input, speech input, or tactile input).

[0128] The systems and techniques described herein can be implemented in a computing system that includes backend components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes frontend components (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described herein), or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system can be interconnected with each other by digital data communication in any form or medium (e.g., a communication network). Examples of communication networks include: local area network (LAN), wide area network (WAN), and the Internet.

[0129] A computer system can include a client and a server. The client and the server are generally far from each other and typically interact through a communication network. The client-server relationship is generated by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, a server of a distributed system, or a server combined with a blockchain.

[0130] It should be understood that various forms of the processes shown above can be used, steps can be reordered, added, or deleted. For example, the steps recited in this disclosure can be executed in parallel, sequentially, or in a different order, as long as the desired results of the technical solutions disclosed in this application can be achieved, and this is not limited herein.

[0131] The above specific embodiments do not constitute a limitation on the protection scope of this application. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this application shall be included within the protection scope of this application.

Claims

1. A method for processing ledger data of safety supervision objects, characterized in that, The method includes: Obtaining the ledger data to be processed of the safety supervision object; In response to determining that there is missing data in the ledger data, using multi-level data repair rules to repair the missing data to obtain the repaired ledger data; Based on the repaired ledger data, using a preset address error correction algorithm to determine the error confidence level of the repaired ledger data; Based on a preset update condition and the error confidence level, performing an update process on the repaired ledger data to obtain the target ledger data of the safety supervision object.

2. The method according to claim 1, characterized in that, The obtaining the ledger data to be processed of the safety supervision object includes: Obtaining the initial ledger data of the safety supervision object from multiple data platforms; the initial ledger data includes the safety supervision object identifier; Based on the safety supervision object identifier, performing a fusion process on the initial ledger data of multiple data platforms to obtain the ledger data to be processed.

3. The method according to claim 1, characterized in that, The missing data includes missing data of the venue address. In response to determining that there is missing data in the ledger data, using multi-level data repair rules to repair the missing data to obtain the repaired ledger data, including: In response to determining that there is missing data of the venue address in the ledger data, sending the missing data of the venue address to the first repair level management terminal to obtain the first repair result of the first repair level management terminal; In response to determining that the first repair result is a repair failure, sending the missing data of the venue address to the second repair level management terminal to obtain the second repair result of the second repair level management terminal; In response to determining that the second repair result is a repair failure, sending the missing data of the venue address to the third repair level management terminal to obtain the third repair result of the third repair level management terminal; In response to determining that the third repair result is a repair success, obtaining the repaired ledger data.

4. The method according to claim 1, characterized in that, The determining the error confidence level of the repaired ledger data based on the repaired ledger data and using a preset address error correction algorithm includes: Obtaining the address data in the repaired ledger data; Performing word segmentation on the address data to obtain word segmentation text data at the geographical level; Based on the word segmentation text data, using a preset address error correction algorithm to calculate and obtain the error confidence level of the repaired ledger data.

5. The method according to claim 4, characterized in that, The calculating and obtaining the error confidence level of the repaired ledger data based on the word segmentation text data and using a preset address error correction algorithm includes: Obtaining the municipal text data and the district / street level text data in the word segmentation text data; Based on a preset address corpus and the municipal text data and the district / street level text data, respectively calculating and obtaining the municipal error confidence level corresponding to the municipal text data and the district / street level error confidence level corresponding to the district / street level text data; Based on the municipal error confidence level or the district / street level error confidence level, obtaining an address anomaly confidence level; Inputting the word segmentation text data into a pre-trained address semantic model to obtain a semantic anomaly confidence level; Verify the segmented text data by using location-based services to obtain the spatio-temporal anomaly confidence level; Calculate the error confidence level of the ledger data after the repair process based on the address anomaly confidence level, semantic anomaly confidence level, and spatio-temporal anomaly confidence level.

6. The method according to claim 1, characterized in that, Update the ledger data after the repair process based on the preset update conditions and the error confidence level to obtain the target ledger data of the safety supervision object, including: In response to the error confidence level meeting the preset update conditions, obtain the safety supervision object identifier in the ledger data after the repair process; Based on the safety supervision object identifier, update the address data of the safety supervision object until the error confidence level does not meet the preset update conditions; Obtain the target ledger data of the safety supervision object based on the ledger data corresponding to the error confidence level that does not meet the preset update conditions.

7. A device for processing ledger data of safety supervision objects, characterized in that, The device includes: An acquisition unit configured to acquire the ledger data to be processed of the safety supervision object; A repair unit configured to, in response to determining that there is missing data in the ledger data, repair the missing data by using multi-level data repair rules to obtain the ledger data after the repair process; A determination unit configured to determine the error confidence level of the ledger data after the repair process by using a preset address error correction algorithm based on the ledger data after the repair process; An acquisition unit configured to update the ledger data after the repair process based on the preset update conditions and the error confidence level to obtain the target ledger data of the safety supervision object.

8. An electronic device, characterized in that, Comprising: 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, and the instructions are executed by the at least one processor so that the at least one processor can execute the method according to any one of claims 1-6.

9. A non-transitory computer-readable storage medium storing computer instructions, characterized in that, The computer instructions are used to cause the computer to execute the method according to any one of claims 1-6.

10. A computer program product, characterized in that, Comprising a computer program which, when executed by a processor, implements the method according to any one of claims 1-6.

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