Bidding enterprise compliance determination method and system based on government data fusion
By integrating and sharing government data, the problem of insufficient comprehensive and in-depth processing of internal government data has been resolved, effective judgment of the compliance of bidding companies has been achieved, and the depth and breadth of data application has been enhanced.
Patent Information
- Application Number
- CN202510690829.7
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-05-27
- Publication Date
- 2025-09-12
- Estimated Expiration
- Not applicable · inactive patent
AI Technical Summary
At present, governments at all levels in China are still in the exploratory stage in terms of data openness, sharing and application. The lack of mature data fusion models has led to the failure to fully and deeply process internal government data and the neglect of the correlation between data.
A bidding enterprise compliance determination method and system based on government data fusion is proposed. Through data resource sorting, database table design, data collection and storage, data processing and analysis, and data service application, the integration and sharing of internal government data are realized.
It realizes the sharing and integration of internal government data, provides data models and data services, and provides data support for internal government managers to judge the compliance of bidding companies, thereby improving the depth and breadth of data application.
Smart Images
Figure CN120634578A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the field of big data information processing technology, and specifically to a bidding enterprise compliance determination method and system based on government data fusion. Background Art
[0002] With the rapid development of information technology, the internet, the Internet of Things, and big data technologies, and the rapid growth of data such as text, images, audio, and video, humanity has officially entered the era of big data. Data has permeated every industry and business function today, becoming a vital factor in production. The mining and utilization of massive amounts of data heralds a new wave of productivity growth and consumer surplus. At the same time, the national government has repeatedly emphasized the importance of "cloud-based government affairs" and "government transparency" in the big data era, strengthening the management and application of internal government data.
[0003] However, at present, governments at all levels in China are still in the exploratory research stage for open data sharing applications. The sharing platforms they have built are mostly at the level of sorting data sets, and have not comprehensively and deeply processed the data sets within the government. They have ignored the relationship between data from various departments, and there is no mature data fusion model to support data applications. Summary of the Invention
[0004] The purpose of the present invention is to provide a bidding enterprise compliance determination method and system based on government data fusion to solve the problems raised in the above background technology.
[0005] To achieve the above objectives, the present invention provides the following technical solution: a method for determining compliance of bidding enterprises based on government data fusion, comprising the following steps:
[0006] Data resource sorting: Based on the data requirements list and actual conditions, sort out the corresponding data resources, search for resources on the shared platform, identify and analyze them, and select appropriate resources. For resources that meet the requirements, confirm the information items, compile a list of missing or problematic information items, and a list related to unshared data requirements. Integrate data resources and information item-related issues to form a project data requirements list and send it to each business department for comments.
[0007] Database table design: Design core table structures and business table structures. The core table structure includes the core fields of enterprise name, unified social credit code, legal representative information, bidder name, citizen ID number, whether the enterprise is an employee, whether the enterprise has abnormal business operations, and whether social security payments are made on time, as well as their source departments and directories. The business table structure covers information on abnormal business operations, bidding enterprise information, bidder information, social security payment information, enterprise basic information query database table names, and their core information items.
[0008] Data collection and storage: Adopting a data warehouse solution, using ETL tools to extract data from data sources, and after data cleaning, loading it into the data warehouse according to the pre-defined data warehouse model; for data with high confidentiality requirements, it is collected by connecting to the government external network and using specific system interfaces. At the same time, the data collection layer provides data update and data quality verification functions; data storage adopts a combination of relational databases and non-relational databases, and the government's internal structured data is stored in the relational database MySQL.
[0009] Preferably, the data processing and analysis step specifically includes:
[0010] Business understanding and data sorting: Familiarize yourself with and classify the structured data of different commissions and bureaus, sort out the structured data containing enterprise information, and discover field primary keys that can be used for data fusion, such as the "unified social credit code";
[0011] Data conversion: Select the primary key of the data fusion field for each data source, mainly using numeric data fields and supplemented by character data, mark the primary keys of the data fields that can be fused, convert the formats of data sets from different data sources, and unify the standard formats of data elements and data dictionaries;
[0012] Data combination and storage: Create a new data fusion table to connect the dimensions of data from different departments, sort out the data set structure of each fusion, create a new table structure containing all fusion data fields in the new data table, and summarize the table content in the new data fusion table according to the data fusion fields;
[0013] Data identification rules: Data comparison and verification is carried out based on the bidding enterprise information and bidder information list provided by the public resource transaction center, the list of enterprises with abnormal business operations of the market supervision department, and the social security payment information of the human resources and social security department. This includes verifying the unified social credit code through the enterprise basic information query interface, comparing with the list of enterprises with abnormal business operations to verify whether it is an enterprise with abnormal business operations, and comparing with the social security payment information to verify whether the bidder is an employee of the enterprise and whether the social security has been paid on time.
[0014] Preferably, in the data discrimination rules, when comparing and verifying with the list of enterprises with abnormal operations, if the bidding enterprise is an enterprise with abnormal operations, the enterprise will be labeled "Is it an enterprise with abnormal operations" and the field value will be "Yes"; if the bidding enterprise is not matched in the list of enterprises with abnormal operations, the field value of "Is it an enterprise with abnormal operations" will be "No".
[0015] Preferably, in the data discrimination rules, when comparing and verifying with the social security payment information, if the social security payment unit of the bidder is the same as the bidding enterprise, the value of the "Is it an enterprise employee" field is "Yes"; if they are inconsistent, it is "No"; if the social security paying enterprise is the bidding enterprise, the bidding time and the social security payment time are compared. If the social security has been paid one month before the bid, the value of the "Whether the social security has been paid according to the prescribed time" field is "Yes"; if there is no payment record or it has not been paid one month ago, it is "No".
[0016] Preferably, the data service application step includes:
[0017] Bidding Enterprise Compliance Information Query Service: This service uses the unified social credit code as the associated field to query the compliance information of bidding enterprises. Input the unified social credit code, enterprise name, bidder name, and bidder's citizen ID number. Output includes the bidding enterprise name, unified social credit code, whether the bidding enterprise has abnormal operations, whether the bidder is an employee of the enterprise, and whether the social security payment time meets the standards.
[0018] Bidding enterprise compliance information verification service: Input the unified social credit code, enterprise name, bidder name, and bidder citizen ID number, and output the bidding enterprise name, unified social credit code, and compliance information through data model fusion and data verification;
[0019] Compliance information comparison service for bidding enterprises: Compare the data list of bidding enterprises and bidders provided by the customer with the generated bidding enterprise information data to generate comparison results.
[0020] A system for determining compliance of bidding enterprises based on government data fusion, comprising:
[0021] Data resource sorting module: This module is used to sort out the corresponding data resources according to the data requirements list and actual conditions, search for resources from the shared platform, identify and analyze them, and select appropriate resources. For resources that meet the requirements, the module verifies the information items, compiles a list of missing or problematic information items, and a list of unshared data requirements. The module integrates data resources and information item-related issues to form a project data requirements list, which is then sent to various business departments for comments.
[0022] Database table design module: used to design core table structures and business table structures. The core table structure includes the core fields of enterprise name, unified social credit code, legal representative information, bidder name, citizen ID number, whether the enterprise is an employee, whether the enterprise has abnormal business operations, whether social security is paid on time, and their source departments and directories; the business table structure covers information on abnormal business operations, bidding enterprise information, bidder information, social security payment information, enterprise basic information query database table name and its core information items;
[0023] Data collection and storage module: This module uses a data warehouse solution to extract data from data sources using ETL tools. After data cleaning, data is loaded into the data warehouse according to a pre-defined data warehouse model. For data with high confidentiality requirements, data is collected by connecting to the government extranet and using specific system interfaces. The data collection layer also provides data update and data quality verification functions. Data storage uses a combination of relational and non-relational databases, and internal government structured data is stored in the relational database MySQL.
[0024] Data processing and analysis module: used to integrate and process compliance-related data of bidding companies, including business understanding and data sorting, data conversion, data combination and storage, and data identification rules;
[0025] Data service application module: used to systematically and comprehensively display the processed data, including bidding enterprise compliance information query service, bidding enterprise compliance information verification service, and bidding enterprise compliance information comparison service.
[0026] Preferably, the data discrimination rules in the data processing and analysis module specifically include: when comparing and verifying with the list of enterprises with abnormal operations, if the bidding enterprise is an enterprise with abnormal operations, the enterprise will be labeled "Is it an enterprise with abnormal operations" and the field value will be "Yes"; if the bidding enterprise is not matched in the list of enterprises with abnormal operations, the field value of "Is it an enterprise with abnormal operations" will be "No"; when comparing and verifying with social security payment information, if the social security payment unit of the bidder is the same as that of the bidding enterprise, the field value of "Is it an enterprise employee" will be "Yes"; if not, it will be "No"; if the enterprise paying social security is the bidding enterprise, the bidding time and the social security payment time will be compared. If social security has been paid one month before the bid, the field value of "Whether social security has been paid according to the prescribed time" will be "Yes"; if there is no payment record or it has not been paid one month ago, it will be "No".
[0027] Preferably, in the data resource sorting module, the required data include the abnormal operation list information of the market supervision department, the bidder information of the public resource trading center, the bidding enterprise information, and the social security payment information data of the human resources and social security department; for information items that do not correspond to information items in the demand list, are missing or ambiguous, a list of missing information items or problem information items is compiled; for data requirements that are not shared on the sharing platform, a list of unshared data requirements is compiled.
[0028] Preferably, in the data collection and storage module, for data with high confidentiality requirements for organizational data of party and government agencies, administrative institutions, and judicial agencies, data is collected by connecting to the government external network and using specific system interface-related methods; when storing data, the relational database is mainly used to support the storage of bidding enterprise data, as well as the storage of analysis result data ultimately formed by analysis and comparison.
[0029] Preferably, the data service application module specifically includes:
[0030] Bidding Enterprise Compliance Information Query Service: This service uses the unified social credit code as the associated field to query the compliance information of bidding enterprises. Input the unified social credit code, enterprise name, bidder name, and bidder's citizen ID number. Output includes the bidding enterprise name, unified social credit code, whether the bidding enterprise has abnormal operations, whether the bidder is an employee of the enterprise, and whether the social security payment time meets the standards.
[0031] Bidding enterprise compliance information verification service: Input the unified social credit code, enterprise name, bidder name, and bidder citizen ID number, and output the bidding enterprise name, unified social credit code, and compliance information through data model fusion and data verification;
[0032] Compliance information comparison service for bidding enterprises: Compare the data list of bidding enterprises and bidders provided by the customer with the generated bidding enterprise information data to generate comparison results.
[0033] Compared with the prior art, the present invention has the following beneficial effects:
[0034] The bidding enterprise compliance determination method and system based on government data fusion proposed in the present invention fully utilizes the information data of various government commissions, offices and bureaus, breaks the "information islands" of data between government commissions, offices and bureaus, and realizes data sharing and integration; realizes a comprehensive and systematic sorting of bidding enterprise and bidder data, provides a set of data models and data services, and provides data support for government internal managers to determine the compliance of bidding enterprises; the present invention is highly practical, has a wide range of applications, and is easy to promote, providing a broad idea for government internal personnel to deeply apply data, and promoting the development of government big data environment and industry. BRIEF DESCRIPTION OF THE DRAWINGS
[0035] Figure 1 Flow chart of the method of the present invention. DETAILED DESCRIPTION
[0036] In order to clearly and completely describe the objectives and technical solutions of the present invention and make the advantages more clearly understood, the embodiments of the present invention are further described in detail below with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are part of the embodiments of the present invention, not all of them, and are only used to explain the embodiments of the present invention, not to limit the embodiments of the present invention. All other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.
[0037] For example 1, please refer to Figure 1The present invention provides a technical solution: a bidding enterprise compliance determination method based on government data fusion, the specific technical solution of which includes the following steps:
[0038] Step 1: Organize data resources.
[0039] The present invention sorts out the correspondence of data resources based on the data requirement list and the actual situation. First, search for resources from the shared platform, identify and analyze the searched resources, and select appropriate resources. For resources that meet the requirements, it is necessary to further confirm the information items. If the information items do not correspond to the information items in the requirement list, there are missing or ambiguous items, it is necessary to compile a list of missing information items or problem information items for further communication with the department. For data requirements that are not shared on the shared platform, a list also needs to be compiled to prepare for the next step of soliciting opinions.
[0040] Based on the data resource review, consolidate the data resources and information item-related issues into a project data requirements list, including unshared resources and shared but missing or ambiguous resources. This data requirements list should be sent to each business department to solicit feedback on the data requirements and whether they can be provided or completed. If they cannot be provided or completed, the reasons should be explained.
[0041] The required data includes the abnormal business list information of the market supervision department, the bidder information and bidding enterprise information of the public resource trading center, and the social security payment information data of the human resources and social security department.
[0042] Step 2: Database table design.
[0043] (1) Core table structure
[0044]
[0045] (2) Business table structure
[0046]
[0047]
[0048] Step 3: Data collection and storage.
[0049] Data collection and storage provide important support for the acquisition, synchronization and update of the bidding enterprise compliance determination data model of the present invention, and different data collection and data storage methods need to be provided for different data sources. The solution adopted by the present invention is a data warehouse, which uses ETL (Extract-Transform-Load) to complete data acquisition. The ETL tool extracts the required data from the data source, cleans the data, and finally loads the data into the data warehouse according to the pre-defined data warehouse model. For data with higher confidentiality requirements such as organizational data of party and government agencies, administrative agencies, and judicial agencies, data can be collected by connecting to the government extranet and using specific system interfaces and other related methods. At the same time, the data collection layer provides data update and data quality verification functions.
[0050] Data storage utilizes a combination of relational and non-relational databases, operating in parallel and collaborative ways. Internal government structured data is still stored using the traditional relational database MySQL. The relational database primarily supports the storage of bidding company data. The analysis results generated through analysis and comparison are also stored as structured data in the traditional relational database.
[0051] Step 4: Data processing and analysis.
[0052] Before storing the data in the previous step, it undergoes simple data cleaning and processing, and outlier data that does not meet the dictionary specifications is detected and eliminated. This step will perform data fusion processing on the compliance-related data of the bidding companies. The core of the bidding company compliance determination data model of the present invention is the fusion of internal government data, which is to extract, fuse, and organize relevant data from multiple commissions, bureaus, and multiple data sources into a new data set. This analysis data set is an independent and flexible entity that can be reorganized, adjusted, and updated as the data source changes. The data fusion achieved in the present invention is divided into the following steps:
[0053] (1) Business understanding and data sorting
[0054] Familiarize yourself with and classify the structured data of different commissions and bureaus, sort out the structured data containing enterprise information, study the data, and discover field primary keys that can be used for data integration, such as the "unified social credit code" and other field primary keys.
[0055] (2) Data conversion
[0056] After combing through the data, select the primary key fields for data fusion from each data source, primarily using numeric data fields, supplemented by character data. Mark the primary key fields for data fusion in each data source. Convert the formats of datasets from different data sources, unify the standardized formats of data elements, and standardize the standardized formats of the data dictionary to facilitate the subsequent data fusion process.
[0057] (3) Data combination and storage
[0058] The present invention uses a new data fusion data table to perform dimension concatenation on data from different departments. First, the data set structure of each data fusion is sorted out, and a new table structure containing all fused data fields is established in the new data table, and then the table content is summarized in the new data fusion table according to its data fusion field. Structured data uses a traditional relational database combined with SQL statements to complete. For example, two data sets from different commissions and bureaus, one is a bidding enterprise information data set from the public resource trading center, and the other is a data set of abnormal business enterprises from the market supervision department. The two data sets can be compared through the field primary key mentioned above, and all data dimension fields of the two data sets are concatenated in the new data fusion data table.
[0059] (4) Data discrimination rules
[0060] Data comparison and verification is carried out based on the bidding enterprise information and bidder information list provided by the Public Resources Trading Center, the list of enterprises with abnormal operations from the market supervision department, and the social security payment information from the human resources and social security department.
[0061] Verify the unified social credit code and basic enterprise information through the State Administration for Market Regulation's enterprise basic information query interface;
[0062] Compare and verify with the list of enterprises with abnormal operations. If the bidding enterprise is an enterprise with abnormal operations, the enterprise will be labeled as an abnormal enterprise, and the value of this field will be yes; if the bidding enterprise is not matched in the list of enterprises with abnormal operations, the value of the "Is it an abnormal enterprise" field will be no;
[0063] Compare and verify with the social security payment information. If the social security payment unit of the bidder is the same as that of the bidding enterprise, the value of the "Is the enterprise employee" field is yes; if not, it is no;
[0064] Compare and verify with the social security payment information. If the enterprise paying social security is the bidding enterprise, compare the bidding time with the social security payment time to see whether social security has been paid one month before the bidding. If so, the value of the "Whether social security has been paid according to the prescribed time" field is yes; if there is no payment record or it was not paid one month ago, it is no.
[0065] Step 5: Data service application.
[0066] In order to systematically and comprehensively display the processed data, the present invention designs three data service applications, including bidding enterprise compliance information query service, bidding enterprise compliance information verification service, and bidding enterprise compliance information comparison service.
[0067] (1) Bidding enterprise compliance information inquiry service
[0068] Use the unified social credit code as the associated field to query the compliance information of bidding companies. Input: unified social credit code, company name, bidder name, bidder citizen ID number. Output: bidding company name, bidding company unified social credit code, whether the bidding company has abnormal operations, whether the bidder is an employee of the company, and whether the social security payment time meets the standards.
[0069] (2) Compliance information verification service for bidding companies
[0070] Input the unified social credit code, company name, bidder name, and bidder citizen ID number, and use the data model to integrate data verification to output the bidding company name, bidding company unified social credit code, whether the company is compliant, and other information.
[0071] (3) Compliance information comparison service for bidding companies
[0072] The comparison results can be generated based on a list of bidding companies and bidders data provided by the customer and the generated bidding company information data.
[0073] Example 2, based on Example 1, proposes a system for the bidding enterprise compliance determination method based on government data fusion according to claim 5, characterized in that it includes:
[0074] Data resource sorting module: used to sort out the corresponding data resources according to the data requirement list and actual conditions, search for resources from the shared platform, identify and analyze them, and select appropriate resources; for resources that meet the requirements, confirm the information items, compile a list of missing or problematic information items, and a list related to unshared data requirements; integrate data resources and information item-related issues to form a project data requirement list, and send it to various business departments for comments; the required data includes the market supervision department's business anomaly list information, the public resource trading center's bidder information, bidding enterprise information, and the human resources and social security department's social security payment information data; for information items that cannot correspond to information items in the requirement list, are missing or ambiguous, compile a list of missing information items or problematic information items; for data requirements that are not shared on the shared platform, compile a list of unshared data requirements.
[0075] Database table design module: used to design core table structures and business table structures. The core table structure includes the core fields of enterprise name, unified social credit code, legal representative information, bidder name, citizen ID number, whether the enterprise is an employee, whether the enterprise has abnormal business operations, whether social security is paid on time, and their source departments and directories; the business table structure covers information on abnormal business operations, bidding enterprise information, bidder information, social security payment information, enterprise basic information query database table name and its core information items;
[0076] Data collection and storage module: used to adopt data warehouse solutions, use ETL tools to extract data from data sources, and load data into the data warehouse according to the pre-defined data warehouse model after data cleaning; for data with high confidentiality requirements, it is collected by connecting to the government external network and using specific system interfaces, and the data collection layer provides data update and data quality verification functions; data storage adopts a combination of relational databases and non-relational databases, and the government's internal structured data is stored in the relational database MySQL; for organizational data of party and government agencies, administrative agencies, and judicial agencies with high confidentiality requirements, it is collected by connecting to the government external network and using specific system interfaces; when storing data, the relational database is mainly used to support the storage of bidding company data, as well as the storage of analysis result data formed by analysis and comparison.
[0077] Data processing and analysis module: used to carry out data fusion processing on compliance-related data of bidding enterprises, including business understanding and data sorting, data conversion, data combination and storage, and data discrimination rules; Business understanding and data sorting: familiarize yourself with and classify the structured data of different commissions and bureaus, sort out the structured data containing enterprise information, and discover the field primary keys that can be used for data fusion; when comparing and verifying with the list of enterprises with abnormal operations, if the bidding enterprise belongs to an enterprise with abnormal operations, the enterprise will be labeled "Is it an enterprise with abnormal operations" and the field value will be "yes"; if If the bidding enterprise is not matched in the list of enterprises with abnormal operations, the value of the "Is it an abnormal operation enterprise" field is "No"; when comparing and verifying with the social security payment information, if the social security payment unit of the bidder is the same as that of the bidding enterprise, the value of the "Is it an enterprise employee" field is "Yes"; if they are inconsistent, it is "No"; if the social security paying enterprise is the bidding enterprise, compare the bidding time with the social security payment time. If social security has been paid one month before the bid, the value of the "Is social security paid according to the prescribed time" field is "Yes"; if there is no payment record or it was not paid one month ago, it is "No".
[0078] Data conversion: Select the primary key of the data fusion field for each data source, mainly using numeric data fields and supplemented by character data, mark the primary keys of the data fields that can be fused, convert the formats of data sets from different data sources, and unify the standard formats of data elements and data dictionaries;
[0079] Data combination and storage: Create a new data fusion table to connect the dimensions of data from different departments, sort out the data set structure of each fusion, create a new table structure containing all fusion data fields in the new data table, and summarize the table content in the new data fusion table according to the data fusion fields;
[0080] Data identification rules: Data comparison and verification is carried out based on the bidding enterprise information and bidder information list provided by the public resource transaction center, the list of enterprises with abnormal business operations of the market supervision department, and the social security payment information of the human resources and social security department. This includes verifying the unified social credit code through the enterprise basic information query interface, comparing with the list of enterprises with abnormal business operations to verify whether it is an enterprise with abnormal business operations, and comparing with the social security payment information to verify whether the bidder is an employee of the enterprise and whether the social security has been paid on time.
[0081] Data service application module: used to systematically and comprehensively display processed data, including bidding enterprise compliance information query service, bidding enterprise compliance information verification service, and bidding enterprise compliance information comparison service; specifically including:
[0082] Bidding Enterprise Compliance Information Query Service: This service uses the unified social credit code as the associated field to query the compliance information of bidding enterprises. Input the unified social credit code, enterprise name, bidder name, and bidder's citizen ID number. Output includes the bidding enterprise name, unified social credit code, whether the bidding enterprise has abnormal operations, whether the bidder is an employee of the enterprise, and whether the social security payment time meets the standards.
[0083] Bidding enterprise compliance information verification service: Input the unified social credit code, enterprise name, bidder name, and bidder citizen ID number, and output the bidding enterprise name, unified social credit code, and compliance information through data model fusion and data verification;
[0084] Compliance information comparison service for bidding enterprises: Compare the data list of bidding enterprises and bidders provided by the customer with the generated bidding enterprise information data to generate comparison results.
[0085] While embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions, and variations may be made to these embodiments without departing from the principles and spirit of the invention, and that the scope of the invention is defined by the appended claims and their equivalents.
Claims
1. A bidding enterprise compliance determination method based on government data fusion, characterized by: The following steps are involved: Data resource sorting: Based on the data requirements list and actual conditions, sort out the corresponding data resources, search for resources on the shared platform, identify and analyze them, and select appropriate resources. For resources that meet the requirements, confirm the information items, compile a list of missing or problematic information items, and a list related to unshared data requirements. Integrate data resources and information item-related issues to form a project data requirements list and send it to each business department for comments. Database table design: Design core table structures and business table structures. The core table structure includes the core fields of enterprise name, unified social credit code, legal representative information, bidder name, citizen ID number, whether the enterprise is an employee, whether the enterprise has abnormal business operations, and whether social security payments are made on time, as well as their source departments and directories. The business table structure covers information on abnormal business operations, bidding enterprise information, bidder information, social security payment information, enterprise basic information query database table names, and their core information items. Data collection and storage: Adopting a data warehouse solution, using ETL tools to extract data from data sources, and after data cleaning, loading it into the data warehouse according to the pre-defined data warehouse model; for data with high confidentiality requirements, it is collected by connecting to the government external network and using specific system interfaces. At the same time, the data collection layer provides data update and data quality verification functions; data storage adopts a combination of relational databases and non-relational databases, and the government's internal structured data is stored in the relational database MySQL.
2. A bidding enterprise compliance determination method based on government data fusion according to claim 1, characterized in that: The data processing and analysis steps specifically include: Business understanding and data sorting: Familiarize yourself with and categorize the structured data of different commissions, offices, and bureaus, sort out structured data containing enterprise information, and discover field primary keys that can be used for data fusion, such as the "unified social credit code"; Data conversion: Select the primary key of the data fusion field for each data source, mainly using numeric data fields and supplemented by character data, mark the primary keys of the data fields that can be fused, convert the formats of data sets from different data sources, and unify the standard formats of data elements and data dictionaries; Data combination and storage: Create a new data fusion table to connect the dimensions of data from different departments, sort out the data set structure of each fusion, create a new table structure containing all fusion data fields in the new data table, and summarize the table content in the new data fusion table according to the data fusion fields; Data identification rules: Data comparison and verification is carried out based on the bidding enterprise information and bidder information list provided by the public resource transaction center, the list of enterprises with abnormal business operations of the market supervision department, and the social security payment information of the human resources and social security department. This includes verifying the unified social credit code through the enterprise basic information query interface, comparing with the list of enterprises with abnormal business operations to verify whether it is an enterprise with abnormal business operations, and comparing with the social security payment information to verify whether the bidder is an employee of the enterprise and whether the social security has been paid on time.
3. The method for determining compliance of bidding enterprises based on government data fusion according to claim 2 is characterized by: In the data identification rules, when comparing and verifying with the list of enterprises with abnormal operations, if the bidding enterprise is an enterprise with abnormal operations, the enterprise will be labeled "Is it an abnormal operation enterprise?" and the field value will be "Yes"; If the bidding enterprise is not matched in the list of enterprises with abnormal business operations, the value of the "Is it an enterprise with abnormal business operations" field will be "No".
4. The method for determining compliance of bidding enterprises based on government data fusion according to claim 3 is characterized by: In the data identification rules, when comparing and verifying with social security payment information, if the social security payment unit of the bidder is the same as that of the bidding enterprise, the value of the "Is Enterprise Employee" field is "Yes"; if they are not consistent, the value is "No"; If the enterprise that pays social insurance is the bidding enterprise, the bidding time and the social insurance payment time will be compared. If the social insurance has been paid one month before the bidding, the value of the "Whether social insurance has been paid on time" field will be "Yes"; if there is no payment record or it has not been paid one month before, the value will be "No".
5. The method for determining compliance of bidding enterprises based on government data fusion according to claim 4 is characterized by: The data service application steps include: Bidding Enterprise Compliance Information Query Service: This service uses the unified social credit code as the associated field to query the compliance information of bidding enterprises. Input the unified social credit code, enterprise name, bidder name, and bidder's citizen ID number. Output includes the bidding enterprise name, unified social credit code, whether the bidding enterprise has abnormal operations, whether the bidder is an employee of the enterprise, and whether the social security payment time meets the standards. Bidding enterprise compliance information verification service: Input the unified social credit code, enterprise name, bidder name, and bidder citizen ID number, and output the bidding enterprise name, unified social credit code, and compliance information through data model fusion and data verification; Compliance information comparison service for bidding enterprises: Compare the data list of bidding enterprises and bidders provided by the customer with the generated bidding enterprise information data to generate comparison results.
6. A system for determining compliance of bidding enterprises based on government data fusion according to claim 5, characterized in that: include: Data resource sorting module: This module is used to sort out the corresponding data resources according to the data requirements list and actual conditions, search for resources from the shared platform, identify and analyze them, and select appropriate resources. For resources that meet the requirements, the module verifies the information items, compiles a list of missing or problematic information items, and a list of unshared data requirements. The module integrates data resources and information item-related issues to form a project data requirements list, which is then sent to various business departments for comments. Database table design module: used to design core table structures and business table structures. The core table structure includes the core fields of enterprise name, unified social credit code, legal representative information, bidder name, citizen ID number, whether the enterprise is an employee, whether the enterprise has abnormal business operations, whether social security is paid on time, and their source departments and directories; the business table structure covers information on abnormal business operations, bidding enterprise information, bidder information, social security payment information, enterprise basic information query database table name and its core information items; Data collection and storage module: This module uses a data warehouse solution to extract data from data sources using ETL tools. After data cleaning, data is loaded into the data warehouse according to a pre-defined data warehouse model. For data with high confidentiality requirements, data is collected by connecting to the government extranet and using specific system interfaces. The data collection layer also provides data update and data quality verification functions. Data storage uses a combination of relational and non-relational databases, and internal government structured data is stored in the relational database MySQL. Data processing and analysis module: used to integrate and process compliance-related data of bidding companies, including business understanding and data sorting, data conversion, data combination and storage, and data identification rules; Data service application module: used to systematically and comprehensively display the processed data, including bidding enterprise compliance information query service, bidding enterprise compliance information verification service, and bidding enterprise compliance information comparison service.
7. A system according to claim 6, characterized in that: The data discrimination rules in the data processing and analysis module specifically include: when comparing and verifying with the list of enterprises with abnormal operations, if the bidding enterprise is an enterprise with abnormal operations, the enterprise will be labeled "Is it an enterprise with abnormal operations" and the field value will be "Yes"; if the bidding enterprise is not matched in the list of enterprises with abnormal operations, the field value of "Is it an enterprise with abnormal operations" will be "No"; when comparing and verifying with social security payment information, if the bidder's social security payment unit is the same as the bidding enterprise, the field value of "Is it an enterprise employee" will be "Yes"; if not, it will be "No"; if the social security paying enterprise is the bidding enterprise, the bidding time and the social security payment time will be compared. If social security has been paid one month before the bid, the field value of "Whether social security has been paid on time" will be "Yes"; if there is no payment record or it was not paid one month ago, it will be "No".
8. A system according to claim 7, characterized in that: In the data resource sorting module, the required data include the abnormal operation list information of the market supervision department, the bidder information of the public resource trading center, the bidding enterprise information, and the social security payment information data of the human resources and social security department; for information items that do not correspond to information items in the demand list, are missing or ambiguous, a list of missing information items or problem information items is compiled; for data requirements that are not shared on the sharing platform, a list of unshared data requirements is compiled.
9. A system according to claim 8, characterized in that: In the data collection and storage module, for data with high confidentiality requirements for organizational data of party and government agencies, administrative institutions, and judicial organs, data is collected by connecting to the government external network and using specific system interface-related methods; when storing data, the relational database is mainly used to support the storage of bidding enterprise data, as well as the storage of analysis result data ultimately formed by analysis and comparison.
10. A system according to claim 9, characterized in that: The data service application module specifically includes: Bidding Enterprise Compliance Information Query Service: This service uses the unified social credit code as the associated field to query the compliance information of bidding enterprises. Input the unified social credit code, enterprise name, bidder name, and bidder's citizen ID number. Output includes the bidding enterprise name, unified social credit code, whether the bidding enterprise has abnormal operations, whether the bidder is an employee of the enterprise, and whether the social security payment time meets the standards. Bidding enterprise compliance information verification service: Input the unified social credit code, enterprise name, bidder name, and bidder citizen ID number, and output the bidding enterprise name, unified social credit code, and compliance information through data model fusion and data verification; Compliance information comparison service for bidding enterprises: Compare the data list of bidding enterprises and bidders provided by the customer with the generated bidding enterprise information data to generate comparison results.