Automatic arrangement method and system for enterprise qualification authentication process
Through data collection, process analysis and automated orchestration, combined with web crawlers and natural language processing technology, the problems of high manpower consumption and low efficiency in the traditional enterprise qualification certification process have been solved, and efficient and accurate qualification certification process management has been achieved.
Patent Information
- Application Number
- CN202510853423.6
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-06-24
- Publication Date
- 2025-10-14
- Estimated Expiration
- Not applicable · inactive patent
AI Technical Summary
The traditional enterprise qualification certification process requires a lot of manpower and time, is prone to errors in data collection, has low process decomposition efficiency, and lacks scientific task allocation, which leads to extended certification cycles and difficulty in real-time progress tracking and exception handling.
It adopts the methods of data collection, process analysis, automated orchestration and execution monitoring, utilizes web crawlers and natural language processing technology, automatically generates execution order through the rule engine, and monitors and adjusts the process in real time.
It improves the efficiency and accuracy of qualification certification, reduces manual operation errors, shortens the certification cycle, and enhances the ability to respond to anomalies.
Smart Images
Figure CN120782231A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to the field of information technology, and in particular to a method and system for automatically arranging an enterprise qualification certification process. Background Art
[0002] In the modern business environment, enterprise qualification certification is of vital importance to the development of enterprises. Qualification certification is not only an important reflection of the strength and compliance of enterprises, but also a key entry condition for enterprises to enter specific markets, participate in project bidding and obtain government support. With the increasingly fierce market competition, enterprises are facing an urgent need to obtain more qualification certifications to enhance their competitiveness. The traditional enterprise qualification certification process is full of drawbacks. When collecting data, a lot of manpower and time are required to collect basic information, business data and related documents from complex sources and in different formats. Standardization processing is cumbersome and prone to errors or omissions. The qualification certification process is complicated. Manual decomposition of sub-processes, analysis of pre- and post-conditions, and construction of relationship maps are inefficient and prone to errors. It is difficult to sort out the process logic. In terms of task allocation and execution sequence determination, manual operations lack scientific and systematic planning, and cannot quickly generate the optimal solution based on certification requirements and actual conditions, resulting in a longer certification cycle. During the certification execution period, it is difficult for humans to track the progress in real time and comprehensively. In the face of anomalies, they cannot adjust or rearrange the process in time according to the strategy, which seriously restricts the certification efficiency and success rate. Summary of the Invention
[0003] In response to the above-mentioned shortcomings of the existing technology, the present invention provides a method and system for automated orchestration of enterprise qualification certification processes, which can effectively solve the problems in the existing technology that the data collection stage requires a lot of manpower and time and is prone to errors and omissions due to the wide range of data sources and diverse formats; the process disassembly link is inefficient and prone to errors in manually analyzing sub-process related conditions and constructing relationship maps; the task allocation and execution sequence determination lack scientificity, resulting in an extension of the certification cycle; and it is difficult for humans to track progress and handle exceptions in a timely and comprehensive manner during the execution process.
[0004] To achieve the above objectives, the present invention is implemented through the following technical solutions: The present invention provides a method for automating the process of enterprise qualification certification, comprising the following steps: Data collection steps: Collect the company's basic information, business data and various documents and materials related to qualification certification, and standardize the data; Process analysis steps: break down the qualification certification process into multiple sub-processes, analyze the preconditions, execution steps, and post-conditions of each sub-process, and construct a sub-process relationship map; Automated orchestration step: Based on the sub-process relationship graph and a preset rule engine, automatically generate an execution sequence that meets the qualification certification requirements and assign tasks to corresponding processing modules; Execution monitoring steps: real-time tracking of task execution progress, collection of feedback information during the execution process, and when exceptions occur, adjustments or rescheduling of processes based on preset exception handling strategies. Preferably, in the data collection step, industry dynamics, policy and regulatory information related to the enterprise is obtained from public channels through web crawler technology to assist in the judgment of the qualification certification process. Preferably, in the process analysis step, natural language processing technology is used to analyze the qualification certification standard document to automatically identify key process nodes and condition restrictions. Preferably, the rule engine includes multiple rule types, including at least time-based rules, data threshold-based rules, and logical judgment-based rules, so as to flexibly adapt to the orchestration requirements of different qualification certification processes. An automated orchestration system for enterprise qualification certification processes, characterized by including the following modules: Data collection module: used to collect basic information of enterprises, business data and various documents and materials related to qualification certification, and perform standardized processing; Process analysis module: breaks down the qualification certification process into multiple sub-processes, analyzes the preconditions, execution steps, and post-conditions of the sub-processes, and constructs a sub-process relationship map; Automatic orchestration module: Based on the sub-process relationship map and the preset rule engine, it automatically generates the execution order of qualification certification and assigns tasks to the corresponding processing modules; Execution monitoring module: tracks task execution progress in real time, collects feedback information, and adjusts or re-arranges processes based on preset exception handling strategies when exceptions occur. Preferably, the data collection module is also integrated with a web crawler component for acquiring industry dynamics, policy and regulatory information related to the enterprise from public channels. Preferably, the process analysis module includes a natural language processing unit for analyzing qualification certification standard documents and automatically identifying key process nodes and condition restrictions. Preferably, the rule engine module has multiple rule types, including at least time-based rules, data threshold-based rules, and logical judgment-based rules, so as to achieve flexible process orchestration.
[0005] Compared with the prior art, the technical solution provided by the present invention has the following beneficial effects: The enterprise qualification certification process automatic arrangement method and system of the present application realizes the automation of the enterprise qualification certification process through data acquisition, process analysis, automatic arrangement and execution monitoring steps and modules. The network crawler technology and natural language processing technology are used to improve the comprehensiveness of the data and the accuracy of the process analysis. The rule engine of the present application can flexibly adapt to different qualification certification processes, greatly improving the certification efficiency and accuracy, and reducing the errors and costs of manual operation. BRIEF DESCRIPTION OF DRAWINGS
[0006] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, the drawings needed to be used in the embodiments or prior art description will be briefly introduced. Obviously, the drawings in the following description are only some embodiments of the present application, and other drawings can be obtained by those skilled in the art without creative labor.
[0007] Fig. 1 The operation flowchart of the present application; Fig. 2 The module flowchart of the present application. DETAILED DESCRIPTION
[0008] In order to make the purpose, technical solutions and advantages of the embodiments of the present application more clear, the technical solutions in the embodiments of the present application will be described clearly and completely with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are part of the embodiments of the present application, not all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor are within the scope of protection of the present application.
[0009] The present application will be further described below in conjunction with the embodiments.
[0010] Embodiment: Refer to Figs. 1-2 A kind of enterprise qualification certification process automatic arrangement method, comprising the following steps: Data collection step: Collect the basic information of the enterprise, business data and various types of file materials related to qualification certification, and standardize the data. In the process of enterprise operation, the basic information covers the registration information of the enterprise, such as enterprise name, legal representative, registered address, registered capital, etc.; business data includes the business scope, business performance, customer information and other aspects of the enterprise, and the file materials related to qualification certification may include the business license, tax registration certificate, relevant industry employment permit, etc. In order to ensure the consistency and availability of the data, after collecting these data, it is necessary to standardize the data. For example, the date format is unified to "YYYY-MM-DD", and the numerical data is unified in unit and precision. Through this standardization, accurate and standardized data basis can be provided for subsequent process analysis and automatic arrangement.
[0011] Process analysis step: The qualification certification process is divided into multiple sub-processes, the preconditions, execution steps and postconditions of each sub-process are analyzed, and a sub-process relationship graph is constructed. Different qualification certifications often contain complex processes, and dividing them into sub-processes helps to manage and analyze them more carefully. For example, for a qualification certification in the construction industry, it may include the enterprise basic condition audit sub-process, personnel qualification review sub-process, performance evaluation sub-process, etc. In the analysis of each sub-process, the precondition refers to the condition that must be met before the sub-process begins to execute, such as in the personnel qualification review sub-process, the precondition may be that the enterprise has submitted all relevant qualification certificates of employees; the execution step is the specific operation process of the sub-process, such as checking the qualification certificates of employees one by one; the postcondition refers to the state or result reached after the execution of the sub-process, such as the postcondition of the personnel qualification review sub-process may be to determine that all employee qualifications meet the requirements. Through the analysis of these conditions and steps, a sub-process relationship graph is constructed, which intuitively shows the sequence and dependency relationship between each sub-process.
[0012] Automatic arrangement step: According to the sub-process relationship graph, based on the pre-set rule engine, the execution order that meets the qualification certification requirements is automatically generated, and the tasks are assigned to the corresponding processing modules. The sub-process relationship graph provides a clear framework for automatic arrangement, and the pre-set rule engine is the key to flexible arrangement. The rule engine will automatically calculate the best execution order according to the logical relationship between sub-processes and various rules. For example, if the postcondition of a sub-process is the precondition of another sub-process, the rule engine will ensure that the two sub-processes are executed in the correct order. At the same time, tasks are assigned to corresponding processing modules, such as data processing modules responsible for analyzing and processing data, audit modules responsible for auditing relevant information, etc. This can improve the execution efficiency and accuracy of the entire qualification certification process.
[0013] The monitoring step is performed to track the progress of task execution in real time, collect feedback information during execution, and adjust or rearrange the process according to the preset exception handling strategy when an exception occurs. During the execution of the qualification certification process, the execution of each sub-process can be monitored in real time to understand the execution of each sub-process. For example, a progress bar or status indicator light can be set to visually display the completion of the task. Collect feedback information during execution, such as problems encountered by a processing module when processing tasks or data anomalies found, etc. When an exception occurs, the preset exception handling strategy will play a role. For example, if a sub-process takes too long to execute, it may be because the data volume is too large or the processing logic is complex, at which time the exception handling strategy can be to adjust the task allocation, assign part of the task to other processing modules, or optimize the processing logic to rearrange the process to ensure that the entire qualification certification process can proceed smoothly.
[0014] In the data collection step, the network crawler technology is used to obtain industry trends and policy and regulation information related to the enterprise in the public channel to assist in the judgment of the qualification certification process. Network crawler technology can automatically capture information related to the enterprise from various public channels, such as government official websites, industry association websites, news media websites, etc., according to pre-set rules. For example, for an enterprise engaged in the environmental protection industry, the network crawler can capture the latest environmental protection policies and regulations to understand the possible new requirements or changes in qualification certification, and through analysis of this information, it can more accurately determine whether the enterprise meets the conditions for qualification certification and what aspects need to be paid attention to in the certification process, thereby improving the success rate of qualification certification.
[0015] In the process analysis step, natural language processing technology is used to analyze the qualification certification standard documents to automatically identify key process nodes and condition restrictions. Qualification certification standard documents are usually written in natural language and contain a lot of information. Natural language processing technology can perform in-depth analysis of these documents. For example, through lexical analysis, syntactic analysis, and semantic analysis techniques, key words, key phrases, and key sentences in the document can be identified. In the qualification certification standard document, the key process nodes may be "submit application", "on-site audit", etc.; the condition restrictions may be "the enterprise must have been established for more than 3 years", "the turnover in the past year must be more than 5 million yuan", etc. After automatically identifying these key information, the qualification certification process can be more accurately decomposed into sub-processes, and the prerequisites, execution steps, and postconditions of each sub-process are clearly defined, providing a reliable basis for subsequent process arrangement.
[0016] The rule engine includes multiple rule types, including at least time-based rules, data threshold-based rules, and logic-based rules, to flexibly adapt to the arrangement needs of different qualification certification processes.
[0017] Time-based rules can ensure that the process is executed in the prescribed time sequence. For example, in some certification, it is stipulated that the preliminary audit must be completed within 15 working days after the enterprise submits the application, then the rule engine can automatically arrange the relevant tasks and sub-processes according to this time requirement.
[0018] Data threshold-based rules are based on the numerical value or range of data to determine the direction of the process. For example, when a certain business indicator of an enterprise reaches a certain threshold, it can enter the next sub-process. For example, when the number of employees of an enterprise reaches 100 or more, it can apply for higher-level certification.
[0019] Logic-based rules are based on the logical relationship between various conditions to arrange the process. For example, only when the enterprise meets both the conditions of "having relevant professional and technical personnel" and "having certain fixed assets" can it enter the subsequent audit process. Through the combination of these various rule types, the rule engine can flexibly adapt to the complex requirements of different certification processes.
[0020] Data collection module: used to collect the basic information of enterprises, business data and various types of file materials related to certification, and to standardize the processing. This module can realize automatic data collection by interfacing with various systems within the enterprise, such as interfacing with the enterprise's financial management system to obtain the enterprise's financial data, and interfacing with the human resource management system to obtain the relevant information of employees. At the same time, for some data that need to be manually input, the module also provides a friendly user interface to facilitate users to enter data. In terms of standardization processing, the module has built-in data cleaning and conversion algorithms, which can automatically process the collected data to ensure the quality and consistency of the data.
[0021] Process analysis module: decomposes the certification process into multiple sub-processes, analyzes the preconditions, execution steps and postconditions of the sub-processes, and constructs a sub-process relationship graph. The module uses advanced process analysis algorithms combined with natural language processing technology to accurately decompose complex certification processes. When analyzing the conditions and steps of the sub-processes, the module will establish a detailed database to store this information for subsequent query and management. When constructing the sub-process relationship graph, the module can use visualization tools to display the graph in an intuitive graphical manner, allowing users to clearly understand the relationship between each sub-process.
[0022] The automation arrangement module automatically generates the execution sequence of the qualification certification according to the sub-process relationship graph and the preset rule engine, and assigns tasks to the corresponding processing modules. This module closely cooperates with the rule engine, and intelligently calculates and decides according to the information in the sub-process relationship graph and the rules of the rule engine. When generating the execution sequence, the module will consider various factors, such as the priority of the task, the load of the processing module, etc., to ensure the rationality of the execution sequence. In terms of task allocation, the module will accurately allocate tasks to the most suitable module according to the functions and capabilities of the processing module, improving the running efficiency of the entire system.
[0023] The execution monitoring module tracks the task execution progress in real time, collects feedback information, and adjusts or rearranges the process according to the preset exception handling strategy when an exception occurs. The module communicates with each processing module in real time to obtain the execution status and progress information of the task. At the same time, the module will also collect various feedback information generated by the processing module during the execution process, such as error logs, warning information, etc. When an exception is detected, the module will quickly respond according to the preset exception handling strategy. For example, if a processing module fails, the module will automatically reassign the task to other available modules and adjust the execution sequence of the process to ensure that the entire qualification certification process is not affected.
[0024] The data collection module also integrates a web crawler component for obtaining industry trends and policy and regulation information related to the enterprise from public channels. The web crawler component has high flexibility and customizability. Users can set the crawling range and frequency of the crawler according to their own needs. For example, for some enterprises that are sensitive to industry trends, the crawler can be set to crawl the latest information from multiple related websites every day. At the same time, the crawler component also has data screening and filtering functions, which can filter out useful information related to the enterprise from a large amount of crawling data, avoiding interference from irrelevant information. The collected information will be integrated into the data collection module in a timely manner and processed and analyzed together with other data of the enterprise.
[0025] The process analysis module includes a natural language processing unit for analyzing the qualification certification standard documents and automatically identifying key process nodes and condition restrictions. The natural language processing unit uses advanced deep learning models such as the Transformer model, which can efficiently and accurately analyze the qualification certification standard documents. When processing the documents, the unit will preprocess the documents, such as removing noise, word segmentation, etc., and then use the model for semantic understanding and information extraction. For the identification of key process nodes and condition restrictions, the unit will make judgments based on the trained model and related knowledge base. For example, for the sentence "the enterprise needs to submit complete application materials within the specified time", the unit can accurately identify that "submit complete application materials" is a key process node and "within the specified time" is a condition restriction. Through such accurate analysis, it can provide strong support for process analysis.
[0026] The rule engine module has multiple rule types, including at least time-based rules, data threshold-based rules, and logic-based rules, to achieve flexible process orchestration. The rule engine module provides a user-friendly rule configuration interface, allowing users to easily add, modify, and delete rules according to specific qualification certification requirements. For example, users can add new data threshold-based rules to specify that a certain technical indicator of an enterprise must meet a certain value to pass the qualification certification. During rule execution, the module monitors the state and data changes of the process in real time and makes corresponding decisions and adjustments based on the rules. At the same time, the rule engine module also has the function of rule conflict detection and resolution. When conflicts arise between different rules, the module can automatically analyze the conflict reasons and take appropriate strategies to solve them, ensuring the accuracy and reliability of process orchestration.
[0027] The above embodiments are only used to illustrate the technical solutions of the present application, and not to limit them; although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that they can still modify the technical solutions recorded in the foregoing embodiments, or make equivalent replacements for part of the technical features; and these modifications or replacements will not cause the essence of the corresponding technical solutions to deviate from the protection scope of the technical solutions of the embodiments of the present application.
Claims
1. A method for automating the process of enterprise qualification certification, characterized in that: The following steps are involved: Data collection steps: Collect the company's basic information, business data and various documents and materials related to qualification certification, and standardize the data; Process analysis steps: break down the qualification certification process into multiple sub-processes, analyze the preconditions, execution steps, and post-conditions of each sub-process, and construct a sub-process relationship map; Automated orchestration step: Based on the sub-process relationship graph and a preset rule engine, automatically generate an execution sequence that meets the qualification certification requirements and assign tasks to corresponding processing modules; Execution monitoring steps: real-time tracking of task execution progress, collection of feedback information during the execution process, and when exceptions occur, adjustments or rescheduling of processes based on preset exception handling strategies.
2. The method for automating the process of enterprise qualification certification according to claim 1, characterized in that: In the data collection step, web crawler technology is used to obtain industry dynamics, policy and regulatory information related to the enterprise from public channels to assist in the judgment of the qualification certification process.
3. The method for automating the process of enterprise qualification certification according to claim 1, characterized in that: In the process analysis step, natural language processing technology is used to analyze the qualification certification standard document to automatically identify key process nodes and condition restrictions.
4. The method for automating the process of enterprise qualification certification according to claim 1, characterized in that: The rule engine includes multiple rule types, including at least time-based rules, data threshold-based rules, and logical judgment-based rules, so as to flexibly adapt to the orchestration requirements of different qualification certification processes.
5. A method for automating the process of enterprise qualification certification, using a system for automating the process of enterprise qualification certification as described in claims 1-4, characterized in that: Includes the following modules: Data collection module: used to collect basic information of enterprises, business data and various documents and materials related to qualification certification, and perform standardized processing; Process analysis module: breaks down the qualification certification process into multiple sub-processes, analyzes the preconditions, execution steps, and post-conditions of the sub-processes, and constructs a sub-process relationship map; Automatic orchestration module: Based on the sub-process relationship map and the preset rule engine, it automatically generates the execution order of qualification certification and assigns tasks to the corresponding processing modules; Execution monitoring module: tracks task execution progress in real time, collects feedback information, and adjusts or re-arranges processes based on preset exception handling strategies when exceptions occur.
6. The automated orchestration system for enterprise qualification certification process according to claim 5, characterized in that: The data collection module is also integrated with a web crawler component for obtaining industry dynamics, policy and regulatory information related to the enterprise from public channels.
7. The automated orchestration system for enterprise qualification certification process according to claim 5, characterized in that: The process analysis module includes a natural language processing unit for analyzing qualification certification standard documents and automatically identifying key process nodes and condition restrictions.
8. The automated orchestration system for enterprise qualification certification process according to claim 5, characterized in that: The rule engine module has multiple rule types, including at least time-based rules, data threshold-based rules, and logical judgment-based rules, to achieve flexible process orchestration.