Government affair data automatic processing system based on intelligent agent

Abstract

The invention provides a government affair data automatic processing system based on an intelligent agent, and relates to the technical field of government affair data automatic processing systems. Comprising a data acquisition agent, a data cleaning agent, a data classification agent, a data storage agent, a data analysis agent, a data visualization agent, a task scheduling agent, a safety management agent, a user interaction agent and a central control agent, the data acquisition intelligent agent adopts a multi-source data acquisition technology, so that the data processing efficiency is improved, a series of operations such as automatic acquisition, cleaning, classification, storage, analysis and visualization of the government affair data are realized through cooperative work of the intelligent agents, the data processing period is greatly shortened, and the data processing efficiency is improved. Compared with a traditional manual processing mode, the efficiency is improved by several times or even dozens of times, and data support can be quickly provided for government affair decision making.

Description

Technical Field

[0001] The present invention belongs to the technical field of government data automated processing systems, and more specifically, particularly relates to a government data automated processing system based on agents. Background Art

[0002] In the government affairs field, with the continuous advancement of informatization construction, each department has accumulated a vast amount of government data. However, traditional data processing methods mainly rely on manual operations and have many problems. First, the efficiency of manual data collection is low, and errors and omissions are prone to occur, making it difficult to ensure the integrity and timeliness of data. Second, data cleaning and classification work is cumbersome, requiring a large amount of manpower and time, and due to the lack of unified standards, the data quality is uneven. Third, the data analysis ability is limited, making it difficult to quickly extract valuable information from the vast amount of data and unable to meet the requirements of government decision-making for the depth and breadth of data. In addition, data security management faces challenges, and there is a risk of data leakage during the manual operation process. At the same time, the interaction between users and the data system is not convenient and efficient enough, affecting the overall efficiency of government affairs work. Therefore, there is an urgent need for a system that can automate the processing of government data to improve data processing efficiency, quality, and security, and enhance the level of government services and the scientific nature of decision-making. Summary of the Invention

[0003] To solve the above technical problems, the present invention provides a government data automated processing system based on agents to solve the above problems.

[0004] A government data automated processing system based on agents includes a data collection agent, a data cleaning agent, a data classification agent, a data storage agent, a data analysis agent, a data visualization agent, a task scheduling agent, a security management agent, a user interaction agent, and a central control agent. Each agent collaborates with each other to jointly complete the automated processing process of government data.

[0005] Preferably, the data collection agent adopts multi-source data collection technology and can collect data from different government department databases, e-government platforms, and offline files. Its collection process follows specific data collection rules, and the formula is: , where represents the data source type, represents the access method, represents the data format, and has a data integrity and consistency verification function. The data cleaning agent uses data denoising, duplicate data deletion, and missing value processing algorithms to clean the collected data. Its data denoising algorithm is based on statistical principles and judges and processes by setting a noise threshold. The formula is: , where represents the noisy data, Denotes the noise threshold to ensure that the quality of the cleaned data meets the requirements of subsequent processing. The data classification agent classifies the cleaned data using predefined government data classification standards and machine learning classification algorithms. The classification algorithms use models such as decision trees, neural networks, or support vector machines. The formula is: , where Denotes the cleaned data, Denotes the classification model, which can automatically divide the data into corresponding government service categories.

[0006] Preferably, the data storage agent adopts a distributed storage architecture, stores the data in different storage nodes according to the classification and importance of the data, and uses data encryption and redundant backup technologies during the storage process. Its data encryption uses the Advanced Encryption Standard algorithm, and the redundant backup formula is: , where Denotes the stored data, Denotes the redundancy factor to ensure the security and reliability of the data. The data analysis agent conducts in-depth analysis of the stored data based on big data analysis technologies and artificial intelligence algorithms, and can generate various government data analysis reports, such as trend analysis, correlation analysis, and prediction analysis reports, etc. The algorithms used in the analysis process include time series analysis, association rule mining, and regression analysis, etc. The formula is: , where Denotes the stored data, Denotes the analysis algorithm. The data visualization agent converts the data analysis results into intuitive visual forms such as charts, graphs, or maps, etc., and supports a variety of visualization tools and technologies, such as Echarts, D3.js, etc. The visualization conversion formula is: , where Denotes the analysis report, Denotes the visualization tool, which is convenient for government personnel to intuitively understand the meaning of the data.

[0007] Preferably, the task scheduling agent reasonably allocates system resources and schedules the task execution order of each agent according to the preset task priorities and resource status. Its task scheduling algorithm is based on the priority queue and resource load balancing strategy. The formula is: , where Denotes the task list, Denotes the resource status, Denotes the priority rule to ensure the efficient operation of the system. The security management agent is responsible for the security protection of the entire system, including functions such as user identity authentication, access control, data encrypted transmission, and network security monitoring, etc. The user identity authentication adopts a multi-factor authentication method, and the access control is based on the role-based access control model. The formula is: , where Denotes the user information, Represents role information, Represents permission rules to ensure the security of system data and operations. The user interaction agent provides a friendly user interface to support government staff in interacting with the system, such as functions like data query, task submission, and result feedback. The user interface design follows the principles of human-computer interaction and has good usability and operability. Its interaction response formula is: , where Represents a user request, Represents system functions to ensure that users can efficiently use the system.

[0008] Compared with the prior art, the present invention has the following beneficial effects:

[0009] Improve data processing efficiency: Through the collaborative work of agents, a series of operations such as automated collection, cleaning, classification, storage, analysis, and visualization of government data are realized, greatly shortening the data processing cycle. Compared with traditional manual processing methods, the efficiency is increased by several times or even dozens of times, and it can quickly provide data support for government decision-making.

[0010] Enhance data quality: The integrity and consistency verification function of the data collection agent and the professional algorithms of the data cleaning agent effectively remove noise, duplicate data, and handle missing values, ensuring the accuracy and reliability of the data entering the subsequent processes, providing a high-quality data foundation for government analysis and decision-making, and reducing decision-making mistakes caused by data errors.

[0011] Enhance data analysis capabilities: The data analysis agent uses big data analysis technology and various artificial intelligence algorithms to deeply mine potential information in government data, generate comprehensive and in-depth analysis reports, such as accurate trend predictions and complex correlation analyses, providing more insightful decision-making basis for government staff and helping to formulate scientific and reasonable policies and plans.

[0012] Ensure data security: The multi-faceted security protection measures of the security management agent, from user identity authentication to data encryption transmission and access permission control, comprehensively protect the security and privacy of government data, prevent data leakage and illegal access, ensure the safe and stable development of government work, and maintain the credibility of the government.

[0013] Optimize the user experience: The user interaction agent provides a convenient and easy-to-use interface, enabling government staff to easily interact with the system, quickly obtain the required data and analysis results, reducing the usage threshold and improving work efficiency. At the same time, the task scheduling agent reasonably allocates resources and schedules tasks to ensure the smooth operation of the system, further enhancing user satisfaction. Brief Description of the Drawings

[0014] Figure 1 Is the overall system architecture flowchart of the present invention;

[0015] Figure 2 is the data collection flow chart of the present invention;

[0016] Figure 3 is the data cleaning flow chart of the present invention;

[0017] Figure 4 is the data classification flow chart of the present invention;

[0018] Figure 5 is the data storage flow chart of the present invention;

[0019] Figure 6 is the data analysis flow chart of the present invention;

[0020] Figure 7 is the data visualization flow chart of the present invention;

[0021] Figure 8 is the task scheduling flow chart of the present invention;

[0022] Figure 9 is the security management flow chart of the present invention;

[0023] Figure 10 is the user interaction flow chart of the present invention. Detailed implementation manners

[0024] The following further describes the implementation manners of the present invention in detail with reference to the accompanying drawings and embodiments. The following embodiments are used to illustrate the present invention, but cannot be used to limit the scope of the present invention.

[0025] Please refer to Figures 1-10 , the present invention provides an agent-based automated government data processing system, including a data collection agent, a data cleaning agent, a data classification agent, a data storage agent, a data analysis agent, a data visualization agent, a task scheduling agent, a security management agent, a user interaction agent, and a central control agent. Each agent cooperates with each other to jointly complete the automated processing process of government data.

[0026] Among them, the data collection agent adopts multi-source data collection technology and can collect data from different government department databases, e-government platforms, and offline files. Its collection process follows specific data collection rules, and the formula is: , where represents the data source type, represents the access method, Represents the data format and has functions for data integrity and consistency verification. The data cleaning agent uses data denoising, duplicate data deletion, and missing value processing algorithms to clean the collected data. Its data denoising algorithm is based on statistical principles and makes judgments and processes by setting a noise threshold. The formula is: , where represents the noisy data, represents the noise threshold, ensuring that the quality of the cleaned data meets the requirements of subsequent processing. The data classification agent uses predefined government data classification standards and machine learning classification algorithms to classify the cleaned data. The classification algorithms use models such as decision trees, neural networks, or support vector machines. The formula is: , where represents the cleaned data, represents the classification model, which can automatically divide the data into corresponding government service categories.

[0027] The data storage agent adopts a distributed storage architecture and stores the data in different storage nodes according to the classification and importance of the data. During the storage process, data encryption and redundant backup technologies are used. Its data encryption uses the Advanced Encryption Standard algorithm. The redundant backup formula is: , where represents the stored data, represents the redundancy factor, ensuring the security and reliability of the data. The data analysis agent conducts in-depth analysis on the stored data based on big data analysis technologies and artificial intelligence algorithms, and can generate various government data analysis reports, such as trend analysis, association analysis, and prediction analysis reports, etc. The algorithms used in the analysis process include time series analysis, association rule mining, and regression analysis, etc. The formula is: , where represents the stored data, represents the analysis algorithm. The data visualization agent converts the data analysis results into intuitive visual forms such as charts, graphs, or maps, etc., and supports a variety of visualization tools and technologies, such as Echarts, D3.js, etc. The visualization conversion formula is: , where represents the analysis report, represents the visualization tool, facilitating government personnel to intuitively understand the meaning of the data.

[0028] The task scheduling agent reasonably allocates system resources and schedules the task execution order of each agent according to the preset task priorities and resource status. Its task scheduling algorithm is based on a priority queue and a resource load balancing strategy. The formula is: , where represents the task list, represents the resource status, Represents the priority rules to ensure the efficient operation of the system. The security management agent is responsible for the security protection of the entire system, including functions such as user identity authentication, access control, data encryption transmission, and network security monitoring. User identity authentication adopts a multi-factor authentication method, and access control is based on a role-based access control model, with the formula: , where represents user information, represents role information, represents the permission rules to ensure the security of system data and operations. The user interaction agent provides a friendly user interface to support the interaction between government officials and the system, such as functions like data query, task submission, and result feedback. The user interface design follows the principles of human-computer interaction and has good usability and operability. Its interaction response formula is: , where represents the user request, represents the system function to ensure that users can use the system efficiently.

[0029] Examples:

[0030] Example 1:

[0031] · Hardware configuration:

[0032] · Server: Select a high-performance server equipped with an Intel Xeon E5 processor, 32GB of memory, and a 1TB hard drive to meet the basic requirements for system operation and data storage.

[0033] · Network equipment: Adopt a gigabit Ethernet switch to ensure the stability and speed of data transmission.

[0034] · Software system:

[0035] · Data acquisition agent: Configure connection drivers for common government database types (such as Oracle, MySQL, etc.), collect data from specified database tables at a preset collection frequency (such as once per hour), and check data integrity through data verification algorithms (such as CRC verification) during the collection process.

[0036] · Data cleaning agent: Set the noise threshold to 3 times the standard deviation of the data, use a statistical-based filtering algorithm to remove noise data, and at the same time use a hash algorithm to detect and delete duplicate data.

[0037] · Data classification agent: Based on the general classification standards in the government affairs field, construct a decision tree classification model to classify the cleaned data. For example, divide economic data, people's livelihood data, etc. into corresponding categories.

[0038] · Data Storage Agent: It uses the Hadoop Distributed File System (HDFS) for data storage, stores different categories of data in different HDFS directories, and encrypts the stored data using the AES algorithm. The redundancy backup factor is set to 3 to ensure data security and reliability.

[0039] · Data Analysis Agent: It uses simple statistical analysis methods (such as summation and average calculation) and linear regression analysis algorithms to preliminarily analyze the stored data and generate a basic data analysis report.

[0040] · Data Visualization Agent: It uses the Echarts library to display the key data in the data analysis report in the form of bar charts, line charts, etc. on the Web interface of the system for government affairs personnel to view conveniently.

[0041] · Task Scheduling Agent: It uses a task scheduling algorithm that combines First-Come-First-Served (FCFS) and a simple resource utilization threshold (such as adjusting the task priority when the CPU usage exceeds 80%) to schedule the tasks of each agent.

[0042] · Security Management Agent: It uses a basic identity authentication method of username and password, combined with a Role-Based Access Control (RBAC) model, to assign corresponding operation permissions to government affairs personnel of different roles (such as administrators and ordinary operators). For example, administrators have system configuration permissions, and ordinary operators only have data query and basic analysis permissions.

[0043] · User Interaction Agent: It develops a Web application based on HTML, CSS, and JavaScript as the user interface, provides function modules such as data query forms and analysis report display pages. Users access the system through a browser, and the interaction response time is controlled within 3 seconds.

[0044] Example 2:

[0045] · Hardware Optimization:

[0046] · Upgrade the server to a high-performance cluster server. A cluster is composed of multiple servers, and each server is equipped with an Intel Xeon Gold 6200 series processor, 64GB of memory, and 2TB of hard disk. A load balancing device is used to balance the server load, improving the overall performance and reliability of the system.

[0047] · Upgrade the network device to a 10 Gigabit fiber optic switch to improve the data transmission speed and meet the network requirements for large-scale data processing.

[0048] · Software Upgrade:

[0049] · Data collection agent: Introduce a distributed data collection framework such as Flume, which can efficiently collect data from multiple data sources simultaneously (including government department databases and real-time data interfaces in different regions), and use data fingerprint technology to enhance the data integrity verification ability.

[0050] · Data cleaning agent: Adopt anomaly detection algorithms based on deep learning, such as autoencoder models, to more accurately identify and process abnormal data. At the same time, combine semantic analysis technology to clean and standardize text data.

[0051] · Data classification agent: Use the convolutional neural network (CNN) model of deep learning to classify government affairs data with complex structures (such as images, documents, etc.), improving the classification accuracy and generalization ability.

[0052] · Data storage agent: Adopt the Ceph distributed storage system, combine erasure coding technology to achieve more efficient data redundant storage, reduce storage costs, and use the distributed lock mechanism to ensure the consistency of data storage.

[0053] · Data analysis agent: Introduce a big data analysis platform such as Spark, combine complex machine learning algorithms (such as random forest, gradient boosting tree, etc.) for in-depth data analysis, and generate more detailed and accurate analysis reports, including multi-dimensional trend analysis and factor correlation analysis.

[0054] · Data visualization agent: Integrate advanced visualization libraries such as D3.js and Three.js to achieve 3D visualization and interactive visualization effects of data, such as creating interactive 3D data maps and dynamic information charts, enhancing the intuitiveness and attractiveness of data display.

[0055] · Task scheduling agent: Based on the task scheduling algorithm of reinforcement learning, the agent continuously learns and optimizes the task scheduling strategy, dynamically adjusts the task execution order and resource allocation according to factors such as system real-time load, task priority, and resource cost, improving the system resource utilization rate and task processing efficiency.

[0056] · Security management agent: Adopt a multi-factor identity authentication method that combines biometric technologies (such as fingerprint recognition, face recognition) with digital certificates to enhance the security of user identity authentication; use blockchain technology to record data access and operation logs, ensuring the immutability and traceability of data operations, and further improving the data security protection ability.

[0057] · User interaction agent: Develop a mobile application program to support government affairs personnel to access the system anytime and anywhere through mobile devices such as mobile phones and tablets. Adopt responsive design and push notification technology to optimize the user interaction experience, such as real-time pushing of data analysis results and system notifications, and the interaction response time is shortened to within 1 second.

[0058] Example 3:

[0059] · Hardware innovation:

[0060] · Adopt edge computing devices, such as high-performance industrial PCs, as data collection and preprocessing nodes, and deploy them at the data source ends of each government department to achieve near-source data collection and preliminary processing, reducing data transmission latency and the load on the central server. These edge devices are equipped with Intel Core i7 processors, 16GB of memory, 500GB solid-state drives, and communicate with the central server through 5G networks.

[0061] · The central server adopts a cloud computing architecture, leases elastic computing resources from a cloud service provider, and dynamically adjusts the server configuration according to actual business needs. For example, it automatically expands CPU and memory resources during peak data processing periods, reducing hardware procurement and maintenance costs.

[0062] · Software expansion:

[0063] · Data collection agent: Integrate with Internet of Things devices (such as smart sensors) to achieve real-time collection of government-related environmental data, device operation data, etc. At the same time, use edge computing technology to perform real-time analysis and filtering of the collected data locally, and only transmit valuable data to the central server, reducing network transmission pressure.

[0064] · Data cleaning agent: Adopt federated learning technology to collaborate with other government departments for data cleaning and data quality improvement without transmitting raw data, protecting data privacy while improving the data cleaning effect.

[0065] · Data classification agent: Combine natural language processing technology and knowledge graph technology to perform semantic understanding and classification on unstructured government text data (such as policy documents, meeting minutes, etc.), and automatically construct a government knowledge graph to improve the intelligence level of data classification and knowledge association ability.

[0066] · Data storage agent: Utilize the object storage service of cloud storage, such as AWS S3 or Alibaba Cloud OSS, and combine the data life cycle management strategy to automatically migrate and archive data according to the access frequency and importance of the data, reducing storage costs and improving data management efficiency.

[0067] · Data analysis agent: Use the recurrent neural network (RNN) of deep learning and its variants (such as LSTM, GRU) to perform predictive analysis on government data with time series characteristics (such as the change of economic development indicators over time). At the same time, combine transfer learning technology to use similar data models in other regions or fields to accelerate local model training, improving the analysis accuracy and efficiency.

[0068] · Data Visualization Agent: By adopting Mixed Reality (MR) technology, it combines the data visualization results with the real environment. For example, in a government affairs meeting room, it displays three-dimensional data models and analysis results through MR devices, providing immersive data interaction experiences for government affairs personnel and enhancing the intuitiveness and effectiveness of decision-making discussions.

[0069] · Task Scheduling Agent: It introduces container orchestration technology such as Kubernetes to deploy and run each agent in a containerized manner. Through the dynamic scheduling and resource allocation of containers, it improves the elasticity and scalability of the system. At the same time, it uses the microservices architecture to split each agent into independent microservices, facilitating development, maintenance, and upgrade.

[0070] · Security Management Agent: By adopting homomorphic encryption technology, it directly performs certain specific data analysis operations in the data encrypted state, ensuring data privacy and the accuracy of analysis results. It uses an artificial intelligence-driven security monitoring system to real-time monitor the security threats and abnormal behaviors of the system, such as intrusion detection and data leakage warning, improving the proactive security defense ability of the system.

[0071] · User Interaction Agent: It develops intelligent voice interaction functions. Government affairs personnel can interact with the system through voice commands, such as querying data and starting analysis tasks. The system uses speech recognition and natural language processing technologies to understand user intentions and provide corresponding feedback, further improving the convenience and efficiency of user operations.

[0072] Example 4:

[0073] · Hardware Configuration Adjustment:

[0074] · The server uses a minicomputer server, which has high reliability and stability, and is equipped with an IBM Power9 processor, 128GB of memory, and a 4TB hard disk. It is suitable for government affairs application scenarios with extremely high requirements for data processing reliability, such as financial data processing and social security data management.

[0075] · The storage device uses an enterprise-level storage array, such as the EMC VNX series, which provides high-speed data reading and writing capabilities and a large-capacity data storage space. At the same time, it has data snapshot and cloning functions, facilitating data backup and recovery.

[0076] · Software System Customization:

[0077] · Data Acquisition Agent: It develops a dedicated data acquisition interface for specific government affairs business systems (such as the tax collection and management system), and triggers data acquisition by combining timed tasks and event-driven methods to ensure the timely acquisition of key business data. At the same time, it uses a data encryption transmission protocol (such as SSL / TLS) to ensure data transmission security.

[0078] · Data cleaning agent: According to the characteristics of tax data, formulate specialized data cleaning rules and algorithms, such as performing format verification and authenticity verification on invoice data, and performing logical checks and outlier processing on tax declaration data to ensure the accuracy and compliance of the data.

[0079] · Data classification agent: Based on the tax business classification system and industry standards, build a rule-based classification engine, and combine a machine learning classification model to classify tax data. For example, classify and store data of different tax types such as value-added tax and income tax.

[0080] · Data storage agent: Use the cluster technology of relational databases (such as Oracle RAC) to store tax data, achieve highly available and high-performance data storage, and at the same time optimize data query and retrieval performance through database partitioning and indexing technologies.

[0081] · Data analysis agent: Develop special algorithms and models for tax data analysis, such as tax revenue prediction models, tax risk assessment models, etc. Use data mining technology to discover potential tax collection and management problems and risk points, and provide strong support for tax decision-making.

[0082] · Data visualization agent: According to tax business requirements, customize and develop visualization reports and dashboards, such as tax revenue trend charts, taxpayer distribution maps, etc. Adopt professional visualization design principles and color schemes to make data display clearer, more accurate and more beautiful.

[0083] · Task scheduling agent: Adopt a task scheduling strategy based on priority and resource reservation, allocate high priority and sufficient system resources to key tax business tasks (such as tax calculation and declaration processing), ensure that tasks are completed on time, and at the same time use task monitoring and warning mechanisms to timely discover and handle problems during task execution.

[0084] · Security management agent: Follow strict tax information security specifications, use hardware security modules (HSM) for data encryption and key management, and implement strict user identity authentication and authorization mechanisms, such as using two-factor authentication and multi-level authorization approval processes, to ensure the security and confidentiality of tax data.

[0085] · User interaction agent: Develop specifically.

[0086] The embodiments of the present invention are given for purposes of illustration and description, and are not exhaustive or limit the present invention to the disclosed form. Many modifications and variations are obvious to those of ordinary skill in the art. The embodiments are chosen and described in order to better illustrate the principles of the present invention and its practical applications, and to enable those of ordinary skill in the art to understand the present invention and design various embodiments with various modifications suitable for specific purposes.

Claims

1. An agent-based automated government data processing system, characterized in that It includes a data collection agent, a data cleaning agent, a data classification agent, a data storage agent, a data analysis agent, a data visualization agent, a task scheduling agent, a security management agent, a user interaction agent, and a central control agent. These agents cooperate with each other to jointly complete the automated processing process of government affairs data. The data classification agent classifies the cleaned data using predefined government affairs data classification criteria and machine learning classification algorithms. The classification algorithms use models such as decision trees, neural networks, or support vector machines. The formula is: , where represents the cleaned data, represents the classification model, which can automatically divide the data into corresponding government affairs business categories. The task scheduling agent reasonably allocates system resources and schedules the task execution order of each agent according to the preset task priorities and resource status. Its task scheduling algorithm is based on a priority queue and a resource load balancing strategy. The formula is: , where represents the task list, represents the resource status, represents the priority rule to ensure the efficient operation of the system. The security management agent is responsible for the security protection of the entire system, including functions such as user identity authentication, access control, encrypted data transmission, and network security monitoring. User identity authentication uses a multi-factor authentication method, and access control is based on a role-based access control model. The formula is: , where represents the user information, represents the role information, represents the permission rule to ensure the security of system data and operations.

2. The agent-based automated government data processing system according to claim 1, wherein The government affairs data automated processing system according to claim 1, wherein the data collection agent adopts multi-source data collection technology and can collect data from databases of different government departments, e-government platforms, and offline documents. Its collection process follows specific data collection rules, and the formula is: , where represents the data source type, represents the access method, represents the data format, and has the functions of data integrity and consistency verification.

3. The government affairs data automatic processing system according to claim 1, wherein the data cleaning agent uses data denoising, duplicate data deletion, and missing value processing algorithms to clean the collected data. The data denoising algorithm is based on statistical principles and makes judgments and processes by setting a noise threshold. The formula is: , where represents the noisy data, represents the noise threshold, ensuring that the quality of the cleaned data meets the requirements of subsequent processing.

4. The government affairs data automated processing system according to claim 1, wherein the data storage intelligent agent adopts a distributed storage architecture, stores data in different storage nodes according to the classification and importance of the data, and applies data encryption and redundant backup technologies during the storage process. The data encryption adopts the Advanced Encryption Standard algorithm, and the redundant backup formula is: , where represents the stored data, represents the redundancy factor, ensuring the security and reliability of the data.

5. The government affairs data automated processing system according to claim 1, wherein the data analysis intelligent agent conducts in-depth analysis on the stored data based on big data analysis technology and artificial intelligence algorithms, and can generate various government affairs data analysis reports, such as trend analysis, correlation analysis, and prediction analysis reports, etc. The algorithms adopted in the analysis process include time series analysis, association rule mining, and regression analysis, etc., and the formula is: , where represents the stored data, represents the analysis algorithm.

6. For the government affairs data automated processing system according to claim 1, the data visualization agent converts the data analysis results into intuitive visual forms such as charts, graphs, or maps, supports a variety of visualization tools and technologies, such as Echarts, D3.js, etc., and the visualization conversion formula is: , where represents the analysis report, represents the visualization tool, which is convenient for government affairs personnel to intuitively understand the meaning of the data.

7. The government affairs data automated processing system according to claim 1, wherein the user interaction agent provides a friendly user interface to support the interaction operations between government affairs personnel and the system, such as functions of data query, task submission, and result feedback. The user interface design follows the principles of human-computer interaction, with good usability and operability. Its interaction response formula is: , where represents a user request, represents a system function, ensuring that users can use the system efficiently.

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