Abnormal state processing method and device of service system, equipment and storage medium

Abstract

The invention relates to an abnormal state processing method of a service system, and aims to solve the problem of how to improve the efficiency and accuracy of processing an abnormal state by the system. Whether the communication interface is in an abnormal state or not is detected by monitoring the request of the communication interface; when the abnormal state is detected, a prompt window is generated, a user selects a specific processing mode through the prompt window, and the specific processing mode comprises automatic processing of the system and processing of the user according to a solution displayed by the prompt window; and when the specific processing mode is system automatic processing, identifying a current operation step of the user, determining a target preset operation script according to the current operation step, and processing the abnormal state through the target preset operation script. According to the invention, real-time monitoring and efficient processing of the abnormal state of the system can be realized, and the reliability of the system and the user experience are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of computer systems, and in particular to a method, device, equipment and storage medium for processing abnormal status of a service system. Background Art

[0002] With the rapid development of computer technology and the Internet, service systems have been widely used in various industries, such as e-commerce systems, financial service systems, medical information systems, etc. In the operation of these service systems, various abnormal conditions are often encountered, such as communication interface abnormalities, operation step failures, data processing errors, etc. If these abnormal conditions cannot be handled in a timely and effective manner, they will not only affect the normal operation of the system, but may also cause data loss, service interruption, and even cause more serious system failures, causing inconvenience and losses to users.

[0003] Existing service systems usually rely on manual intervention when handling abnormal conditions. Staff need to manually monitor system logs and manually handle abnormalities when they are found. This approach is not only inefficient but also prone to errors. Especially when faced with complex and changing abnormal situations, the response speed and accuracy of manual processing are difficult to guarantee. In addition, some existing automated processing methods also have certain limitations. They are often only targeted at specific types of abnormal conditions and lack flexibility and adaptability.

[0004] With the development of artificial intelligence and big data technology, more and more research has begun to explore the use of intelligent technology to automatically detect and handle abnormal conditions. For example, machine learning algorithms are used to analyze historical data to automatically identify and predict abnormal situations; image recognition technology is used to analyze operation pages to automatically determine whether the user's operation steps are correct. However, these technologies still have some problems in practical applications, such as high algorithm complexity, strong data dependence, and low processing efficiency, which still need further optimization and improvement.

[0005] Therefore, there is an urgent need for an efficient, accurate and intelligent service system abnormal state processing method that can monitor the system operation status in real time, automatically detect and handle abnormal situations, improve system reliability and user experience, reduce manual intervention, and realize intelligent management and optimization of the system. Summary of the invention

[0006] The main purpose of the present invention is to provide a method, device, equipment and storage medium for handling abnormal status of a service system, aiming to solve the technical problem of how to improve the efficiency and accuracy of the system in handling abnormal status.

[0007] To achieve the above object, the present invention provides a method for handling an abnormal state of a service system, the method comprising the following steps:

[0008] Monitoring the communication interface request and detecting whether the communication interface is in an abnormal state;

[0009] When an abnormal state is detected, a prompt window is generated for the user to select a specific processing method through the prompt window, and the specific processing method includes automatic processing by the system and processing by the user according to the solution displayed in the prompt window;

[0010] When the specific processing method is automatic processing by the system, the user's current operation steps are identified, a target preset operation script is determined according to the current operation steps, and the abnormal state is processed by the target preset operation script.

[0011] Optionally, the step of identifying the user's current operation step includes:

[0012] Using an image recognition algorithm to segment the operation page where the current operation step is located, and extracting features from the segmented operation page to obtain a feature map;

[0013] A candidate frame is obtained by using the feature map and the region candidate network, an operation candidate frame is screened out from the candidate frame, and a current operation step of the user is determined according to the operation candidate frame.

[0014] Optionally, before the step of determining a target preset operation script according to the current operation step, the method further includes:

[0015] A preset operation script library is constructed, in which preset operation scripts corresponding to the operation steps are stored, and the preset operation scripts are used to automatically execute preset operation tasks.

[0016] Optionally, the step of building a preset operation script library includes:

[0017] Acquire historical operation data, perform cluster analysis on the historical operation data using a clustering algorithm, generate operation step clusters, generate one or more preset operation scripts for each operation step cluster, and construct the preset operation script library through the preset operation scripts of all operation step clusters.

[0018] Optionally, the step of determining a target preset script according to the current operation step includes:

[0019] The corresponding target preset operation script is determined from the preset operation script library according to the current operation step.

[0020] Optionally, after the step of building a preset operation script library, the method further includes:

[0021] Acquire historical processing information of historical abnormal states, and identify inefficient operation steps in a preset operation script from the historical processing information, wherein the inefficient operation steps include operation steps whose average processing time is greater than a first preset threshold and / or whose failure rate is greater than a second preset threshold;

[0022] The historical processing information is used to train and generate a script optimization model, and the inefficient operation steps are adjusted through the script optimization model, so as to optimize and update the preset operation scripts in the preset operation script library.

[0023] Optionally, after the step of allowing the user to select a specific processing method through the prompt window, the method further includes:

[0024] When the specific processing method is that the user processes the solution displayed in the prompt window, the prompt window displays one or more solutions, and the solutions include specific operation steps and operation suggestions;

[0025] The specific operation steps and operation suggestions are provided for the user to refer to and execute to handle the abnormal state. When the specific operation steps are completed, the user is prompted to submit feedback information to confirm whether the abnormal state is successfully handled.

[0026] Furthermore, in order to achieve the above-mentioned object, the present invention also provides an abnormal state processing device of a service system, and the abnormal state processing device of the service system comprises:

[0027] An abnormal state detection module monitors the request of the communication interface and detects whether the communication interface is in an abnormal state;

[0028] A processing method selection module generates a prompt window when an abnormal state is detected, allowing the user to select a specific processing method through the prompt window, wherein the specific processing method includes automatic processing by the system and processing by the user according to the solution displayed in the prompt window;

[0029] The system automatic processing module, when the specific processing method is system automatic processing, identifies the user's current operation steps, determines the target preset operation script according to the current operation steps, and processes the abnormal state through the target preset operation script.

[0030] Furthermore, to achieve the above-mentioned purpose, the present invention also provides an abnormal state processing device of a service system, wherein the abnormal state processing device of the service system includes a memory, a processor, and an abnormal state processing program of the service system stored in the memory and executable on the processor, and when the abnormal state processing program of the service system is executed by the processor, the steps of the abnormal state processing method of the service system as described above are implemented.

[0031] Furthermore, to achieve the above-mentioned purpose, the present invention also provides a computer storage medium, on which is stored an abnormal state handling program of a service system, and when the abnormal state handling program of the service system is executed by a processor, the steps of the abnormal state handling method of the service system as described above are implemented.

[0032] The present invention relates to an abnormal state processing method of a service system, aiming to solve the problem of how to improve the efficiency and accuracy of the system in processing abnormal states. The present invention detects whether a communication interface is in an abnormal state by monitoring the request of the communication interface; when an abnormal state is detected, a prompt window is generated, and the user selects a specific processing method through the prompt window, and the specific processing method includes automatic processing by the system and processing by the user according to the solution displayed in the prompt window; when the specific processing method is automatic processing by the system, the user's current operation steps are identified, and a target preset operation script is determined according to the current operation steps, and the abnormal state is processed by the target preset operation script. The present invention can realize real-time monitoring and efficient processing of abnormal states of the system, and improve the reliability of the system and user experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] Figure 1 A schematic diagram of the structure of the equipment hardware operating environment involved in the embodiment of the abnormal state processing device of the service system of the present invention;

[0034] Figure 2 A flowchart of a first embodiment of a method for handling abnormal status of a service system of the present invention;

[0035] Figure 3 It is a functional module diagram of a preferred embodiment of the abnormal state processing device of the service system of the present invention.

[0036] The realization of the purpose, functional features and advantages of the present invention will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0037] It should be understood that the specific embodiments described herein are only used to explain the present invention, and are not used to limit the present invention.

[0038] It should be noted that with the rapid development of computer technology and the Internet, service systems have been widely used in various industries, such as e-commerce systems, financial service systems, medical information systems, etc. In the operation of these service systems, various abnormal conditions are often encountered, such as communication interface abnormalities, operation step failures, data processing errors, etc. If these abnormal conditions cannot be handled in a timely and effective manner, they will not only affect the normal operation of the system, but may also cause data loss, service interruption, and even cause more serious system failures, causing inconvenience and losses to users.

[0039] Existing service systems usually rely on manual intervention when handling abnormal conditions. Staff need to manually monitor system logs and manually handle abnormalities when they are found. This approach is not only inefficient but also prone to errors. Especially when faced with complex and changing abnormal situations, the response speed and accuracy of manual processing are difficult to guarantee. In addition, some existing automated processing methods also have certain limitations. They are often only targeted at specific types of abnormal conditions and lack flexibility and adaptability.

[0040] With the development of artificial intelligence and big data technology, more and more research has begun to explore the use of intelligent technology to automatically detect and handle abnormal conditions. For example, machine learning algorithms are used to analyze historical data to automatically identify and predict abnormal situations; image recognition technology is used to analyze operation pages to automatically determine whether the user's operation steps are correct. However, these technologies still have some problems in practical applications, such as high algorithm complexity, strong data dependence, and low processing efficiency, which still need further optimization and improvement.

[0041] Therefore, there is an urgent need for an efficient, accurate and intelligent service system abnormal state processing method that can monitor the system operation status in real time, automatically detect and handle abnormal situations, improve system reliability and user experience, reduce manual intervention, and realize intelligent management and optimization of the system.

[0042] Based on the above-mentioned defects, the present invention provides an abnormal state processing device of a service system, referring to Figure 1 , Figure 1 A schematic diagram of the structure of the device hardware operating environment involved in the abnormal state processing device embodiment of the service system of the present invention.

[0043] like Figure 1 As shown, the abnormal state processing device of the service system may include: a processor 1001, such as a CPU, a communication bus 1002, a user interface 1003, a network interface 1004, and a memory 1005. Among them, the communication bus 1002 is used to realize the connection and communication between these components. The user interface 1003 may include a display screen (Display), an input unit such as a keyboard (Keyboard), and the optional user interface 1003 may also include a standard wired interface and a wireless interface. The network interface 1004 may optionally include a standard wired interface and a wireless interface (such as a WI-FI interface). The memory 1005 may be a high-speed RAM memory, or a stable memory (non-volatile memory), such as a disk memory. The memory 1005 may also be a storage device independent of the aforementioned processor 1001.

[0044] Those skilled in the art will understand that Figure 1The hardware structure of the abnormal state processing device of the service system shown in the figure does not constitute a limitation on the abnormal state processing device of the service system, and may include more or less components than shown in the figure, or combine certain components, or arrange the components differently.

[0045] like Figure 1 As shown, the memory 1005 as a storage medium may include an operating system, a network communication module, a user interface module, and an abnormal state processing program of the service system. The operating system is a program for managing and controlling the abnormal state processing equipment and software resources of the service system, and supports the operation of the network communication module, the user interface module, the abnormal state processing program of the service system, and other programs or software; the network communication module is used to manage and control the network interface 1004; the user interface module is used to manage and control the user interface 1003.

[0046] exist Figure 1 In the hardware structure of the abnormal state processing device of the service system shown in the figure, the network interface 1004 is mainly used to connect to the background server and perform data communication with the background server; the user interface 1003 is mainly used to connect to the client and perform data communication with the client; the processor 1001 can call the abnormal state processing program of the service system stored in the memory 1005, and perform the following operations:

[0047] Monitoring the communication interface request and detecting whether the communication interface is in an abnormal state;

[0048] When an abnormal state is detected, a prompt window is generated for the user to select a specific processing method through the prompt window, and the specific processing method includes automatic processing by the system and processing by the user according to the solution displayed in the prompt window;

[0049] When the specific processing method is automatic processing by the system, the user's current operation steps are identified, a target preset operation script is determined according to the current operation steps, and the abnormal state is processed by the target preset operation script.

[0050] Furthermore, the step of identifying the current operation step of the user includes:

[0051] Using an image recognition algorithm to segment the operation page where the current operation step is located, and extracting features from the segmented operation page to obtain a feature map;

[0052] A candidate frame is obtained by using the feature map and the region candidate network, an operation candidate frame is screened out from the candidate frame, and a current operation step of the user is determined according to the operation candidate frame.

[0053] Furthermore, before the step of determining the target preset operation script according to the current operation step, the method further includes:

[0054] A preset operation script library is constructed, in which preset operation scripts corresponding to the operation steps are stored, and the preset operation scripts are used to automatically execute preset operation tasks.

[0055] Furthermore, the step of constructing a preset operation script library includes:

[0056] Acquire historical operation data, perform cluster analysis on the historical operation data using a clustering algorithm, generate operation step clusters, generate one or more preset operation scripts for each operation step cluster, and construct the preset operation script library through the preset operation scripts of all operation step clusters.

[0057] Furthermore, the step of determining a target preset script according to the current operation step includes:

[0058] The corresponding target preset operation script is determined from the preset operation script library according to the current operation step.

[0059] Furthermore, after the step of building a preset operation script library, the following step is further included:

[0060] Acquire historical processing information of historical abnormal states, and identify inefficient operation steps in a preset operation script from the historical processing information, wherein the inefficient operation steps include operation steps whose average processing time is greater than a first preset threshold and / or whose failure rate is greater than a second preset threshold;

[0061] The historical processing information is used to train and generate a script optimization model, and the inefficient operation steps are adjusted through the script optimization model, so as to optimize and update the preset operation scripts in the preset operation script library.

[0062] Furthermore, after the step of allowing the user to select a specific processing method through the prompt window, the method further includes:

[0063] When the specific processing method is that the user processes the solution displayed in the prompt window, the prompt window displays one or more solutions, and the solutions include specific operation steps and operation suggestions;

[0064] The specific operation steps and operation suggestions are provided for the user to refer to and execute to handle the abnormal state. When the specific operation steps are completed, the user is prompted to submit feedback information to confirm whether the abnormal state is successfully handled.

[0065] The specific implementation of the abnormal state processing device of the service system of the present invention is basically the same as the various embodiments of the abnormal state processing method of the service system described below, and will not be repeated here.

[0066] The present invention also provides a method for processing an abnormal state of a service system based on the abnormal state processing device of the service system.

[0067] Reference Figure 2 , Figure 2 It is a flowchart of a first embodiment of a method for handling abnormal status of a service system of the present invention.

[0068] The embodiment of the present invention provides an embodiment of a method for handling abnormal status of a service system. It should be noted that although a logical order is shown in the flow chart, in some cases, the steps shown or described may be executed in an order different from that shown here.

[0069] In various embodiments of the abnormal state processing method of the service system, the execution subject is the abnormal state processing device of the service system.

[0070] The abnormal state processing method of the service system is applied to the abnormal state processing device of the service system, and the abnormal state processing method of the service system includes:

[0071] Step S10, monitoring the request of the communication interface to detect whether the communication interface is in an abnormal state;

[0072] With the rapid development of computer technology and the Internet, service systems have been widely used in various industries, such as e-commerce systems, financial service systems, medical information systems, etc. In the operation of these service systems, various abnormal conditions are often encountered, such as communication interface abnormalities, operation step failures, data processing errors, etc. If these abnormal conditions cannot be handled in a timely and effective manner, they will not only affect the normal operation of the system, but may also cause data loss, service interruption, and even cause more serious system failures, causing inconvenience and losses to users.

[0073] Existing service systems usually rely on manual intervention when handling abnormal conditions. Staff need to manually monitor system logs and manually handle abnormalities when they are found. This approach is not only inefficient but also prone to errors. Especially when faced with complex and changing abnormal situations, the response speed and accuracy of manual processing are difficult to guarantee. In addition, some existing automated processing methods also have certain limitations. They are often only targeted at specific types of abnormal conditions and lack flexibility and adaptability.

[0074] With the development of artificial intelligence and big data technology, more and more research has begun to explore the use of intelligent technology to automatically detect and handle abnormal conditions. For example, machine learning algorithms are used to analyze historical data to automatically identify and predict abnormal situations; image recognition technology is used to analyze operation pages to automatically determine whether the user's operation steps are correct. However, these technologies still have some problems in practical applications, such as high algorithm complexity, strong data dependence, and low processing efficiency, which still need further optimization and improvement.

[0075] Therefore, there is an urgent need for an efficient, accurate and intelligent service system abnormal state processing method that can monitor the system operation status in real time, automatically detect and handle abnormal situations, improve system reliability and user experience, reduce manual intervention, and realize intelligent management and optimization of the system.

[0076] In this embodiment, the requests of each communication interface in the service system are continuously monitored, including but not limited to API calls, data transmission, network connections, etc. This can be achieved through log records, network packet capture, application monitoring tools, etc.

[0077] Monitoring tools or modules can be deployed in the service system to monitor all communication interface requests in real time. The monitoring tool can record detailed information of each request, such as request time, request type, request parameters, response time, response status, etc. The monitoring data is stored in the log system for subsequent analysis and processing.

[0078] Analyze and judge the requests and responses of the communication interface to identify whether there are any abnormal situations, such as request timeout, response error, connection failure, etc. Judgment can be made through preset rules or anomaly detection algorithms, such as checking HTTP status code, response time, error information, etc.

[0079] Set up anomaly detection rules, for example:

[0080] Request timeout: If the response time of a request exceeds the preset threshold, it is considered a request timeout exception.

[0081] Response error: If the HTTP status code of a request is not in the 2xx range, it is considered a response error exception.

[0082] Connection failure: If a request cannot establish a connection, it is considered a connection failure exception.

[0083] Analyze monitoring data in real time and identify abnormal conditions based on abnormality detection rules. When an abnormal condition is detected, the subsequent abnormality handling process is triggered.

[0084] Example description: HTTPAPI interface monitoring

[0085] Monitor communication interface requests: deploy a monitoring module to record all HTTP API interface request information in real time. The recorded content includes: request URL, request method (GET, POST, etc.), request parameters, request time, response time, HTTP status code, response content, etc.

[0086] Check whether the communication interface is in an abnormal state:

[0087] To set anomaly detection rules:

[0088] Request timeout: If the response time of a request exceeds 3 seconds, it is considered a request timeout exception.

[0089] Response error: If the HTTP status code of a request is not in the 2xx range, it is considered a response error exception.

[0090] Connection failure: If a request cannot establish a connection, it is considered a connection failure exception.

[0091] The monitoring module analyzes the recorded data in real time and identifies abnormal conditions according to the above rules. When an abnormal condition is detected, the monitoring module generates corresponding logs and triggers the abnormality handling process, such as notifying the operation and maintenance personnel or automatically executing the preset recovery operation.

[0092] By monitoring the requests of the communication interface and detecting whether there are any abnormal conditions, abnormal situations that may occur in the service system can be discovered and handled in a timely manner, thereby improving the reliability and stability of the system.

[0093] Step S20, when an abnormal state is detected, a prompt window is generated for the user to select a specific processing method through the prompt window, and the specific processing method includes automatic processing by the system and processing by the user according to the solution displayed in the prompt window;

[0094] In this embodiment, when an abnormal state of the system is detected, the system will automatically pop up a prompt window to inform the user that an abnormality has occurred, so that the user can choose an appropriate processing method after understanding the abnormal situation. The information displayed in the prompt window includes: abnormality type, abnormality description, occurrence time, etc. The prompt window also includes options for selecting a processing method, such as "system automatic processing" and "user manual processing".

[0095] The system provides two ways to handle exceptions: automatic system handling: the system automatically handles exceptions according to preset rules or scripts; users handle according to the solutions displayed in the prompt window: the prompt window provides specific solutions and operation suggestions, and users manually handle exceptions according to these suggestions. It provides flexible handling methods, which can automatically handle common exceptions and allow users to manually intervene when necessary.

[0096] The user views the exception information in the prompt window and selects a specific processing method according to the prompt. If the user selects "Automatic processing by the system", the system will automatically execute the preset processing script. If the user selects "Manual processing by the user", the prompt window will display specific solutions and operation suggestions to guide the user to perform manual processing.

[0097] When the user selects automatic processing by the system, the system automatically calls the preset processing script or rule and performs the corresponding operation to resolve the exception. For example, for a request timeout exception, the system can automatically retry the request or switch to an alternate server.

[0098] Example description: Exception handling in Web applications

[0099] Generate a prompt window: In a web application, when the system detects that an API request has timed out, a prompt window is generated, displaying the following information:

[0100] Exception type: Request timeout

[0101] Exception description: The API request did not return a response within the scheduled time.

[0102] Time of occurrence: 2024-08-01 12:00:00

[0103] The prompt window contains processing mode options: "Automatic processing by the system" and "Manual processing by the user".

[0104] The user selects a specific processing method through the prompt window: After the user sees the prompt window, select "Automatic processing by the system". Automatic processing by the system: The system automatically retries the API request or switches to the backup API server.

[0105] If the user selects "User Manual Processing", the prompt window will display the following solutions:

[0106] Check whether the network connection is normal

[0107] Manually resend the API request

[0108] Contact your system administrator

[0109] The user follows the prompts and performs the operations in the solution step by step to solve the API request timeout problem.

[0110] By generating a prompt window and providing specific processing methods, the system can promptly notify users of abnormal situations and provide flexible processing options, which can automatically handle common exceptions and allow users to manually intervene when necessary, thereby improving system reliability and user experience.

[0111] Step S30, when the specific processing method is automatic processing by the system, the current operation steps of the user are identified, a target preset operation script is determined according to the current operation steps, and the abnormal state is processed by the target preset operation script.

[0112] In this embodiment, when the user selects the system to automatically process, the system needs to identify the operation steps currently being performed by the user and understand the specific operation scenario in which the user is when the exception occurs, so as to select an appropriate preset operation script for processing. The current operation steps can be identified by analyzing the user's operation log, page status, input content, etc., and the page monitoring tool can be used to track the user's current page and its interaction details.

[0113] The system matches the identified current operation step with the scripts in the operation script library. The operation script library contains multiple scripts, each of which is associated with a specific operation step and abnormal situation. The system selects the target preset operation script that matches the current operation step and abnormal status from the operation script library.

[0114] The system executes the instructions in the target preset operation script. The script can include the following operations: retry the current operation steps, such as resending the request or reloading the page; adjust related configurations, such as modifying network settings or increasing resource allocation; perform specific recovery operations, such as restarting services or clearing caches; after executing the operation script, the system monitors the operation results and records the processing process and results.

[0115] Example: Exception handling in an online shopping system

[0116] Identify the user's current operation step: When the user is making a payment, the system detects that the payment request has timed out. The user selects the system to automatically process, and the system begins to identify the user's current operation step, that is, the payment operation is in progress. The system determines through log records and page monitoring that the user is currently on the payment page and has entered the payment information.

[0117] Determine the target preset operation script based on the current operation steps: The system finds the script related to the payment operation in the operation script library. The target preset operation scripts include: retrying payment request, checking payment gateway status, switching backup payment channel, etc.

[0118] Handle abnormal status through target preset operation script: The system executes the instructions in the script, first retries the payment request, and if it still fails, checks the payment gateway status. If there is a problem with the payment gateway, it switches to the backup payment channel and resends the payment request. The system monitors the results of the payment request and records the entire processing process.

[0119] By identifying the user's current operation steps, determining the target preset operation script according to the current operation steps, and handling the abnormal state through the target preset operation script, it is possible to realize automatic processing of system abnormalities and improve system reliability and user experience.

[0120] The present invention relates to an abnormal state processing method of a service system, aiming to solve the problem of how to improve the efficiency and accuracy of the system in processing abnormal states. The present invention detects whether a communication interface is in an abnormal state by monitoring the request of the communication interface; when an abnormal state is detected, a prompt window is generated, and the user selects a specific processing method through the prompt window, and the specific processing method includes automatic processing by the system and processing by the user according to the solution displayed in the prompt window; when the specific processing method is automatic processing by the system, the user's current operation steps are identified, and a target preset operation script is determined according to the current operation steps, and the abnormal state is processed by the target preset operation script. The present invention can realize real-time monitoring and efficient processing of abnormal states of the system, and improve the reliability of the system and user experience.

[0121] Furthermore, a second embodiment of the abnormal state processing method of the service system of the present invention is proposed. In the above step S30, the step of identifying the current operation step of the user includes:

[0122] Step a1, segmenting the operation page where the current operation step is located using an image recognition algorithm, and extracting features from the segmented operation page to obtain a feature map;

[0123] Step a2, using the feature map and the region candidate network to obtain a candidate box, an operation candidate box selected from the candidate box, and determining the current operation step of the user according to the operation candidate box.

[0124] In this embodiment, a convolutional neural network (CNN) is used to segment the operation page currently located by the user, and the page is divided into multiple small areas. Feature extraction is performed on each small area to generate a feature map. The feature map contains the features of each element in the page, such as buttons, input boxes, text boxes, etc. The feature extraction process can include multi-layer convolution, pooling and activation operations to obtain a high-quality feature map.

[0125] The system generates multiple candidate boxes through the region proposal network (RPN), each of which represents a potential operation area. For each candidate box, the system calculates its feature vector and matches it with the preset operation feature library, and selects the candidate box with the highest similarity as the operation candidate box. Feature matching includes the following steps:

[0126] Extract visual features (such as color, shape, texture, etc.) of elements within the candidate box.

[0127] Calculate the feature vector of the elements within the candidate box.

[0128] The calculated feature vector is compared with the feature vector in the operational feature library, and the candidate box with the highest similarity is selected.

[0129] You can also filter the candidate boxes by:

[0130] Filtering based on position and layout: Filter candidate boxes that meet the expected operation area based on the position and layout characteristics of the elements on the page. Filter candidate boxes that meet specific position and layout characteristics by comparing the position coordinates, area, aspect ratio and other attributes of the candidate boxes.

[0131] Filtering based on context information: Use the context information of other elements on the page to filter out the candidate boxes that are most likely to contain the user's operation steps. By analyzing the type, content, and relationship of other elements on the page, determine which candidate boxes are associated with the current operation step. For example, if the user operates near an input box, the input box and its nearby candidate boxes may be operation candidate boxes.

[0132] Filtering based on action detection: By detecting the user's operation actions (such as clicking, sliding, inputting, etc.), the candidate boxes that match the user's operation actions are filtered out. By recording and analyzing the user's operation trajectory and action features, the candidate boxes that match these action features are selected. For example, the user's click action is detected to filter out the clicked candidate boxes.

[0133] Then, based on the filtered operation candidate box, the specific operations of its internal elements are further analyzed.

[0134] The analysis steps include:

[0135] Determine the operation type: Determine the user's operation type by analyzing the element types in the candidate box (such as buttons, input boxes, drop-down menus, etc.).

[0136] Determine the operation content: For example, for a button operation, determine the button label or ID; for an input box operation, determine the input text content.

[0137] The system determines the user's current operation step by combining the operation type and operation content. For example, when a user fills out an online form, the system generates multiple candidate boxes through the regional candidate network (RPN). For each candidate box, the system extracts the feature vectors of the elements within it, such as the border features and position features of the text box. The system matches these feature vectors with the feature vectors in the operation feature library and selects the most similar candidate box. If the system recognizes that the user clicks a "Submit" button, the user's current operation step is determined: the system analyzes the filtered operation candidate boxes and determines the specific operations within them. By analyzing the features of the elements in the candidate boxes, the system recognizes that the user clicked on the "Submit" button. The system combines the operation type (button click) and the operation content (button label) to determine that the user's current operation step is "Submit Form".

[0138] Example: Operation step identification in an online form filling system

[0139] Use image recognition algorithms to segment the operation page where the current operation step is located, and extract features from the segmented operation page to obtain a feature map: When users fill out online forms, the system uses convolutional neural networks (CNN) to segment the form page into multiple regions. Extract features from each region to generate a feature map. The feature map includes various elements in the form, such as text boxes, check boxes, buttons, etc.

[0140] Use feature maps and region candidate networks to obtain candidate boxes, and filter out operation candidate boxes from the candidate boxes: The system uses the region candidate network (RPN) to process the feature map and generate multiple candidate boxes. Each candidate box represents a potential operation area. Perform feature matching on each candidate box and select the candidate box that is most similar to the predefined features in the operation feature library. For example, the system recognizes that the user clicked a "Submit" button.

[0141] Determine the user's current operation step based on the operation candidate box: Analyze the filtered operation candidate box and determine the specific operation inside it. The system recognizes that the user clicked on the "Submit" button, and based on the operation type and operation content, determines that the user's current operation step is "Submit the form."

[0142] Through the above steps, this embodiment can accurately identify the user's operation behavior, and select a suitable processing script for automatic processing based on the user's operation behavior, thereby improving the intelligence and automation level of the system.

[0143] Furthermore, a third embodiment of the abnormal state processing method of the service system of the present invention is proposed. In the above step S30, before the step of determining the target preset operation script according to the current operation step, it also includes:

[0144] Step b1, constructing a preset operation script library, in which there are preset operation scripts corresponding to the operation steps, and the preset operation scripts are used to automatically execute preset operation tasks.

[0145] In this embodiment, common operation steps and corresponding abnormal states in the system are collected, and preset operation scripts are written for each operation step and abnormal state. These scripts contain detailed operation steps and instructions. The written operation scripts are stored in a structured database or script library to facilitate system calls. These preset operation scripts can automatically execute preset operation tasks and perform exception handling when abnormal states are detected.

[0146] Ensure that each operation step has a corresponding preset operation script, which contains specific operations to handle abnormal conditions that may occur in the step. In the script library, each operation step and abnormal condition has a unique identifier for quick search and call.

[0147] When the system detects an abnormal state and identifies the user's current operation steps, the system will search for the corresponding preset operation script in the script library. The system automatically calls and executes the found operation script to complete the preset operation task and handle the abnormal state. The operation script can include specific operation instructions such as retrying requests, modifying configurations, and restarting services.

[0148] Example description:

[0149] Build a preset operation script library: Collect common operation steps in the financial insurance service system, such as user login, policy query, premium payment, claim application, etc. Write preset operation scripts to handle common abnormal conditions in these operation steps. For example, operation scripts to handle login failure, query timeout, payment failure, claim application failure, etc. Store the written operation scripts in a structured database and build a preset operation script library.

[0150] The preset operation script library contains preset operation scripts corresponding to the operation steps: Ensure that each operation step has a corresponding preset operation script, which contains specific operations for handling abnormal conditions that may occur in the step. In the script library, each operation step and abnormal condition has a unique identifier for quick search and call.

[0151] For example, collect common operation steps and abnormal status:

[0152] User login: Login failed;

[0153] Policy query: Query timeout;

[0154] Premium Payment: Payment Failure;

[0155] Claim application: Application failed.

[0156] To write a preset action script:

[0157] Login failure script: retry login, change network settings, send reminder emails, etc.

[0158] Query timeout script: re-query, optimize query conditions, notify technical support, etc.;

[0159] Payment failure script: retry payment, check payment gateway status, switch to alternative payment method, etc.;

[0160] Application failure script: retry application, check application information, notify customer service, etc.

[0161] Store operation scripts: Store the written operation scripts in a structured database and establish a preset operation script library.

[0162] When the system detects an abnormal state and identifies the user's current operation steps, the system will search for the corresponding preset operation script in the script library. The system automatically calls and executes the found operation script to complete the preset operation task and handle the abnormal state.

[0163] Through the above steps, this embodiment can automatically execute preset operation tasks when an abnormal state is detected, realize automatic processing of the system, and improve processing efficiency and accuracy.

[0164] Furthermore, a fourth embodiment of the abnormal state processing method of the service system of the present invention is proposed. In the above step b1, the step of building a preset operation script library includes:

[0165] Step c1, obtaining historical operation data, performing cluster analysis on the historical operation data using a clustering algorithm, generating operation step clusters, generating one or more preset operation scripts for each operation step cluster, and constructing the preset operation script library through the preset operation scripts of all operation step clusters.

[0166] In this embodiment, obtaining historical operation data refers to collecting user operation data generated during the operation of the system, which includes user behavior records in different operation steps. The user operation data generated during the operation of the system can be collected by log recording, database query, etc. The data includes user behavior records in different operation steps, such as click, input, submit and other operations, as well as operation time, operation results and other information. For example, in the financial insurance service system, operation data such as user login, policy query, premium payment, and claim application are collected.

[0167] Select appropriate clustering algorithms, such as K-means, DBSCAN, etc., to perform cluster analysis on historical operation data. Clustering algorithms classify similar operation steps into one category and generate multiple operation step clusters. For example, operations where user login failed are classified into one category, operations where policy query timed out are classified into one category, and operations where premium payment failed are classified into one category.

[0168] Based on the cluster analysis results, multiple operation step clusters are generated. For each operation step cluster, a preset operation script is written. These scripts contain specific operations for handling common abnormal states of the operation steps in the cluster. For example, an operation script for retrying login and changing network settings is written for the operation step cluster of user login failure; an operation script for re-querying and optimizing query conditions is written for the operation step cluster of policy query timeout.

[0169] Summarize the preset operation scripts generated by clustering all operation steps, and organize and classify them according to the operation step clusters. Store the organized operation scripts in a structured database to build a preset operation script library. For example, store all operation scripts that handle user login failures and all operation scripts that handle policy query timeouts together to facilitate system calls.

[0170] Example description:

[0171] Obtain historical operation data: Collect user operation data in the financial insurance service system, such as login, query, payment, application and other operation records. The data includes operation type, operation time, operation result and other information.

[0172] Use a clustering algorithm to perform cluster analysis on the historical operation data: Select the K-means clustering algorithm to perform cluster analysis on the collected operation data. Group similar operation steps into one category and generate multiple operation step clusters. For example, group all user login failure operations into one category, and group all policy query timeout operations into one category.

[0173] Generate operation step clusters and generate one or more preset operation scripts for each operation step cluster: Based on the clustering results, write a preset operation script for each operation step cluster. For example, write an operation script for retrying login and changing network settings for the operation step cluster of failed user login. Write an operation script for re-querying and optimizing query conditions for the operation step cluster of policy query timeout.

[0174] The preset operation script library is constructed by clustering all the preset operation scripts of the operation steps: the preset operation scripts generated by clustering all the operation steps are summarized, and they are sorted and classified according to the operation step clusters. The sorted operation scripts are stored in a structured database to build a preset operation script library. For example, all the operation scripts for handling user login failures and all the operation scripts for handling policy query timeouts are stored together to facilitate system calls.

[0175] Through the above steps, this embodiment can realize automatic system processing of abnormal conditions and improve processing efficiency and accuracy.

[0176] Furthermore, a fifth embodiment of the abnormal state processing method of the service system of the present invention is proposed. In the above step b1, the step of determining the target preset script according to the current operation step includes:

[0177] Step d1, determining the corresponding target preset operation script from the preset operation script library according to the current operation step.

[0178] In this embodiment, after detecting an abnormal state, the system first identifies the user's current operation steps. Using image recognition algorithms and region candidate networks, the operation candidate boxes are extracted from the operation page and the user's specific operation steps are determined. The operation steps may include login, query, payment, application, etc.

[0179] After identifying the user's current operation step, the system uses the unique identifier of the operation step to search in the preset operation script library. The preset operation script library is a structured database that stores the operation script corresponding to each operation step. Each operation step has a unique identifier in the script library for quick search.

[0180] The system finds the preset operation script corresponding to the current operation step in the preset operation script library. These scripts contain specific operations for handling abnormal conditions that may occur in the current operation step. The found operation script is used as the target preset operation script, and the system automatically calls and executes the script.

[0181] Example description:

[0182] Identify the current operation step: When a user queries an insurance policy in the financial insurance service system, the system detects an abnormal query timeout. The system uses image recognition algorithms and region candidate networks to identify that the user's current operation step is "policy query."

[0183] Searching the preset operation script library: The system uses the unique identifier of the "policy query" operation step to search in the preset operation script library. The preset operation script library stores the operation scripts for handling various abnormal states in the "policy query" step, including query timeout, query failure, etc.

[0184] Determine the target preset operation script: The system finds the operation script for handling "policy query timeout" in the preset operation script library. The operation script includes specific operations such as re-querying, optimizing query conditions, and notifying technical support. The system uses the found operation script as the target preset operation script and automatically calls and executes it.

[0185] In this embodiment, by searching for the corresponding target preset operation script in the preset operation script library, the system can automatically handle the abnormal state quickly and accurately.

[0186] Furthermore, a sixth embodiment of the abnormal state processing method of the service system of the present invention is proposed. In the above step b1, after the step of building a preset operation script library, the method further includes:

[0187] Step e1, obtaining historical processing information of historical abnormal states, and identifying inefficient operation steps in a preset operation script from the historical processing information, wherein the inefficient operation steps include operation steps with an average processing time greater than a first preset threshold and / or operation steps with a failure rate greater than a second preset threshold;

[0188] Step e2, using the historical processing information to train and generate a script optimization model, and adjusting the inefficient operation steps through the script optimization model, so as to optimize and update the preset operation scripts in the preset operation script library.

[0189] In this embodiment, when the system processes an abnormal state, it will record various information during the process, including operation steps, processing time, processing results, etc. This historical processing information is collected as basic data for subsequent analysis and optimization. For example, the processing information of abnormal states such as user login failure, policy query timeout, and premium payment failure in the financial insurance service system is collected.

[0190] Use data analysis tools (such as Python's Pandas, NumPy, etc.) to collect statistics and analyze the historical processing information. Identify the operation steps whose average processing time is greater than the first preset threshold and / or whose failure rate is greater than the second preset threshold. For example, analyze the processing information of user login failures and find the operation steps whose average processing time exceeds 5 seconds or whose failure rate exceeds 10%.

[0191] Use machine learning algorithms (such as decision trees, random forests, neural networks, etc.) to train historical processing information and generate optimization models. When training the model, input features include the processing time, failure rate, processing results, etc. of the operation steps, and output optimization suggestions.

[0192] For example, collect historical processing information from sources such as system logs and database records. The data includes operation steps, processing time, processing results, failure rate, etc. Deal with data problems such as missing values ​​and outliers to ensure data quality. Extract useful features from the original data. For example, extract processing time, operation type, user behavior, system status, etc. Select the features that most affect processing efficiency and success rate as the input of the model. Divide the prepared data set into training set and test set. Usually divided in an 80:20 ratio, that is, 80% is used for training the model and 20% is used for testing the model. Use the training data to build a decision tree model, and minimize the classification error or mean square error of each node by continuously splitting the data set. Use the test data to evaluate the trained model, and the evaluation indicators include accuracy, precision, recall, F1-score, mean square error, etc. Select the best model based on the evaluation results. The stability and generalization ability of the model can be further verified through cross-validation. Select the best model as the script optimization model, and use the model to optimize inefficient operation steps.

[0193] According to the recommendations of the optimization model, adjust the identified inefficient operation steps, optimize their execution order, parameter settings, etc. Update the optimized operation scripts to the preset operation script library to ensure that the script library is always efficient and accurate. For example, adjust the user login failure processing steps, optimize the interval time for retrying login, change the specific parameters of network settings, etc., and update the optimized scripts to the script library.

[0194] Example description:

[0195] Obtain historical processing information of historical abnormal states: Collect user operation data in the financial insurance service system, such as login failure, query timeout, payment failure, application failure and other processing information. The data includes operation steps, processing time, processing results, failure rate and other information.

[0196] Identify inefficient operation steps in preset operation scripts from historical processing information: Use data analysis tools to collect statistics and analyze the collected historical processing information. Identify operation steps with an average processing time greater than 5 seconds and / or a failure rate greater than 10%. For example, analyze the processing information of user login failures and find out the operation steps with a processing time greater than 5 seconds.

[0197] Use historical processing information to train and generate script optimization models: Use machine learning algorithms to train historical processing information and generate optimization models. For example, use the random forest algorithm to train the model and generate a model that optimizes the steps for processing failed user logins.

[0198] Adjust inefficient operation steps through the script optimization model to update the preset operation scripts in the preset operation script library: According to the recommendations of the optimization model, adjust the identified inefficient operation steps and optimize their execution order, parameter settings, etc. Update the optimized operation scripts to the preset operation script library to ensure that the script library is always efficient and accurate. For example, adjust the steps for handling user login failures, optimize the interval time for retrying logins, change the specific parameters of network settings, etc., and update the optimized scripts to the script library.

[0199] Through the above steps, this embodiment can continuously optimize and update the preset operation script library to improve the efficiency and accuracy of the system in handling abnormal conditions.

[0200] Furthermore, a seventh embodiment of the abnormal state processing method of the service system of the present invention is proposed. In the above step S20, after the step of allowing the user to select a specific processing method through the prompt window, the method further includes:

[0201] Step f1, when the specific processing method is that the user processes according to the solution displayed in the prompt window, the prompt window displays one or more solutions, and the solutions include specific operation steps and operation suggestions;

[0202] Step f2, the specific operation steps and operation suggestions are provided for the user to refer to and execute to handle the abnormal state. When the specific operation steps are completed, the user is prompted to submit feedback information to confirm whether the abnormal state is successfully handled.

[0203] In this embodiment, after the system detects an abnormal state, a prompt window is generated, and the user selects a specific processing method through the prompt window. If the user chooses to manually process the abnormal state, the system will display one or more solutions in the prompt window. For example, the prompt window displays two solutions:

[0204] Solution 1: Re-query

[0205] Specific steps:

[0206] Return to the query page

[0207] Re-enter the search criteria

[0208] Click the query button

[0209] Solution 2: Optimize query conditions

[0210] Specific steps:

[0211] Check the query conditions you entered

[0212] Confirm that the query conditions are correct

[0213] Simplify the query conditions and re-enter

[0214] Click the query button

[0215] The solution displayed in the prompt window can include text, video, diagram, etc. For example:

[0216] Text solutions: Detailed text instructions with step-by-step instructions and suggestions.

[0217] Video Solutions: Tutorial videos that show you how to do it.

[0218] Pictorial solutions: Instructions with screenshots or diagrams that visually demonstrate each step.

[0219] Interactive guides: Users can click and interact to complete the steps step by step.

[0220] The user follows the specific steps and suggestions displayed in the prompt window and performs the operation step by step. The system monitors the user's operation in real time and provides further guidance when necessary.

[0221] After the user completes all the operation steps, the system will automatically pop up a feedback prompt window, asking the user to confirm whether the abnormal state has been resolved. The content of the feedback prompt window can be pre-set. For example, the feedback prompt window will display the following content:

[0222] Prompt message: such as "Please confirm whether the problem has been resolved."

[0223] Action buttons: Options such as "Solved", "Unsolved", "Need more help", etc.

[0224] Feedback Instructions: Users can select specific feedback options and fill in additional feedback information.

[0225] The user selects one or more feedback options in the feedback prompt window:

[0226] "Solved": Indicates that the user has successfully resolved the abnormal status through the solution provided by the system.

[0227] “Unresolved”: indicates that the user has not been able to resolve the abnormal status through the solution provided by the system.

[0228] "Need more help": Indicates that the user needs further guidance and assistance.

[0229] Users can fill in detailed feedback descriptions, such as specific problems encountered, reasons for failure to resolve, etc.

[0230] Submit feedback information: After the user selects the feedback option, click the "Submit" button to submit the feedback information to the system. The system receives the feedback information submitted by the user and records it in the database.

[0231] System processing feedback information: The system automatically adjusts the preset operation script library based on user feedback information. If the user selects "unresolved" or "need more help", the system will generate further guidance plans or notify the technical support team to intervene. The system will analyze user feedback information, identify inefficient operation steps, and optimize the processing process.

[0232] Example description:

[0233] User steps: User follows the steps in the video tutorial to reset password. User clicks "Forgot Password", enters registered email address, resets password according to email instructions, and tries to log in again.

[0234] Display feedback prompt window: After the user completes all operation steps, the system will automatically pop up a feedback prompt window. Prompt message: "Please confirm whether the problem has been solved"; operation buttons: "Solved", "Unsolved", "Need more help".

[0235] User selects feedback option: User selects the "Solved" option and fills in the feedback description: "After resetting the password, I successfully logged in."

[0236] Submit feedback information: The user clicks the "Submit" button to submit feedback information.

[0237] The system records user feedback information.

[0238] The system processes the feedback information: The system records the solution as a success case. The system analyzes the feedback information and confirms the effectiveness of the solution.

[0239] This embodiment can effectively obtain user feedback, help the system optimize solutions, and improve the intelligence and automation level of the system by prompting the user to submit feedback information to confirm whether the abnormal state is successfully resolved.

[0240] The invention also provides an abnormal state processing device for a service system.

[0241] Reference Figure 3 , Figure 3 This is a functional module diagram of the first embodiment of the abnormal state processing device of the service system of the present invention. The abnormal state processing device of the service system includes:

[0242] An abnormal state detection module monitors the request of the communication interface and detects whether the communication interface is in an abnormal state;

[0243] A processing method selection module generates a prompt window when an abnormal state is detected, allowing the user to select a specific processing method through the prompt window, wherein the specific processing method includes automatic processing by the system and processing by the user according to the solution displayed in the prompt window;

[0244] The system automatic processing module, when the specific processing method is system automatic processing, identifies the user's current operation steps, determines the target preset operation script according to the current operation steps, and processes the abnormal state through the target preset operation script.

[0245] In addition, an embodiment of the present invention further provides a computer storage medium.

[0246] The storage medium stores an abnormal state processing program of the service system, and when the abnormal state processing program of the service system is executed by the processor, the steps of the abnormal state processing method of the service system as described above are implemented.

[0247] The specific implementation of the storage medium of the present invention is basically the same as the embodiments of the abnormal state processing method of the above-mentioned service system, and will not be repeated here.

[0248] The embodiments of the present invention are described above in conjunction with the accompanying drawings, but the present invention is not limited to the above-mentioned specific implementation methods. The above-mentioned specific implementation methods are merely illustrative and not restrictive. Under the enlightenment of the present invention, ordinary technicians in this field can also make many forms without departing from the scope of protection of the present invention and the claims. All equivalent structures or equivalent process changes made using the contents of the specification and drawings of the present invention, or directly or indirectly used in other related technical fields, are protected by the present invention.

[0249] In the embodiments provided in the present application, it should be understood that the disclosed devices and methods can also be implemented in other ways. The device embodiments described above are merely schematic. For example, the flowcharts and block diagrams in the accompanying drawings show the possible architecture, functions and operations of the devices, methods and computer program products according to the multiple embodiments of the present application. In this regard, each box in the flowchart or block diagram can represent a module, a program segment or a part of a code, and the module, a program segment or a part of a code contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two consecutive boxes can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or the flowchart, and the combination of boxes in the block diagram and / or the flowchart can be implemented with a dedicated hardware-based system that performs a specified function or action, or can be implemented with a combination of dedicated hardware and computer instructions.

[0250] In addition, each functional module in each embodiment of the present application can be integrated together to form an independent part, or each module can exist separately, or two or more modules can be integrated to form an independent part. If the function is implemented in the form of a software functional module and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on such an understanding, the technical solution of the present application is essentially or the part that contributes to the prior art or the part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including several instructions to enable a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM, Read-Only Memory), a random access memory (RAM, RandomAccess Memory), a disk or an optical disk.

[0251] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprise a ..." do not exclude the existence of other identical elements in the process, method, article or device including the elements.

[0252] The above are only various implementations of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A method for handling abnormal status of a service system, characterized in that: The following steps are involved: Monitoring the communication interface request and detecting whether the communication interface is in an abnormal state; When an abnormal state is detected, a prompt window is generated for the user to select a specific processing method through the prompt window, and the specific processing method includes automatic processing by the system and processing by the user according to the solution displayed in the prompt window; When the specific processing method is automatic processing by the system, the user's current operation steps are identified, a target preset operation script is determined according to the current operation steps, and the abnormal state is processed by the target preset operation script.

2. The abnormal state processing method of the service system according to claim 1, characterized in that: The step of identifying the current operation step of the user comprises: Using an image recognition algorithm to segment the operation page where the current operation step is located, and extracting features from the segmented operation page to obtain a feature map; A candidate frame is obtained by using the feature map and the region candidate network, an operation candidate frame is screened out from the candidate frame, and a current operation step of the user is determined according to the operation candidate frame.

3. The abnormal state processing method of the service system according to claim 1, characterized in that: Before the step of determining the target preset operation script according to the current operation step, the method further includes: A preset operation script library is constructed, in which preset operation scripts corresponding to the operation steps are stored, and the preset operation scripts are used to automatically execute preset operation tasks.

4. The abnormal state processing method of the service system according to claim 3, characterized in that: The steps of constructing a preset operation script library include: Acquire historical operation data, perform cluster analysis on the historical operation data using a clustering algorithm, generate operation step clusters, generate one or more preset operation scripts for each operation step cluster, and construct the preset operation script library through the preset operation scripts of all operation step clusters.

5. The abnormal state processing method of the service system according to claim 3, characterized in that: The step of determining the target preset script according to the current operation step comprises: The corresponding target preset operation script is determined from the preset operation script library according to the current operation step.

6. The abnormal state processing method of the service system according to claim 3, characterized in that: After the step of building the preset operation script library, the following steps are also included: Acquire historical processing information of historical abnormal states, and identify inefficient operation steps in a preset operation script from the historical processing information, wherein the inefficient operation steps include operation steps whose average processing time is greater than a first preset threshold and / or whose failure rate is greater than a second preset threshold; The historical processing information is used to train and generate a script optimization model, and the inefficient operation steps are adjusted through the script optimization model, so as to optimize and update the preset operation scripts in the preset operation script library.

7. The abnormal state processing method of the service system as claimed in claim 1, characterized in that: After the step of allowing the user to select a specific processing method through the prompt window, the method further includes: When the specific processing method is that the user processes the solution displayed in the prompt window, the prompt window displays one or more solutions, and the solutions include specific operation steps and operation suggestions; The specific operation steps and operation suggestions are provided for the user to refer to and execute to handle the abnormal state. When the specific operation steps are completed, the user is prompted to submit feedback information to confirm whether the abnormal state is successfully handled.

8. An abnormal state processing device for a service system, characterized in that: The abnormal state processing device of the service system includes: An abnormal state detection module monitors the request of the communication interface and detects whether the communication interface is in an abnormal state; A processing method selection module generates a prompt window when an abnormal state is detected, allowing the user to select a specific processing method through the prompt window, wherein the specific processing method includes automatic processing by the system and processing by the user according to the solution displayed in the prompt window; The system automatic processing module, when the specific processing method is system automatic processing, identifies the user's current operation steps, determines the target preset operation script according to the current operation steps, and processes the abnormal state through the target preset operation script.

9. An abnormal state processing device for a service system, characterized in that: The abnormal state processing device of the service system includes a memory, a processor, and an abnormal state processing program of the service system stored in the memory and executable on the processor. When the abnormal state processing program of the service system is executed by the processor, the steps of the abnormal state processing method of the service system as described in any one of claims 1 to 7 are implemented.

10. A computer storage medium, characterized in that: The storage medium stores an abnormal state processing program of the service system, and when the abnormal state processing program of the service system is executed by the processor, the steps of the abnormal state processing method of the service system according to any one of claims 1 to 7 are implemented.

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