Business work order card processing method and device and storage medium

Abstract

The invention provides a business work order card processing method and device and a storage medium, and the method comprises the steps: obtaining an error log of a business work order, and determining an error code of the error log based on a target BERT model; obtaining a corresponding abnormality diagnosis result based on the error code; determining a corresponding error correction task based on the error code and the abnormality diagnosis result; and on the basis of the error correction task, performing card order error correction processing on the business work order. Therefore, the error correction task is determined through the error code, the card list self-healing processing is automatically completed based on the error correction task, manual intervention is not needed for processing, the cost is reduced, the processing efficiency of opening the card list of the mobile communication service is improved, and the user experience is further improved.

Description

Technical Field

[0001] The present disclosure relates to the field of telecommunication business technology, and in particular to a card order processing method, device and storage medium for a business work order. Background Art

[0002] At present, opening customer services on mobile communication networks involves multiple IT support systems, and multiple IT support systems need to be linked to complete the opening of customer services on the communication network. Specifically, the process of opening customer services on mobile communication networks can include: accepting customer service orders -> allocating hardware / logical resources on the network side such as transmission network / metropolitan area network / core network / value-added network -> completing data configuration on the network side (transmission network / metropolitan area network / core network / value-added network, etc.), opening customer services on the network side -> archiving services and network resources.

[0003] Among them, the activation of customer services in the above mobile communication network may cause card orders due to various reasons (such as inaccurate inventory resource information of the integrated resource system, conflict with existing network resources, and incorrect network element account and password on the network side), thereby affecting user experience and service execution efficiency. In the existing technology, multiple systems cannot be linked and rely on manual processing, which results in high costs, low card order processing efficiency and poor user experience. Summary of the invention

[0004] In order to overcome the problems existing in the related art, the present disclosure provides a method, device and storage medium for processing a business work order.

[0005] According to a first aspect of an embodiment of the present disclosure, a method for processing a service work order is provided, the method comprising:

[0006] Obtain an error log of the business work order, and determine an error code of the error log based on a target BERT model;

[0007] Based on the error code, a corresponding abnormality diagnosis result is obtained;

[0008] Based on the error code and the abnormal diagnosis result, determining a corresponding error correction task;

[0009] Based on the error correction task, the business work order is subjected to error correction processing.

[0010] Optionally, in the embodiment of the present disclosure, determining the error code of the error log based on the target BERT model includes:

[0011] Input the error log into the target BERT model to obtain the entity recognition result and error type corresponding to the error log;

[0012] Obtain error information of the business work order;

[0013] Based on the error information, the entity recognition result and the error type, an error code of the error log is generated by a predefined rule.

[0014] Optionally, in the embodiment of the present disclosure, the error type includes at least one of the following:

[0015] Current network resource conflicts;

[0016] Lack of existing network resources;

[0017] Existing network resources are inconsistent;

[0018] Access issues.

[0019] Optionally, in an embodiment of the present disclosure, the predefined rules include predefined error content and a predefined format; the generating the error code of the error log by the predefined rules includes: generating the error code of the error log according to the predefined format by the predefined error content.

[0020] Optionally, in the embodiment of the present disclosure, performing abnormality diagnosis based on the error code to obtain a corresponding abnormality diagnosis result includes:

[0021] Based on the error code, obtaining an exception information set of the error code through a mapping relationship between the error code and the exception information;

[0022] An abnormality diagnosis is performed on the abnormal information in the abnormal information set to obtain a corresponding abnormality diagnosis result.

[0023] Optionally, in the embodiment of the present disclosure, determining a corresponding error correction task based on the error code and the abnormal diagnosis result includes:

[0024] Based on the error code and the abnormal diagnosis result, determine the corresponding error correction rule through the intelligent error correction service catalog, wherein the intelligent error correction service catalog includes the routing relationship between the error code and the abnormal diagnosis result and the error correction rule;

[0025] Based on the error correction rule, a corresponding error correction task is determined.

[0026] According to a second aspect of an embodiment of the present disclosure, a card order processing device for a business work order is provided, characterized in that the device comprises:

[0027] An error code management module, used to obtain an error log of a business work order and determine an error code of the error log based on a target BERT model;

[0028] An abnormality diagnosis module, used for obtaining a corresponding abnormality diagnosis result based on the error code;

[0029] An intelligent error correction module, used to determine a corresponding error correction task based on the error code and the abnormality diagnosis result;

[0030] The intelligent error correction module is further used to perform card order error correction processing on the business work order based on the error correction task. According to a third aspect of an embodiment of the present disclosure, an electronic device is provided, comprising:

[0031] processor;

[0032] a memory for storing processor-executable instructions;

[0033] The processor is configured to implement the method described in the first aspect above.

[0034] According to a fourth aspect of an embodiment of the present disclosure, a non-temporary computer-readable storage medium is provided, wherein the computer storage medium stores computer-executable instructions; after the computer-executable instructions are executed by a processor, the method described in the first aspect above can be implemented.

[0035] The technical solution provided by the embodiments of the present disclosure may have the following beneficial effects:

[0036] The present disclosure proposes a card order processing method, device and storage medium for a business work order, the method comprising obtaining an error log of the business work order, and determining the error code of the error log based on a target BERT model; obtaining a corresponding abnormal diagnosis result based on the error code; determining a corresponding error correction task based on the error code and the abnormal diagnosis result; and performing card order error correction processing on the business work order based on the error correction task. Thus, the present disclosure can determine the error correction task through the error code, and automatically complete the card order self-healing processing based on the error correction task, without the need for manual intervention, thereby reducing costs, improving the processing efficiency of mobile communication service activation card orders, and further improving user experience.

[0037] It is to be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and, together with the description, serve to explain the principles of the present disclosure.

[0039] Figure 1 It is a flowchart of a method for processing a business work order according to some embodiments of the present disclosure;

[0040] Figure 2 It is a structural schematic diagram of a card order processing device for a business work order according to some embodiments of the present disclosure;

[0041] Figure 3 It is a schematic diagram showing the interaction between a card order processing device for a business work order and a related system according to some embodiments of the present disclosure;

[0042] Figure 4 It is a block diagram of an electronic device suitable for executing a card order processing method for a business work order according to some embodiments of the present disclosure. DETAILED DESCRIPTION

[0043] Some embodiments of the present disclosure will be described in detail here, and examples thereof are shown in the accompanying drawings. When the following description refers to the drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. Various changes, modifications and equivalents of the methods, devices and / or systems described herein will become apparent after understanding the present disclosure. For example, the order of operations described herein is merely an example and is not limited to those orders set forth herein, but can be changed as becomes apparent after understanding the present disclosure, except for operations that must be performed in a specific order. In addition, for clarity and brevity, descriptions of features known in the art may be omitted.

[0044] The embodiments described in some embodiments of the present disclosure below do not represent all embodiments consistent with the present disclosure. Instead, they are merely examples of devices and methods consistent with some aspects of the present disclosure as detailed in the appended claims.

[0045] The service work order in the disclosed embodiment may be a service activation work order. For example, taking customer activation as an example, to activate the customer Internet dedicated line service accessed by GPON (Gigabit-capable Passive Optical Networks), network data configuration is required in the GPON transmission network and the metropolitan area network. If a card is generated when configuring the network side data of the metropolitan area network, the reason for the card may be that the SVLAN (Service Variable Length Subnet) + CVLAN (Customer VLAN) in the service activation form is occupied by other dedicated line services in the existing network, that is, the SVLAN + CVLAN resources in the service activation form conflict with the network side resources of the existing network. The network side data of the metropolitan area network is configured in the network configuration activation system, and the SVLAN + CVLAN resources are allocated in the integrated resource management system.

[0046] In current technology, the service activation form is stuck in the network configuration activation system. The card processing personnel need to log in to the network configuration activation system, confirm that the reason for the stuck form is that SVLAN+CVLAN conflicts with existing network resources in the network configuration activation system, manually close the network configuration activation system work order, and manually return to the integrated resource management system to reallocate SVLAN+CVLAN resources step by step (by flow link) in the service activation system. The automatic activation process of GPON customer Internet dedicated line service involves as many as 6 links: GPON network resource allocation (allocation of PON (Passive Optical Network) ports, ONU (Optical Network Unit) resources, etc.), metropolitan area network resource allocation (SVLAN+CVLAN, IP (Internet Protocol, the protocol for interconnection between networks) addresses, etc.), GPON network data configuration, metropolitan area network data configuration, on-site construction, and service commissioning. Among them, if a card order is automatically activated for a business, it is required to manually process, roll back step by step, manually reallocate resources and calibrate the comprehensive resource system resources. The average time for the card order processing personnel to manually process a card order is 35 minutes, which affects the efficiency of business activation and reduces the user experience.

[0047] Figure 1 is a flowchart of a method for processing a business work order according to some embodiments of the present disclosure, such as Figure 1 As shown, the method may include the following steps:

[0048] Step 101: Obtain an error log of a business work order, and determine an error code of the error log based on a target BERT model.

[0049] Among them, it should be noted that the executor of the above-mentioned business work order card order processing method is the business work order card order processing device, and the business work order card order processing device can be implemented by software and / or hardware. The business work order card order processing device in this embodiment can be configured in an electronic device.

[0050] In this example embodiment, the electronic device may include devices such as terminal devices and servers, and this embodiment does not limit the electronic device.

[0051] In the embodiment of the present disclosure, the above-mentioned service work order may be a service activation work order, wherein the error log of the service activation work order may be obtained through the relevant system and / or network equipment (such as a router or a switch) involved in the service activation work order.

[0052] In the disclosed embodiments, the related systems involved in the above-mentioned service activation work order may include a network configuration activation system, a service activation system and an integrated resource management system. Among them, the integrated resource management system is responsible for the reallocation of resources such as SVLAN+CVLAV, the service activation system is responsible for cross-system scheduling and work order process information adjustment, and the network configuration activation system is responsible for network-side instruction generation and issuance, collection and comparison of existing network resource information, and reverse analysis of the existing network resource information and return it to the service activation system, which will correct the information to the corresponding process link or system. For example, the error log is "The inner and outer VLANs to be configured have been used by other interfaces."

[0053] In the embodiment of the present disclosure, after obtaining the error log of the business work order through the above steps, the error code of the error log can be determined based on the target BERT model. The training method of the target BERT model may include the following steps:

[0054] Step 1: Obtain first training data, and perform data cleaning on the first training data to obtain second training data;

[0055] Step 2: label the second training data to obtain third training data;

[0056] Step 3: Based on the third training data, obtain a corresponding training data set and a verification data set;

[0057] Step 4: Train the initial BERT model based on the training data set to obtain a trained BERT model;

[0058] Step 5: Use the verification data set to verify the trained BERT model to obtain the target BERT model.

[0059] In the disclosed embodiment, historical error logs can be collected from network devices (such as routers, switches, servers) and systems, and the historical error logs can be determined as the first training data. The error logs include but are not limited to command line interface outputs, system log files, and alarm logs of network management software.

[0060] For example, in the embodiment of the present disclosure, the error log returned by the system is:

[0061] ① The inner and outer VLANs to be configured are already used by other interfaces;

[0062] ② The existing network lacks SVLAN information;

[0063] ③IP address is not bound to the work order to be deleted inner and outer VLAN;

[0064] ④Network element connection timeout;

[0065] ⑤The current device does not have an IP address to be deleted;

[0066] ⑥The VPN instance name to be adjusted is inconsistent with the VPN instance name of the device;

[0067] ⑦ The service sub-interface to be added already exists in the existing network;

[0068] For example, in the embodiment of the present disclosure, the error log returned by the network device is:

[0069] [~GDJIM-MS-IPMAN-BNG01-SNL-HW-Eth-Trunk1.10233000]qinq terminationpe-vid1023ce-vid 3000

[0070] Error:VLAN 3000QINQ 1023have been used by the other sub-interface.

[0071] [~GDJIM-MS-IPMAN-BNG01-SNL-HW-Eth-Trunk1.10233000]commit

[0072] [~GDJIM-MS-IPMAN-BNG01-SNL-HW-Eth-Trunk1.10233000]

[0073] Among them, in the embodiment of the present disclosure, the method of performing data cleaning on the above-mentioned first training data to obtain the second training data may include: performing log formatting and key information extraction on the first training data, and determining the extracted key information as the second training data.

[0074] In the disclosed embodiment, the collected first training data can be log formatted by text extraction or encoding conversion or timestamp standardization, so as to convert the first training data into a unified format for subsequent processing. Also, in the disclosed embodiment, tools such as regular expressions or custom scripts can be used to extract key information from the log formatted data, and the extracted key information can be determined as the second training data to eliminate unnecessary logs.

[0075] In the disclosed embodiment, after obtaining the second training data through the above steps, the second training data may be labeled to obtain the third training data. Before labeling the second training data, the error entity and error type may be defined.

[0076] In the embodiment of the present disclosure, the error entity definition may be a key entity that determines the normal operation of the network device, including but not limited to VLAN (virtual local area network), IP address, device manufacturer, VPN instance, and service interface; the error type definition may be an error type classified based on common network configuration problems, and the error type may include at least one of the following:

[0077] Existing network resource conflict: Network resources have been configured;

[0078] Lack of existing network resources: The core network configuration is missing in the network equipment;

[0079] Inconsistency between existing network resources: local stock resource information is inconsistent with the existing network equipment configuration;

[0080] Access issue: The device response timed out or the connection failed.

[0081] And, in the embodiment of the present disclosure, the second training data can be manually labeled based on the error entities and error types defined above to obtain the third training data, and based on the third training data, the corresponding training data set and verification data set can be obtained. Among them, the third training data can be divided into a training data set and a verification data set for training the initial BERT model according to a preset ratio. For example, assuming that the preset ratio is 7:3, that is, 70% of the data in the third training data is randomly divided into a training data set, and 30% of the data is divided into a verification data set.

[0082] Further, in the embodiment of the present disclosure, the method of training the initial BERT model based on the training data set to obtain the trained BERT model may include the following steps:

[0083] Step a: Input the data in the training dataset into the initial BERT model to obtain the predicted entity recognition results and error types;

[0084] Step b, inputting the predicted entity recognition result and error type and the actual entity recognition result and error type into the loss function to obtain the corresponding loss value;

[0085] Step c: Use the loss value to update the network parameters in the initial BERT model until the initial BERT model converges, or when the number of iterations of the network parameters reaches a preset number, a trained BERT model is obtained.

[0086] Among them, in the embodiment of the present disclosure, the above-mentioned BERT model and loss function are the same as those in the prior art, and the embodiment of the present disclosure will not be repeated here.

[0087] Furthermore, in the embodiment of the present disclosure, after the trained BERT model is obtained through the above steps, the trained BERT model is verified using the validation data set to obtain the accuracy performance of the trained BERT model on new samples and verify the generalization ability of the model. Then, according to the verification results of the validation data set, the trained BERT model is adjusted and optimized, for example, the network structure or hyperparameter settings are changed to improve the accuracy, robustness and performance of the model.

[0088] Further, in the embodiment of the present disclosure, after the target BERT model is obtained through the above steps, the error code of the error log can be determined based on the target BERT model. In the embodiment of the present disclosure, the method for determining the error code of the error log based on the target BERT model may include the steps of:

[0089] Step 1011: Input the error log into the target BERT model to obtain the entity recognition result and error type corresponding to the error log;

[0090] Step 1012: Obtain error information of the business work order;

[0091] Step 1013: Generate an error code for the error log using predefined rules based on the error information, entity recognition result, and error type.

[0092] For example, in the disclosed embodiment, assuming that the error log is "the inner and outer VLANs to be configured have been used by other interfaces", the error log is input into the target BERT model, and the entity recognition result obtained is: "VLAN entity", and the error type is "existing network resource conflict type".

[0093] Among them, in the embodiment of the present disclosure, the error information of the above-mentioned business work order may include the equipment manufacturer and the network element version.

[0094] And, in the embodiment of the present disclosure, the above-mentioned predefined rules may include predefined error content and predefined format. Among them, in the embodiment of the present disclosure, the above-mentioned method of generating error codes of error logs by predefined rules may include: generating error codes of error logs by predefined error content according to predefined format.

[0095] Among them, in the embodiment of the present disclosure, the above-mentioned predefined error content may include the abbreviation of the error occurrence system, the abbreviation of the error handling system, the equipment manufacturer, the network element version, the error entity and the error type, and the corresponding predefined format is "the abbreviation of the error occurrence system_the abbreviation of the error handling system_the equipment manufacturer_the network element version_the error entity_the error type".

[0096] Among them, in the embodiment of the present disclosure, the definition rule of "the abbreviation of the system where the error occurred" can be the English abbreviation of the system, for example, the English abbreviation of the service activation system is SG; the English abbreviation of the integrated resource management system is IRMS; the English abbreviation of the network configuration activation system is CAT.

[0097] In the disclosed embodiment, the definition rule of "error handling system abbreviation" can be defined according to the management system and the card order link. For example, if the card order occurs in the resource verification link of the network configuration activation system, the corresponding error handling system system abbreviation is IRMS; if the card order occurs in the resource issuance link and is handled by the network configuration activation system itself, the corresponding error handling system system abbreviation is CAT.

[0098] In the disclosed embodiment, the above-mentioned "equipment manufacturer" and "network element version" are obtained from the error information of the business work order. For example, device A is HW, and the version information is V600; the definition rule of "error entity" can be: VLAN (virtual local area network) = 1, IP address = 2, equipment manufacturer = 3, VPN instance = 4, service interface = 5, and so on; the definition rule of "error type" can be: existing network resource conflict = a, existing network resource missing = b, existing network resource inconsistency = c; access problem = d.

[0099] For example, in the disclosed embodiment, it is assumed that the error log is "the inner and outer VLANs to be configured have been used by other interfaces", the entity recognition result obtained by the target BERT model is "VLAN entity", the error type is "existing network resource conflict type", and the error code of the error log is determined by the above predefined rules to be "CAT_IRMS_HW_V600_1_a".

[0100] Step 102: Based on the error code, obtain a corresponding abnormality diagnosis result.

[0101] In the disclosed embodiment, after the error code is obtained through the above steps, an abnormality diagnosis can be performed based on the error code to obtain a corresponding abnormality diagnosis result.

[0102] Specifically, in the embodiment of the present disclosure, the method for obtaining the corresponding abnormal diagnosis result based on the error code may include the following steps:

[0103] Step 1021: Based on the error code, obtain an exception information set of the error code through a mapping relationship between the error code and the exception information.

[0104] Step 1022: Perform an abnormality diagnosis on the abnormal information in the abnormal information set to obtain a corresponding abnormality diagnosis result.

[0105] In the embodiment of the present disclosure, the mapping relationship between the error code and the abnormal information can be one error code corresponding to one or more abnormal information. Based on this, the abnormal information set of the error code can be obtained through the mapping relationship between the error code and the abnormal information. For example, the abnormal information set corresponding to the error code is {vlan conflict, network cable is not connected, network card is damaged, data configuration error (PON port error)}.

[0106] Furthermore, in the embodiment of the present disclosure, the above-mentioned abnormal information set is a set of abnormal information that may appear in the error coding. Based on this, it is necessary to perform abnormal diagnosis on the abnormal information in the abnormal information set to obtain an accurate abnormal diagnosis result corresponding to the error coding.

[0107] Specifically, in an embodiment of the present disclosure, the above-mentioned method of performing abnormal diagnosis on abnormal information in an abnormal information set to obtain corresponding abnormal diagnosis results may include: determining a diagnosis rule corresponding to each type of abnormal information in the abnormal information set, and performing abnormal diagnosis based on the diagnosis rule and the corresponding abnormal information to obtain a corresponding abnormal diagnosis result.

[0108] Among them, in the embodiment of the present disclosure, the diagnostic rules of the above-mentioned abnormal information may include one or more of data collection, information comparison, resource verification, and automatic parameter allocation, and the embodiment of the present disclosure does not limit this.

[0109] Step 103: Determine the corresponding error correction task based on the error code and the abnormality diagnosis result.

[0110] In the disclosed embodiment, after the error code and the abnormal diagnosis result are obtained through the above steps, the corresponding error correction task can be determined based on the error code and the abnormal diagnosis result.

[0111] Specifically, in the embodiment of the present disclosure, the method for determining the corresponding error correction task based on the error code and the abnormality diagnosis result may include the following steps:

[0112] Step 1031: Based on the error code and abnormal diagnosis results, the corresponding error correction rules are determined through the intelligent error correction service directory.

[0113] Step 1032: Determine the corresponding error correction task based on the error correction rule.

[0114] In the embodiments of the present disclosure, the same abnormal diagnosis result has different error correction rules for different activated services or different devices. Therefore, the embodiments of the present disclosure propose an intelligent error correction service directory that supports storing error correction rules in a custom directory hierarchy, that is, the intelligent error correction service directory includes error codes and the routing relationship between abnormal diagnosis results and error correction rules. Based on this, after determining the abnormal diagnosis result, the corresponding error correction rules can be routed in the intelligent error correction service directory based on the error code (such as the equipment manufacturer or network element version) and the abnormal diagnosis result to achieve accurate error correction.

[0115] In the embodiment of the present disclosure, based on the directory level in the intelligent error correction service directory, the corresponding error correction rules can be obtained by determining layer by layer in the intelligent error correction service directory according to the error code and the abnormal diagnosis result. The error correction rule can be an error correction strategy, and the error correction rule is exemplified as a "CVLAN correction strategy".

[0116] And, in the embodiment of the present disclosure, after the error correction rule is obtained through the above steps, the error correction task of completing the error correction rule can be determined based on the error correction rule. In the embodiment of the present disclosure, the error correction task corresponding to the error correction rule can be determined based on the mapping relationship between the error correction rule and the error correction task, wherein the error correction task includes executing the error correction system and the corresponding error correction operation.

[0117] Step 104: Based on the error correction task, perform error correction on the business work order.

[0118] In the embodiment of the present disclosure, after obtaining the error correction task through the above steps, the error correction operation in the error correction task can be sent to the error correction execution system in the error correction task, and the error correction execution system executes the error correction operation to perform card order error correction processing on the business work order to complete the card order self-healing processing.

[0119] Among them, in one embodiment of the present disclosure, during the error correction process, it may be necessary to perform linked error correction between systems. At this time, after any system in the linked error correction receives the error code and error correction information sent by other systems, it can perform error correction based on the error code, error correction information and pre-set error correction operations, and automatically send the error correction information obtained after the execution to the next configured system to complete the linked error correction between systems.

[0120] In addition, in another embodiment of the present disclosure, during the error correction process, it may be necessary to perform linked error correction between systems. In this case, after the system performs error correction based on the received error code and error correction information, it can receive the error correction results and / or correction information sent by the system, and send the error correction results and / or correction information to other systems that need to be linked, so that the other systems can perform linked error correction based on the received error correction results and / or correction information.

[0121] Based on the above description, the embodiment of the present disclosure illustrates the card ticket processing method of the above-mentioned business work order.

[0122] For example, in the embodiment of the present disclosure, the card order processing method of the above-mentioned service work order may include: obtaining the error log "Error: VLAN 3000QINQ 1023have been used by the network configuration activation system" sent by the network configuration activation system. othersub-interface."; Based on the target BERT model, determine that the entity recognition result corresponding to the error log is "VLAN entity", and the error type is "existing network resource conflict type"; Based on the error information, entity recognition result and error type of the business work order, determine the error code of the error log as "CAT_IRMS_HW_V600_1_a" through predefined rules; According to the error code, determine the corresponding abnormal information set as {single-layer VLAN conflict, double-layer VLAN conflict}, and the diagnosis rule corresponding to each type of abnormal information; Based on the diagnosis rule, perform abnormal diagnosis on the abnormal information, and obtain the abnormal diagnosis result of "double-layer VLAN conflict, there is an available CVLAN under SVLAN"; Based on the error code "CAT_IRMS_HW_V600_1_a" and the abnormal diagnosis result "double-layer VLAN conflict, there is an available CVLAN under SVLAN", the corresponding error correction rule is obtained through the intelligent error correction service directory as "CVLAN correction strategy"; Determine the error correction execution script and execution error correction system based on the error correction rule The network configuration activation system is a "network configuration activation system"; the error correction execution script is sent to the network configuration activation system. Based on the error correction execution script, the network configuration activation system sends the error code [CAT_IRMS_HW_V600_1_a] and the CVLAN available in the existing network to the service provisioning system to initiate inter-system linkage error correction; the service provisioning system receives the error code [CAT_IRMS_HW_V600_1_a], automatically rolls back the work order link to the resource configuration link, and sends the error code [CAT_IRMS_HW_V600_1_a] and the CVLAN available in the existing network to the integrated resource management system; the integrated resource management system receives the error code [CAT_IRMS_HW_V600_1_a] and the CVLAN available in the existing network, and reallocates the CVLAN; the integrated resource management system automatically returns the error correction result and the newly allocated CVLAN information to the service provisioning system; the service provisioning system returns the correct information to the network configuration activation system, and the network configuration activation completes the modification of the existing network configuration. Finally, the multi-system linkage error correction completes the card single self-healing closed loop.

[0123] It should be noted that in the embodiment of the present disclosure, based on the card order processing method of the service activation work order with the above error coding, the service card order of "VLAN conflict" can be automatically processed within 15 seconds. Before the above method is adopted, manual intervention is required to process the service card order of "VLAN conflict", which takes 35 minutes. Based on this, the present disclosure improves the processing efficiency of the service card order of "VLAN conflict" by 139 times, greatly improving the processing efficiency of the automatic activation card order of mobile communication services.

[0124] And, in the embodiment of the present disclosure, Table 1 is a table of conflict scenarios for mobile service activation.

[0125] Table 1

[0126]

[0127]

[0128] The present disclosure proposes a card order processing method for a business work order, which includes obtaining an error log of the business work order, and determining the error code of the error log based on a target BERT model; obtaining a corresponding abnormal diagnosis result based on the error code; determining a corresponding error correction task based on the error code and the abnormal diagnosis result; and performing card order error correction processing on the business work order based on the error correction task. Thus, the present disclosure can determine the error correction task through the error code, and automatically complete the card order self-healing processing based on the error correction task, without the need for manual intervention, thereby reducing costs, improving the processing efficiency of mobile communication service activation card orders, and further improving user experience.

[0129] Figure 2 A card order processing device for a business work order is shown according to some embodiments of the present disclosure, such as Figure 2 As shown, the device may include:

[0130] The error code management module 201 is used to obtain the error log of the business work order and determine the error code of the error log based on the target BERT model;

[0131] The abnormality diagnosis module 202 is used to obtain the corresponding abnormality diagnosis result based on the error code;

[0132] Intelligent error correction module 203, used to determine the corresponding error correction task based on the error code and abnormal diagnosis result;

[0133] The intelligent error correction module 203 is also used to perform error correction processing on the business work order based on the error correction task.

[0134] In the embodiment of the present disclosure, the error code management module 201 is specifically used to:

[0135] Input the error log into the target BERT model to obtain the entity recognition result and error type corresponding to the error log;

[0136] Get error information of business work orders;

[0137] Based on the error information, entity recognition results and error type, the error code of the error log is generated through predefined rules.

[0138] Optionally, in the embodiment of the present disclosure, the above error type includes at least one of the following:

[0139] Current network resource conflicts;

[0140] Lack of existing network resources;

[0141] Existing network resources are inconsistent;

[0142] Access issues.

[0143] Optionally, in an embodiment of the present disclosure, the predefined rules include predefined error content and a predefined format; the error code management module 201 is further used to generate an error code of the error log according to the predefined error content and the predefined format.

[0144] Optionally, in the embodiment of the present disclosure, the above-mentioned abnormality diagnosis module 202 is specifically used to:

[0145] Based on the error code, the exception information set of the error code is obtained through the mapping relationship between the error code and the exception information;

[0146] Anomaly diagnosis is performed on the abnormal information in the abnormal information set to obtain corresponding abnormality diagnosis results.

[0147] Optionally, in the embodiment of the present disclosure, the intelligent error correction module 203 is specifically used to:

[0148] Based on the error code and the abnormal diagnosis result, the corresponding error correction rule is determined through the intelligent error correction service directory, wherein the intelligent error correction service directory includes the routing relationship between the error code and the abnormal diagnosis result and the error correction rule;

[0149] Based on the error correction rules, the corresponding error correction tasks are determined.

[0150] Figure 3 is a schematic diagram showing the interaction between a card order processing device for a business work order and a related system according to some embodiments of the present disclosure, such as Figure 3As shown, the relevant systems involved in the business activation work order may include a network configuration activation system, a service activation system and an integrated resource management system, wherein the network configuration activation system, the service activation system and the integrated resource management system can send the error log of the card order to the card order processing device of the business work order, the card order processing device of the business work order generates an error code through the error code management module, generates an error correction task through the intelligent error correction module, and sends the error code and the error correction task to the system related to the error correction task, and after receiving the error correction result and / or correction information sent by the system, the error correction result and / or correction information can also be sent to the system that needs to be corrected later, so as to realize inter-system linkage error correction and complete the card order self-healing processing.

[0151] In one or more embodiments of the present disclosure, the error log of the service work order is obtained, and the error code of the error log is determined based on the target BERT model; an abnormal diagnosis is performed based on the error code to obtain the corresponding abnormal diagnosis result; the corresponding error correction task is determined based on the error code and the abnormal diagnosis result; the service work order is corrected based on the error correction task to complete the card self-healing process. Therefore, the present disclosure can determine the error correction task by error code, and automatically complete the card self-healing process based on the error correction task, without manual intervention, thereby reducing costs, improving the processing efficiency of mobile communication service activation card orders, and further improving user experience.

[0152] like Figure 4 As shown, the electronic device 400 includes a computing unit 401, which can perform various appropriate actions and processes according to a computer program stored in a read-only memory (ROM) 402 or a computer program loaded from a storage unit 408 into a random access memory (RAM) 404. In RAM 403, various programs and data required for the operation of the electronic device 400 can also be stored. The computing unit 401, ROM 402 and RAM 403 are connected to each other via a bus 404. An input / output (I / O) interface 405 is also connected to the bus 404.

[0153] A number of components in the electronic device 400 are connected to the I / O interface 405, including: an input unit 408, such as a keyboard, a mouse, etc.; an output unit 407, such as various types of displays, speakers, etc.; a storage unit 408, such as a disk, an optical disk, etc.; and a communication unit 409, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 409 allows the electronic device 400 to exchange information / data with other electronic devices through a computer network such as the Internet and / or various telecommunication networks.

[0154] The computing unit 401 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the computing unit 401 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, digital signal processors (DSPs), and any appropriate processors, controllers, microcontrollers, etc. The computing unit 401 performs the various methods and processes described above, such as a card order processing method for a business work order. For example, in some embodiments, the card order processing method for a business work order may be implemented as a computer software program, which is tangibly contained in a machine-readable medium, such as a storage unit 408. In some embodiments, part or all of the computer program may be loaded and / or installed on the electronic device 400 via the ROM 402 and / or the communication unit 409. When the computer program is loaded into the RAM 403 and executed by the computing unit 401, one or more steps of the card order processing method for the business work order described above may be executed. Alternatively, in other embodiments, the computing unit 401 may be configured to execute a card order processing method for a business work order in any other appropriate manner (eg, by means of firmware).

[0155] Various embodiments of the devices and techniques described above herein can be implemented in digital electronic circuit devices, integrated circuit devices, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), devices on a chip (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable device including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage device, at least one input device, and at least one output device, and transmit data and instructions to the storage device, the at least one input device, and the at least one output device.

[0156] The program code for implementing the method of the present disclosure may be written in any combination of one or more programming languages. These program codes may be provided to a processor or controller of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that the program code, when executed by the processor or controller, enables the functions / operations specified in the flow chart and / or block diagram to be implemented. The program code may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.

[0157] In the context of the present disclosure, a machine-readable medium may be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution device, device, or electronic device. A machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor devices, devices, or electronic devices, or any suitable combination of the foregoing. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage electronic device, a magnetic storage electronic device, or any suitable combination of the foregoing.

[0158] To provide interaction with a user, the devices and techniques described herein can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or trackball) through which the user can provide input to the computer. Other types of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0159] The apparatus and techniques described herein may be implemented in a computing device including backend components (e.g., as a data server), or a computing device including middleware components (e.g., an application server), or a computing device including frontend components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the apparatus and techniques described herein), or a computing device including any combination of such backend components, middleware components, or frontend components. The components of the apparatus may be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), the Internet, and a blockchain network.

[0160] A computer device may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The relationship between the client and the server is generated by computer programs running on the corresponding computers and having a client-server relationship with each other. The server may be a cloud server, also known as a cloud computing server or a cloud host, which is a host product in the cloud computing service system to solve the defects of difficult management and weak business scalability in traditional physical hosts and VPS services ("Virtual Private Server", or "VPS" for short). The server may also be a server of a distributed device, or a server combined with a blockchain.

[0161] It should be understood that the various forms of processes shown above can be used to reorder, add or delete steps. For example, the steps recorded in this disclosure can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solutions disclosed in this disclosure can be achieved, and this document does not limit this.

[0162] The above specific implementations do not constitute a limitation on the protection scope of the present disclosure. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present disclosure shall be included in the protection scope of the present disclosure.

Claims

1. A method for processing a business work order, characterized in that: The method comprises: Obtain an error log of the business work order, and determine an error code of the error log based on a target BERT model; Based on the error code, a corresponding abnormality diagnosis result is obtained; Based on the error code and the abnormal diagnosis result, determining a corresponding error correction task; Based on the error correction task, the business work order is subjected to error correction processing.

2. The method according to claim 1, characterized in that The determining the error code of the error log based on the target BERT model includes: Input the error log into the target BERT model to obtain the entity recognition result and error type corresponding to the error log; Obtain error information of the business work order; Based on the error information, the entity recognition result and the error type, an error code of the error log is generated by a predefined rule.

3. The method according to claim 2, characterized in that The error type includes at least one of the following: Current network resource conflicts; Lack of existing network resources; Existing network resources are inconsistent; Access issues.

4. The method according to claim 2, characterized in that The predefined rules include predefined error content and a predefined format; and the generating the error code of the error log according to the predefined rules includes: generating the error code of the error log according to the predefined error content and the predefined format.

5. The method according to claim 1, characterized in that The abnormality diagnosis based on the error code is performed to obtain the corresponding abnormality diagnosis result, including: Based on the error code, obtaining an exception information set of the error code through a mapping relationship between the error code and the exception information; An abnormality diagnosis is performed on the abnormal information in the abnormal information set to obtain a corresponding abnormality diagnosis result.

6. The method according to claim 1, characterized in that The determining a corresponding error correction task based on the error code and the abnormal diagnosis result includes: Based on the error code and the abnormal diagnosis result, determine the corresponding error correction rule through the intelligent error correction service catalog, wherein the intelligent error correction service catalog includes the routing relationship between the error code and the abnormal diagnosis result and the error correction rule; Based on the error correction rule, a corresponding error correction task is determined.

7. A card order processing device for a business work order, characterized in that: The device comprises: An error code management module, used to obtain an error log of a business work order and determine an error code of the error log based on a target BERT model; An abnormality diagnosis module, used for obtaining a corresponding abnormality diagnosis result based on the error code; An intelligent error correction module, used to determine a corresponding error correction task based on the error code and the abnormality diagnosis result; The intelligent error correction module is also used to perform card error correction processing on the business work order based on the error correction task.

8. The device according to claim 7, characterized in that The error coding management module is specifically used for: Input the error log into the target BERT model to obtain the entity recognition result and error type corresponding to the error log; Obtain error information of the business work order; Based on the error information, the entity recognition result and the error type, an error code of the error log is generated by a predefined rule.

9. A computer program product, comprising a computer program, wherein when the computer program is executed by a processor, the method according to any one of claims 1 to 6 is implemented.

10. A non-transitory computer-readable storage medium, wherein the computer storage medium stores computer-executable instructions; after the computer-executable instructions are executed by a processor, the method according to any one of claims 1 to 6 can be implemented.

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