Work order problem backtracking method and system, electronic equipment and storage medium
By automatically analyzing work orders using the work order classification model and problem description generation model, the problem that complaint handlers need to manually analyze and trace work orders is solved, and the automatic processing of work order problem backtracking is realized, reducing costs and improving analysis accuracy.
Patent Information
- Application Number
- CN202411483414.4
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-10-23
- Publication Date
- 2025-03-04
AI Technical Summary
In the prior art, complaint handlers need to manually analyze and trace the work order, which leads to time-consuming, high cost, repetitive work and susceptible to subjective influence.
By receiving information about pending work orders, using the trained work order classification model and problem description generation model, automatically determine the work order category and problem description information, generate a work order report and send it to the target terminal for problem repair.
It realizes automated processing of work order problem backtracking, reduces labor costs, and improves the accuracy of data analysis.
Smart Images
Figure CN119558512A_ABST
Abstract
Description
Background Art
[0002] At present, front-line complaint handling personnel need to analyze all received complaint tickets one by one every day, label and classify the tickets, summarize the contents of the tickets to form a problem description, and then feedback to the developers for program optimization. After the program is optimized, it is traced back to the front-line personnel. The front-line personnel confirm whether the problem has been solved based on the complaint analysis and track the program optimization effect. This process of manual data analysis is time-consuming, occupies a lot of labor costs, and the work content is repetitive and boring, and it is easily affected by people's subjective consciousness.
[0003] Therefore, it is urgent to provide a technical solution to solve the above problems. Summary of the invention
[0004] In order to solve the above technical problems, the present invention provides a work order problem backtracking method, system, electronic device and storage medium.
[0005] In a first aspect, the present invention provides a work order problem backtracking method, and the technical solution of the method is as follows:
[0006] Receive work order information of pending work orders;
[0007] Based on the work order information, determine the work order category and problem description information of the work order to be processed.
[0008] The beneficial effects of a work order problem backtracking method of the present invention are as follows:
[0009] The method of the present invention can realize the automated processing of work order problem backtracking, reduce labor costs, and improve data analysis accuracy.
[0010] On the basis of the above scheme, a work order problem backtracking method of the present invention can also be improved as follows.
[0011] In an optional manner, the step of determining the work order category of the to-be-processed work order based on the work order information includes:
[0012] The work order information is input into a trained work order classification model to obtain the work order category of the work order to be processed.
[0013] In an optional manner, the step of determining the problem description information of the to-be-processed work order based on the work order information includes:
[0014] The work order information is input into a trained problem description generation model to obtain the problem description information of the work order to be processed.
[0015] In an optional manner, the method further includes:
[0016] Generate work order report information including the work order category and problem description information of the work order to be processed, and send the work order report information to the target terminal for problem repair.
[0017] In an optional manner, the method further includes:
[0018] Based on the work order report information and problem repair evaluation information within a preset time period, the work order classification model and problem description generation model are optimized.
[0019] In a second aspect, the present invention provides a work order problem backtracking system, and the technical solution of the system is as follows:
[0020] Including: receiving module and backtracking module;
[0021] The receiving module is used to: receive work order information of the work order to be processed;
[0022] The backtracking module is used to determine the work order category and problem description information of the work order to be processed based on the work order information.
[0023] The beneficial effects of a work order problem backtracking system of the present invention are as follows:
[0024] The system of the present invention can realize the automated processing of work order problem backtracking, reduce labor costs, and improve data analysis accuracy.
[0025] Based on the above solution, the work order problem backtracking system of the present invention can also be improved as follows.
[0026] In an optional manner, the backtracking module is specifically used to:
[0027] The work order information is input into a trained work order classification model to obtain the work order category of the work order to be processed.
[0028] In an optional manner, the backtracking module is specifically used to:
[0029] The work order information is input into a trained problem description generation model to obtain the problem description information of the work order to be processed.
[0030] In a third aspect, a technical solution of an electronic device of the present invention is as follows:
[0031] The method comprises a memory, a processor and a program stored in the memory and running on the processor. When the processor executes the program, the steps of the work order problem backtracking method of the present invention are implemented.
[0032] In a fourth aspect, the present invention provides a computer-readable storage medium having the following technical solution:
[0033] Instructions are stored in the computer-readable storage medium. When the computer-readable storage medium reads the instructions, the computer-readable storage medium executes the steps of the work order problem backtracking method of the present invention.
[0034] The above description is only an overview of the technical solution of the present invention. In order to more clearly understand the technical means of the present invention, it can be implemented according to the contents of the specification. In order to make the above and other purposes, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are listed below. BRIEF DESCRIPTION OF THE DRAWINGS
[0035] The accompanying drawings are only used to illustrate the embodiments and are not to be considered as limiting the present invention. In addition, the same reference symbols are used to represent the same components throughout the accompanying drawings. In the accompanying drawings:
[0036] Figure 1 A schematic diagram of a flow chart of an embodiment of a work order problem backtracking method of the present invention;
[0037] Figure 2 This is one of the principle diagrams of the work order classification model;
[0038] Figure 3 This is the second schematic diagram of the principle of the work order classification model;
[0039] Figure 4 A schematic diagram of the principles of the model generated for the problem description;
[0040] Figure 5 It is a structural schematic diagram of an embodiment of a work order problem backtracking system of the present invention;
[0041] Figure 6 The figure is a schematic structural diagram of an embodiment of an electronic device of the present invention. DETAILED DESCRIPTION
[0042] Exemplary embodiments of the present invention will be described in more detail below with reference to the accompanying drawings. Although exemplary embodiments of the present invention are shown in the drawings, it should be understood that the present invention can be implemented in various forms and should not be limited to the embodiments set forth herein.
[0043] Figure 1A flow chart of an embodiment of a work order problem backtracking method provided by the present invention is shown, and the work order problem backtracking method can be executed by an electronic device such as a terminal device or a server. The terminal device can be any fixed or mobile terminal such as a user equipment (UE), a mobile device, a user terminal, a terminal, a cellular phone, a cordless phone, a personal digital assistant (PDA), a handheld device, a computing device, a vehicle-mounted device, a wearable device, etc. The server can be a single server or a server cluster composed of multiple servers. Any electronic device can implement the work order problem backtracking method by means of a processor calling computer-readable instructions stored in a memory. Figure 1 As shown, the following steps are included:
[0044] S1. Receive work order information of work orders to be processed.
[0045] Among them, the pending work order is the complaint operation order that needs to be processed in this embodiment. The pending work order can be received and obtained through the inverted triangle service, BOMC (Business Operation Management Center) and online customer service. The work order information is text information containing content related to the work order, which can also be determined according to actual conditions and is not limited here.
[0046] S2. Based on the work order information, determine the work order category and problem description information of the work order to be processed.
[0047] In S2, specifically:
[0048] 1) Based on the work order information, the step of determining the work order category of the work order to be processed comprises:
[0049] The work order information is input into a trained work order classification model to obtain the work order category of the work order to be processed.
[0050] Among them, the work order classification model is a work order classifier. The work order category is determined according to the business type, such as "system defect". Before the work order information is input into the model, data cleaning and word segmentation processing are required. The word libraries involved in word segmentation processing include but are not limited to: professional word library, stammering general word library, professional stop word library and stammering general stop word library. Figure 2 As shown in Figure 1, during the training process of the work order classification model: first, the work order information is manually classified and labeled to obtain labeled samples; second, the labeled samples are cleaned and segmented, and a training sample set and a training test set are constructed; then, the training sample set and the training test set are used to train and tune the work order classification model; Figure 3 As shown, finally, the trained work order classification model is used to identify the work order category of the work order to be processed.
[0051] 2) Based on the work order information, the step of determining the problem description information of the work order to be processed includes:
[0052] The work order information is input into a trained problem description generation model to obtain the problem description information of the work order to be processed.
[0053] The problem description generation model is a problem description generator. The problem description information is determined according to the business type, such as: "The user has completed the customer information service, but is still in the state of not registering with real name." Figure 4 The schematic diagram of the problem description generation model is shown. First, the work order information is cleaned and split to obtain multiple sentences; second, the sentences are represented by vectorization, and the similarity matrix between multiple vectors is calculated; then, the graph structure is constructed according to the similarity matrix to obtain a node connection graph; finally, the TextRank value of each sentence is calculated according to the node connection graph, and the sentence with the highest TextRank value is determined as the problem description information of the work order to be processed.
[0054] In an optional manner, the method further includes:
[0055] Generate work order report information including the work order category and problem description information of the work order to be processed, and send the work order report information to the target terminal for problem repair.
[0056] The work order report information includes the work order category and problem description information of the work order to be processed. The target terminal is the terminal device of the operator. When the operator receives the work order report information through the target terminal, the complaint is moved forward for the corresponding problem, the defect is optimized, and the repair status is synchronized.
[0057] In an optional manner, the method further includes:
[0058] Based on the work order report information and problem repair evaluation information within a preset time period, the work order classification model and problem description generation model are optimized.
[0059] The preset time period can be set according to actual needs, such as one week, which is not limited here. Problem repair evaluation information refers to whether the same or similar problems still exist in the relevant business type (work order category) after the problem involved in the problem description information output by the model is repaired. If so, it means that the work order classification model and the problem description generation model need to be further optimized. If not, it means that the work order classification model and the problem description generation model do not need to be optimized in the short term.
[0060] The technical solution of this embodiment can realize the automated processing of work order problem backtracking, reduce labor costs, and improve data analysis accuracy.
[0061] Figure 5 FIG. 2 is a schematic diagram showing a structure of an embodiment of a work order problem tracing system 200 provided by the present invention. Figure 5 As shown, the system 200 includes: a receiving module 210 and a backtracking module 220;
[0062] The receiving module 210 is used to receive work order information of a work order to be processed.
[0063] Among them, the pending work order is the complaint operation order that needs to be processed in this embodiment. The pending work order can be received and obtained through the inverted triangle service, BOMC (Business Operation Management Center) and online customer service. The work order information is text information containing content related to the work order, which can also be determined according to actual conditions and is not limited here.
[0064] The backtracking module 220 is used to determine the work order category and problem description information of the work order to be processed based on the work order information.
[0065] The backtracking module 220 is specifically used for:
[0066] 1) Inputting the work order information into a trained work order classification model to obtain the work order category of the work order to be processed.
[0067] Among them, the work order classification model is a work order classifier. The work order category is determined according to the business type, such as "system defect". Before the work order information is input into the model, data cleaning and word segmentation processing are required. The word libraries involved in word segmentation processing include but are not limited to: professional word library, stammering general word library, professional stop word library and stammering general stop word library. Figure 2 As shown in Figure 1, during the training process of the work order classification model: first, the work order information is manually classified and labeled to obtain labeled samples; second, the labeled samples are cleaned and segmented, and a training sample set and a training test set are constructed; then, the training sample set and the training test set are used to train and tune the work order classification model; Figure 3 As shown, finally, the trained work order classification model is used to identify the work order category of the work order to be processed.
[0068] 2) Inputting the work order information into the trained problem description generation model to obtain the problem description information of the work order to be processed.
[0069] The problem description generation model is a problem description generator. The problem description information is determined according to the business type, such as: "The user has completed the customer information service, but is still in the state of not registering with real name." Figure 4The schematic diagram of the problem description generation model is shown. First, the work order information is cleaned and split to obtain multiple sentences; second, the sentences are represented by vectorization, and the similarity matrix between multiple vectors is calculated; then, the graph structure is constructed according to the similarity matrix to obtain a node connection graph; finally, the TextRank value of each sentence is calculated according to the node connection graph, and the sentence with the highest TextRank value is determined as the problem description information of the work order to be processed.
[0070] In an optional manner, the method further includes: a repair module; the repair module is used to:
[0071] Generate work order report information including the work order category and problem description information of the work order to be processed, and send the work order report information to the target terminal for problem repair.
[0072] The work order report information includes the work order category and problem description information of the work order to be processed. The target terminal is the terminal device of the operator. When the operator receives the work order report information through the target terminal, the complaint is moved forward for the corresponding problem, the defect is optimized, and the repair status is synchronized.
[0073] In an optional manner, the method further includes: an optimization module; the optimization module is used to:
[0074] Based on the work order report information and problem repair evaluation information within a preset time period, the work order classification model and problem description generation model are optimized.
[0075] The preset time period can be set according to actual needs, such as one week, which is not limited here. Problem repair evaluation information refers to whether the same or similar problems still exist in the relevant business type (work order category) after the problem involved in the problem description information output by the model is repaired. If so, it means that the work order classification model and the problem description generation model need to be further optimized. If not, it means that the work order classification model and the problem description generation model do not need to be optimized in the short term.
[0076] The technical solution of this embodiment can realize the automated processing of work order problem backtracking, reduce labor costs, and improve data analysis accuracy.
[0077] like Figure 6 As shown, an electronic device 300 according to an embodiment of the present invention includes a processor 320, the processor 320 is coupled to a memory 310, and the memory 310 stores at least one computer program 330, and the at least one computer program 330 is loaded and executed by the processor 320, so that the electronic device 300 implements any of the above-mentioned work order problem backtracking methods, specifically:
[0078] The electronic device 300 may have relatively large differences due to different configurations or performances, and may include one or more processors 320 (Central Processing Units, CPU) and one or more memories 310, wherein the one or more memories 310 store at least one computer program 330, and the at least one computer program 330 is loaded and executed by the one or more processors 320, so that the electronic device 300 implements any of the work order problem backtracking methods provided in the above embodiments. Of course, the electronic device 300 may also have components such as a wired or wireless network interface, a keyboard, and an input and output interface for input and output, and the electronic device 300 may also include other components for implementing device functions, which will not be described in detail here.
[0079] A computer-readable storage medium according to an embodiment of the present invention stores at least one computer program, and the at least one computer program is loaded and executed by a processor so that a computer implements any of the above-mentioned work order problem backtracking methods.
[0080] Optionally, the computer-readable storage medium may be a read-only memory (ROM), a random access memory (RAM), a compact disc (CD-ROM), a magnetic tape, a floppy disk, an optical data storage device, and the like.
[0081] In an exemplary embodiment, a computer program product or a computer program is also provided, the computer program product or the computer program comprising computer instructions, the computer instructions being stored in a computer-readable storage medium. A processor of an electronic device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, so that the electronic device executes any of the above-mentioned work order problem backtracking methods.
[0082] It should be noted that the terms "first", "second", etc. in the specification and claims of the present application are used to distinguish similar objects and represent the definition of a specific order or sequence. The order of use of similar objects can be interchanged where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than the order shown or described.
[0083] Those skilled in the art know that the present invention can be implemented as a system, method or computer program product. Therefore, the present disclosure can be specifically implemented in the following forms, namely: it can be complete hardware, it can be complete software (including firmware, resident software, microcode, etc.), or it can be a combination of hardware and software, which is generally referred to as "circuit", "module" or "system" herein. In addition, in some embodiments, the present invention can also be implemented in the form of a computer program product in one or more computer-readable media, and the computer-readable medium contains computer-readable program code.
[0084] Any combination of one or more computer-readable media may be used. A computer-readable medium may be a computer-readable signal medium or a computer-readable storage medium. A computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or device, or any combination thereof. More specific examples (a non-exhaustive list) of computer-readable storage media include: an electrical connection with one or more wires, 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 device, a magnetic storage device, or any suitable combination thereof. In the present application, a computer-readable storage medium may be any tangible medium containing or storing a program that may be used by or in conjunction with an instruction execution system, device, or device.
[0085] Although the embodiments of the present invention have been shown and described above, it is to be understood that the above embodiments are exemplary and are not to be construed as limitations of the present invention. A person skilled in the art may change, modify, replace and vary the above embodiments within the scope of the present invention.
Claims
1. A work order problem backtracking method, characterized in that: include: Receive work order information of pending work orders; Based on the work order information, determine the work order category and problem description information of the work order to be processed.
2. The work order problem backtracking method according to claim 1 is characterized in that: The step of determining the work order category of the to-be-processed work order based on the work order information includes: The work order information is input into a trained work order classification model to obtain the work order category of the work order to be processed.
3. The work order problem backtracking method according to claim 1 is characterized in that: The step of determining the problem description information of the to-be-processed work order based on the work order information includes: The work order information is input into a trained problem description generation model to obtain the problem description information of the work order to be processed.
4. The work order problem backtracking method according to any one of claims 1 to 3, characterized in that: Also includes: Generate work order report information including the work order category and problem description information of the work order to be processed, and send the work order report information to the target terminal for problem repair.
5. The work order problem backtracking method according to claim 4 is characterized in that: Also includes: Based on the work order report information and problem repair evaluation information within a preset time period, the work order classification model and problem description generation model are optimized.
6. A work order problem backtracking system, characterized in that: include: Receiving module and backtracking module; The receiving module is used to: receive work order information of the work order to be processed; The backtracking module is used to determine the work order category and problem description information of the work order to be processed based on the work order information.
7. The work order problem tracing system according to claim 6, characterized in that: The backtracking module is specifically used for: The work order information is input into a trained work order classification model to obtain the work order category of the work order to be processed.
8. The work order problem tracing system according to claim 6, characterized in that: The backtracking module is specifically used for: The work order information is input into a trained problem description generation model to obtain the problem description information of the work order to be processed.
9. An electronic device, characterized in that: The electronic device includes a processor, the processor is coupled to a memory, the memory stores at least one computer program, and the at least one computer program is loaded and executed by the processor so that the electronic device implements the work order problem backtracking method as described in any one of claims 1 to 5.
10. A computer-readable storage medium, characterized in that: At least one computer program is stored in the computer-readable storage medium, and the at least one computer program is loaded and executed by the processor, so that the computer-readable storage medium implements the work order problem backtracking method according to any one of claims 1 to 5.