Work order generation method, device and equipment, medium and product

Abstract

The invention discloses a work order generation method and device, equipment, a medium and a product, and relates to the technical field of artificial intelligence. The method comprises the following steps: receiving a creation triggering operation of a service work order, and obtaining voice data in a process of serving a user; performing intention recognition on the voice data to obtain a corresponding service intention and a key data set; screening out a target work order template from a plurality of preset work order templates based on the business intention; and performing content filling on the target work order template based on the key data set to obtain a service work order corresponding to the voice data. According to the technical scheme provided by the invention, the work order establishment efficiency in customer service can be improved, the service work order is automatically generated, and the working efficiency of a manual service agent and the service experience feeling of a user are improved.

Description

Technical Field

[0001] The present application relates to the field of artificial intelligence technology, and in particular to a work order generation method, device, equipment, medium and product. Background Art

[0002] With the accelerated development of online business, service tickets have also been fully online. For related issues that are not resolved when users come in, the seats will generate and fill out online tickets to support subsequent ticket processing personnel to effectively understand the previous communication situation and better solve customer problems.

[0003] The existing method for manual agents to create service tickets usually relies on the understanding of customer problems based on the current consulting scenario, and is filled out and circulated according to the system's preset ticket template. However, the existing methods have the following problems: 1. Since there is a lot of content filled in the ticket, it will prolong the agent's service time for the user, leading to user complaints; 2. The creation of tickets depends on the agent's understanding of the user's problem and the memory of the conversation content. In the face of each high-intensity incoming call, it will increase the pressure on customer service; 3. Subsequent ticket processing personnel rely on the content filled in the ticket, and there is no user communication record in the early stage as auxiliary processing, which may lead to a longer closed-loop time for the ticket. Therefore, designing a method for automatically generating service tickets to improve the work efficiency of manual agents and the user's service experience has become an urgent problem to be solved. Summary of the invention

[0004] The present application provides a work order generation method, device, equipment, medium and product, which can improve the efficiency of work order creation in customer service, automatically generate service work orders, improve the work efficiency of manual seats and the service experience of users.

[0005] In a first aspect, the present application provides a work order generation method, the method comprising:

[0006] Receive the creation trigger operation of the service ticket and obtain the voice data during the user service process;

[0007] Performing intent recognition on the voice data to obtain corresponding business intent and key data sets;

[0008] Filtering a target work order template from a plurality of preset work order templates based on the business intent;

[0009] The target work order template is filled with content based on the key data set to obtain a service work order corresponding to the voice data.

[0010] Furthermore, the key data set includes basic information and business information of the user; the target work order template is filled with content based on the key data set to obtain a service work order corresponding to the voice data, including: obtaining multiple table fields in the target work order template; classifying the table fields into a first field corresponding to the basic information and a second field corresponding to the business information; filling the first field with content based on the basic information, and filling the second field with content based on the business information to obtain a service work order corresponding to the voice data.

[0011] Furthermore, there are multiple business information; filling the second field with content based on the business information includes: for any business information, matching the corresponding target field from the second field; obtaining the template requirements of the target field; modifying the business information based on the template requirements to obtain the content to be filled; filling the content to be filled into the key value filling position corresponding to the target field; traversing all business information to complete the content filling of the business information in the target work order template.

[0012] Furthermore, the business information is modified based on the template requirements to obtain the content to be filled, including: analyzing the template requirements and the business information to determine the modification direction of the business information; if the modification direction is to concisely express the business information, then identifying redundant components and semantically similar sentences in the business information; deleting redundant components in the business information, and merging semantically similar sentences in the business information to obtain the content to be filled; if the modification direction is to clearly express the business information, then identifying multiple entities in the business information and semantic relationships between multiple entities; and expanding the business information based on the multiple entities and the semantic relationships to obtain the content to be filled.

[0013] Furthermore, after filling the target work order template with content based on the key data set, it also includes: determining whether there is an unfilled third field in the table field of the target work order template; if so, obtaining historical work order data corresponding to the business intent; analyzing the historical work order data to determine the content to be filled in the third field; and filling the content to be filled in the key value filling position corresponding to the third field.

[0014] Furthermore, before filling the target work order template with content based on the key data set, the method further includes: performing data cleaning on the key data set to obtain a processed key data set.

[0015] In a second aspect, the present application provides a work order generation device, the device comprising:

[0016] The voice data acquisition module is used to receive the creation trigger operation of the service ticket and obtain the voice data in the process of serving the user;

[0017] A voice data recognition module is used to perform intent recognition on the voice data to obtain corresponding business intent and key data sets;

[0018] A work order template screening module, used to screen out a target work order template from a plurality of preset work order templates based on the business intent;

[0019] A work order content filling module is used to fill the target work order template with content based on the key data set to obtain a service work order corresponding to the voice data.

[0020] In a third aspect, the present application provides an electronic device, comprising: at least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the work order generation method described in any embodiment of the present application.

[0021] In a fourth aspect, the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the work order generation method described in any embodiment of the present application when executed.

[0022] In a fifth aspect, the present application provides a computer program product, including a computer program, which, when executed by a processor, implements the work order generation method described in any embodiment of the present application.

[0023] In order to address the deficiencies of the prior art in the background technology, an embodiment of the present application provides a work order generation method, and executing the method can bring the following beneficial effects: After the agent receives the user by phone, the present application obtains the voice data in the process of serving the user, analyzes the semantics of the voice data, accurately determines the business intent, and extracts the key data set, which can reduce the work order classification errors caused by manual understanding deviations. Filling the target work order template with content based on the extracted key data set can ensure that the information is accurately filled into the corresponding fields. The present application can improve the efficiency of work order creation in customer service, automatically generate service work orders, and improve the work efficiency of manual agents and the service experience of users.

[0024] It should be noted that the above computer instructions may be stored in whole or in part on a computer-readable storage medium, wherein the computer-readable storage medium may be packaged together with the processor of the work order generating device, or may be packaged separately from the processor of the work order generating device, which is not limited in this application.

[0025] The description of the second, third, ..., and fifth aspects in this application can refer to the detailed description of the first aspect; and the beneficial effects of the description of the second, third, ..., and fifth aspects can refer to the beneficial effect analysis of the first aspect, which will not be repeated here.

[0026] It should be understood that the content described in this section is not intended to identify the key or important features of the embodiments of the present application, nor is it intended to limit the scope of the present application. Other features of the present application will become easily understood through the following description.

[0027] It is understandable that before using the technical solutions disclosed in the embodiments of this application, the type, scope of use, and usage scenarios of the personal information involved in this application should be informed to the user and the user's authorization should be obtained in an appropriate manner in accordance with relevant laws and regulations. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0029] Figure 1 A schematic diagram of a first process of a work order generation method provided in an embodiment of the present application;

[0030] Figure 2 A second flow chart of a work order generation method provided in an embodiment of the present application;

[0031] Figure 3 A schematic diagram of the structure of a work order generation device provided in an embodiment of the present application;

[0032] Figure 4 It is a block diagram of an electronic device used to implement a work order generation method in an embodiment of the present application. DETAILED DESCRIPTION

[0033] In order to make the purpose, technical solution and advantages of the embodiments of the present application clearer, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of this application.

[0034] It should be noted that the terms "first", "second", "target", and "original" in the specification and claims of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than that illustrated or described herein. In addition, the terms "including", "having", and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product, or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products, or devices.

[0035] It should be noted that the relevant information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data for display, data for analysis, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of the relevant data comply with the relevant laws, regulations and standards of the relevant regions.

[0036] Figure 1 This is a first flow chart of a work order generation method provided in an embodiment of the present application. This embodiment can be applied to a scenario where, after an agent receives a user by phone, a corresponding service work order is generated based on voice data during the service process for the user. The work order generation method provided in this embodiment can be executed by a work order generation device provided in an embodiment of the present application. The device can be implemented in software and / or hardware and integrated in an electronic device that executes this method.

[0037] See also Figure 1 The method of this embodiment includes but is not limited to the following steps:

[0038] S110: Receive a service ticket creation trigger operation, and obtain voice data during the user service process.

[0039] In an embodiment of the present application, a user dials a seat telephone or other dedicated line of an organization or enterprise, and is transferred to a manual customer service to handle pending business. After the user agrees, the call status during the service process can be recorded. When the manual customer service fails to solve the user's problem, the user will be informed to register for the current agency business. At this time, the manual customer service manually triggers the virtual button to create a service work order in the digital information processing system or performs a specific interactive behavior to trigger the creation operation of the service work order. The system is in a real-time monitoring and response state. When the system receives a creation trigger operation for a service work order, it obtains voice data in the process of serving the user.

[0040] Optionally, the pending business may be consulting services, technical support services, after-sales maintenance services, etc.

[0041] Furthermore, after acquiring the voice data, general audio processing technology can be used to perform preliminary noise reduction, gain adjustment and other optimization processing on the voice data to ensure that the acquired voice data is clear, discernible, stable and reliable.

[0042] S120: Perform intent recognition on the voice data to obtain corresponding business intent and key data sets.

[0043] In the embodiment of the present application, general natural language processing technology and deep neural network models can be used to perform intent recognition analysis on voice data. First, the voice data is digitized and feature extracted to convert the voice signal into a structured data form that can be recognized and processed by the computer, such as extracting key feature information such as the audio frequency, amplitude and duration of the voice. Then, using the pre-trained intent recognition model, during the parsing process, multiple factors such as lexical semantics, sentence structure, context, and language habits are analyzed to determine the specific business intent corresponding to the voice data, such as business consultation intent, complaint intent, business processing request intent, and other specific types.

[0044] At the same time, general named entity recognition technology and information extraction algorithms can be used to further screen and extract key data sets from voice data. Key data sets can include users' basic information and business information. Basic information can be name, ID number, account number, etc.; business information can be product name, service item, transaction amount, time node, etc.

[0045] S130. Filter out a target work order template from multiple preset work order templates based on business intent.

[0046] In the embodiment of the present application, the system pre-builds and stores multiple preset work order template libraries for different business scenarios and requirements. Each preset work order template can cover various information fields, processing flow nodes and related specification requirements under a specific business type. After determining the business intent, the system will compare and match the intent with the business type label, key feature information and applicable scenario description corresponding to each preset work order template, and finally select the target work order template with the highest matching degree from multiple preset work order templates.

[0047] For example, if the business intention is to apply for a credit card loss report for a user, the system will select a work order template specifically used for credit card loss reporting from multiple preset work order templates as the target work order template. The template will contain specific information fields such as cardholder name, credit card number, loss reporting time, loss reporting reason, etc., so that the user's credit card loss reporting business can be processed subsequently, ensuring the standardization, efficiency and accuracy of the entire business operation.

[0048] S140: Fill the target work order template with content based on the key data set to obtain a service work order corresponding to the voice data.

[0049] Specifically, the target work order template is filled with content based on the key data set to obtain a service work order corresponding to the voice data, including: obtaining multiple table fields pre-set in the target work order template; the system can use a general classification algorithm to classify these table fields into a first field corresponding to basic information and a second field corresponding to business information based on the attributes and uses of the fields; the system will automatically fill the basic information into the key value filling position corresponding to the first field to complete the content filling of the first field; the system will then automatically fill the business information into the key value filling position corresponding to the second field to complete the content filling of the second field to obtain the service work order corresponding to the voice data.

[0050] The first field corresponding to basic information usually contains the customer's identity information, such as customer name, ID number, contact number, email address, etc., which is used to build user files and communicate with users in the future. The second field corresponding to business information usually contains the content of specific business matters, such as business type, business details description, product or service number involved, transaction amount, transaction time, etc., which is used to reflect the core points of the user's pending business.

[0051] Furthermore, before filling the target work order template with content based on the key data set, it also includes: performing data cleaning on the key data set (such as format verification and logic verification) to obtain a processed key data set to ensure that the data filled in the target work order template meets the field requirements and is reasonable and correct in business logic.

[0052] Furthermore, after filling the target work order template with content based on the key data set, it also includes: after completing the preliminary filling operation of the corresponding fields with basic information and business information, the system initiates a comprehensive inspection mechanism to determine whether there is an unfilled third field in the table fields of the target work order template; if unfilled fields are found during the inspection, the system will initiate a data backtracking and mining process, that is, obtain historical work order data corresponding to the current business intention, analyze the historical work order data, and the system can determine the content to be filled in the third field based on past experience and rules; fill in the content to be filled in the key value filling position corresponding to the third field.

[0053] For example, if the current business intention is to handle after-sales maintenance services for a certain type of product, and the unfilled field is "common failure cause speculation", the system analyzes the after-sales maintenance records of similar products in the historical work order data and finds that when the product has the same failure phenomenon, in most cases it is due to the aging or damage of a specific component. In this case, "aging or damage of a certain component" will be determined as the content to be filled in the third field.

[0054] The technical solution provided in this embodiment obtains voice data in the process of serving users by receiving a creation trigger operation of a service work order; performs intent recognition on the voice data to obtain the corresponding business intent and key data set; selects a target work order template from multiple preset work order templates based on the business intent; and fills the target work order template with content based on the key data set to obtain a service work order corresponding to the voice data. After the agent receives the user by phone, the application obtains voice data in the process of serving the user, analyzes the semantics of the voice data, accurately determines the business intent, and extracts the key data set, which can reduce work order classification errors caused by manual understanding deviations. Filling the target work order template with content based on the extracted key data set can ensure that the information is accurately filled in the corresponding fields. The application can improve the efficiency of work order creation in customer service, automatically generate service work orders, and improve the work efficiency of manual agents and the service experience of users.

[0055] The following further describes the work order generation method provided by the embodiment of the present application. Figure 2 A second flow chart of a work order generation method provided in an embodiment of the present application. The embodiment of the present application is optimized on the basis of the above embodiments, and the specific optimization is as follows: the present embodiment explains in detail the process of filling the second field with content based on the business information.

[0056] See also Figure 2 The method of this embodiment includes but is not limited to the following steps:

[0057] S210: For any business information, match a corresponding target field from the second field.

[0058] In an embodiment of the present application, when it is necessary to process specific business information, the system performs an in-depth analysis of the business information to extract its key features, key words, semantic information and other core elements. Then, these extracted elements are matched one by one with each field name, field annotation and associated business logic description in the second field. Through a general intelligent matching algorithm, the algorithm can consider multi-dimensional factors such as vocabulary similarity, semantic relevance and business relevance, and accurately select the target field with the highest matching degree with the business information from multiple second fields.

[0059] For example, if the business information includes the refund amount of a credit card transaction, the system will search for relevant fields such as "credit card refund amount", "transaction refund amount", "refund amount details" in the second field, and determine the most accurate "credit card refund amount" as the corresponding target field based on the matching algorithm.

[0060] S220. Obtain template requirements for the target field.

[0061] In an embodiment of the present application, the system searches for relevant records of the target work order template from a preset storage unit, and then extracts template requirement information about the target field from the record. The template requirements may include multiple aspects, including but not limited to data type requirements, format specification requirements, required and optional attribute requirements, and value range requirements. For example, a data type requirement may be whether the data is an integer, floating point, character, or date type; a value range requirement may be the value range of the target field.

[0062] By obtaining the template requirements of these target fields, a basis and standard are provided for subsequent data filling and data verification of the fields, as well as ensuring the accuracy and standardization of the entire work order data, thus ensuring the stable operation and efficient processing of business processes at the data level.

[0063] S230: modify the business information based on the template requirements to obtain the content to be filled.

[0064] Specifically, the business information is modified based on the template requirements to obtain the content to be filled, including: analyzing the template requirements and the business information to determine the modification direction of the business information; if the modification direction is to concisely express the business information, then identifying redundant components and semantically similar sentences in the business information; deleting redundant components in the business information, and merging semantically similar sentences in the business information to obtain the content to be filled; if the modification direction is to clearly express the business information, then identifying multiple entities in the business information and semantic relationships between multiple entities; and expanding the business information based on multiple entities and semantic relationships to obtain the content to be filled.

[0065] Redundant components refer to some repeated words and phrases, or modifiers and parentheses that do not contribute substantially to the core semantic expression. Semantically similar sentences refer to at least two sentences with similar semantic structure, vocabulary usage, and logical relationships. Entities can be specific concepts or objects such as people, products, places, and time.

[0066] In an embodiment of the present application, the system conducts a comprehensive comparison and comprehensive consideration of the template requirements and the business information, evaluates from multiple dimensions whether the business information meets the standards and specifications set by the template requirements, and then determines the specific modification direction for modifying and adjusting the business information. If, after analysis and judgment, the modification direction is determined to be a concise expression of the business information. At this point, the system will use general natural language processing technology and intelligent text analysis algorithms to identify redundant components and semantically similar sentences in the business information. The system will delete redundant components and merge semantically similar sentences to obtain concise, clear, and focused content to be filled.

[0067] For example, suppose the business information is "The problem reported by the customer this time is about the problem of product failure, and this problem has affected the normal use of the product. The customer wants to apply for a refund and has a demand for a refund", where the redundant components are "the problem reported", "the problem" and "the situation", and the semantically similar sentences are "the customer wants to apply for a refund" and "the customer has a demand for a refund". Then, after simplification, the content to be filled is "the customer reported a product failure, which has affected the normal use, and wants to apply for a refund".

[0068] If the modification direction is to clearly express the business information, the system will also use general natural language processing technology to identify the multiple entities involved in the business information. The system will then further analyze the semantic relationships between these multiple entities. Based on multiple entities and semantic relationships, the system will use appropriate vocabulary, conjunctions, and grammatical structures to expand the business information sentences to obtain clearer, more accurate, and complete content to be filled in.

[0069] As another example, suppose the business information is "Xiao Ming bought a mobile phone in a store in Shanghai and will go to repair it tomorrow", where "Xiao Ming", "Shanghai store", "mobile phone" and "tomorrow" are the entities involved. For example, "Xiao Ming" has a subject-predicate relationship with "purchase" and "repair", "mobile phone" is the object of "purchase" and "repair", "Shanghai store" is the place of "purchase", and "tomorrow" is the time of "repair", etc. Then, after expansion, the content to be filled is "Customer Xiao Ming bought a mobile phone in a store in Shanghai. Because the mobile phone broke down, he plans to go to the repair place tomorrow to repair the mobile phone."

[0070] S240, filling the content to be filled into the key value filling position corresponding to the target field.

[0071] In the embodiment of the present application, the system will perform the filling operation based on the precise mapping relationship between the target field and the key value filling position in the work order template. Among them, the system will accurately locate and identify the specific position of the target field in the work order template and its corresponding key value filling position, which involves in-depth analysis and traversal of the work order template data structure.

[0072] S250, traverse all business information and complete filling the content of the business information in the target work order template.

[0073] In the embodiment of the present application, content filling operation is performed on each piece of business information according to the method logic of the above steps.

[0074] The technical solution provided in this embodiment, for any business information, matches the corresponding target field from the second field; obtains the template requirements of the target field; modifies the business information based on the template requirements to obtain the content to be filled; fills the content to be filled into the key value filling position corresponding to the target field; traverses all business information to complete the content filling of the business information in the target work order template. After the agent receives the user by phone, the application fills the content of the target work order template based on the extracted business information to ensure that the information is accurately filled into the corresponding fields. The system fills in according to the template requirements and data format specifications, avoiding format errors or wrong data filling that may occur during manual filling. The application can improve the efficiency of work order creation in customer service, automatically generate service work orders, and improve the work efficiency of manual agents and the service experience of users.

[0075] Figure 3 A schematic diagram of a work order generation device provided in an embodiment of the present application is shown in FIG. Figure 3 As shown, the device 300 may include:

[0076] The voice data acquisition module 310 is used to receive the creation trigger operation of the service ticket and acquire the voice data in the process of serving the user;

[0077] A voice data recognition module 320 is used to perform intent recognition on the voice data to obtain corresponding business intent and key data sets;

[0078] A work order template screening module 330, configured to screen a target work order template from a plurality of preset work order templates based on the business intent;

[0079] The work order content filling module 340 is used to fill the target work order template with content based on the key data set to obtain a service work order corresponding to the voice data.

[0080] Furthermore, the work order content filling module 340 may include: a first filling unit and a second filling unit;

[0081] In one embodiment, the key data set includes basic information and business information of the user;

[0082] The first filling unit can be used to obtain multiple table fields in the target work order template; classify the table fields into a first field corresponding to the basic information and a second field corresponding to the business information; fill the first field with content based on the basic information, and fill the second field with content based on the business information to obtain a service work order corresponding to the voice data.

[0083] In one embodiment, the number of the business information is multiple;

[0084] Furthermore, the above-mentioned first filling unit can also be specifically used to match the corresponding target field from the second field for any business information; obtain the template requirements of the target field; modify the business information based on the template requirements to obtain the content to be filled; fill the content to be filled into the key value filling position corresponding to the target field; traverse all business information to complete the content filling of the business information in the target work order template.

[0085] Furthermore, the above-mentioned first filling unit can also be specifically used to analyze the template requirements and the business information to determine the modification direction of the business information; if the modification direction is to concisely express the business information, then identify redundant components and semantically similar sentences in the business information; delete redundant components in the business information, and merge semantically similar sentences in the business information to obtain the content to be filled; if the modification direction is to clearly express the business information, then identify multiple entities in the business information and the semantic relationships between multiple entities; expand the business information based on the multiple entities and the semantic relationships to obtain the content to be filled.

[0086] The second filling unit can be used to determine whether there is an unfilled third field in the table field of the target work order template after filling the target work order template with content based on the key data set; if so, obtain the historical work order data corresponding to the business intent; analyze the historical work order data to determine the content to be filled in the third field; and fill the content to be filled in the key value filling position corresponding to the third field.

[0087] Furthermore, the work order generating device may further include: a data cleaning module;

[0088] The data cleaning module is used to clean the key data set before filling the target work order template with content based on the key data set to obtain a processed key data set.

[0089] The work order generation device provided in this embodiment can be applied to the work order generation method provided in any of the above embodiments, and has corresponding functions and beneficial effects.

[0090] Figure 4 It is a block diagram of an electronic device for implementing a work order generation method of an embodiment of the present application. The electronic device 10 is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workbenches, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present application described and / or required herein.

[0091] like Figure 4 As shown, the electronic device 10 includes at least one processor 11, and a memory connected to the at least one processor 11, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc., wherein the memory stores a computer program that can be executed by at least one processor, and the processor 11 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or the computer program loaded from the storage unit 18 to the random access memory (RAM) 13. In the RAM 13, various programs and data required for the operation of the electronic device 10 can also be stored. The processor 11, the ROM 12, and the RAM 13 are connected to each other through a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0092] A number of components in the electronic device 10 are connected to the I / O interface 15, including: an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a disk, an optical disk, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.

[0093] The processor 11 may be a variety of general and / or special processing components with processing and computing capabilities. Some examples of the processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The processor 11 executes the various methods and processes described above, such as a work order generation method.

[0094] In some embodiments, the work order generation method may be implemented as a computer program, which is tangibly contained in a computer-readable storage medium, such as a storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or installed on the electronic device 10 via the ROM 12 and / or the communication unit 19. When the computer program is loaded into the RAM 13 and executed by the processor 11, one or more steps of the work order generation method described above may be performed. Alternatively, in other embodiments, the processor 11 may be configured to execute the work order generation method in any other appropriate manner (e.g., by means of firmware).

[0095] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (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 system 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 system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0096] The computer programs for implementing the methods of the present application may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that when the computer programs are executed by the processor, the functions / operations specified in the flow charts and / or block diagrams are implemented. The computer programs 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.

[0097] In the context of the present application, a computer readable storage medium may be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, device, or equipment. A computer readable storage medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or equipment, or any suitable combination of the foregoing. Alternatively, a computer readable storage medium may be a machine readable signal medium. 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 device, a magnetic storage device, or any suitable combination of the foregoing.

[0098] To provide interaction with a user, the systems and techniques described herein may be implemented on an electronic device 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 electronic device. Other types of devices may also be used to provide interaction with the user; for example, the feedback provided to the user may be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form (including acoustic input, voice input, or tactile input).

[0099] The systems and techniques described herein can be implemented in a computing system that includes backend components (e.g., as a data server) or a computing system that includes middleware components (e.g., an application server) or a computing system that includes 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 systems and techniques described herein) or a computing system that includes any combination of such backend components, middleware components, or frontend components. The components of the system can 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), a blockchain network, and the Internet.

[0100] A computing system 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 client and server relationship 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 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.

[0101] Note that the above are only preferred embodiments of the present application and the technical principles used. Those skilled in the art will understand that the present application is not limited to the specific embodiments described herein, and that various obvious changes, readjustments, and substitutions can be made by those skilled in the art without departing from the scope of protection of the present application. For example, those skilled in the art can use the various forms of processes shown above to reorder, add, or delete steps; the steps recorded in the present application can be performed in parallel, sequentially, or in different orders, as long as the desired results of the technical solution of the present application can be achieved, and this document does not limit them here.

[0102] The above specific implementations do not constitute a limitation on the protection scope of this application. 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 modifications, equivalent substitutions and improvements made within the spirit and principles of this application should be included in the protection scope of this application.

Claims

1. A work order generation method, characterized in that: The method comprises: Receive the creation trigger operation of the service ticket and obtain the voice data during the user service process; Performing intent recognition on the voice data to obtain corresponding business intent and key data sets; Filtering a target work order template from a plurality of preset work order templates based on the business intent; The target work order template is filled with content based on the key data set to obtain a service work order corresponding to the voice data.

2. The work order generation method according to claim 1, characterized in that: The key data set includes basic information and business information of the user; Filling the target work order template with content based on the key data set to obtain a service work order corresponding to the voice data includes: Obtain multiple table fields in the target work order template; Classifying the table fields into a first field corresponding to the basic information and a second field corresponding to the business information; The first field is filled with content based on the basic information, and the second field is filled with content based on the business information to obtain a service work order corresponding to the voice data.

3. The work order generation method according to claim 2, characterized in that: The number of the business information is multiple; and filling the second field with content based on the business information includes: For any piece of business information, matching a corresponding target field from the second field; Obtaining template requirements for the target field; Modify the business information based on the template requirements to obtain content to be filled; Fill the content to be filled into the key value filling position corresponding to the target field; Traverse all business information and complete the content filling of the business information in the target work order template.

4. The work order generation method according to claim 3, characterized in that: The business information is modified based on the template requirements to obtain content to be filled, including: Analyze the template requirements and the business information to determine a modification direction for modifying the business information; If the modification direction is to simplify the expression of the business information, then identifying redundant components and semantically similar sentences in the business information; Deleting redundant components in the business information and merging semantically similar sentences in the business information to obtain the content to be filled; If the modification direction is to clearly express the business information, identifying multiple entities in the business information and semantic relationships between the multiple entities; The business information is sentence expanded based on the multiple entities and the semantic relationship to obtain the content to be filled.

5. The work order generation method according to claim 1, characterized in that: After the target work order template is filled with content based on the key data set, the method further includes: Determine whether there is an unfilled third field in the table field of the target work order template; If it exists, obtain the historical work order data corresponding to the business intent; Analyze the historical work order data to determine the content to be filled in the third field; Fill the content to be filled into the key value filling position corresponding to the third field.

6. The work order generation method according to claim 1, characterized in that: Before filling the target work order template with content based on the key data set, the method further includes: The key data set is cleaned to obtain a processed key data set.

7. A work order generating device, characterized in that: The device comprises: The voice data acquisition module is used to receive the creation trigger operation of the service ticket and obtain the voice data in the process of serving the user; A voice data recognition module is used to perform intent recognition on the voice data to obtain corresponding business intent and key data sets; A work order template screening module, used to screen out a target work order template from a plurality of preset work order templates based on the business intent; A work order content filling module is used to fill the target work order template with content based on the key data set to obtain a service work order corresponding to the voice data.

8. An electronic device, characterized in that: The electronic device comprises: at least one processor; and a memory communicatively coupled to the at least one processor; The memory stores a computer program executed by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the work order generating method according to any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the work order generation method according to any one of claims 1 to 6 when executed.

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

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