A quality inspection and complaint handling method, apparatus, electronic device, and storage medium

Abstract

This application discloses a quality inspection and appeal method, apparatus, electronic device, and storage medium, relating to the field of automated data processing technology. The method includes: receiving a quality inspection plan task request configured by an operations planning platform; obtaining object data according to the quality inspection plan task request; uploading the object data to an analysis platform and receiving the quality inspection results returned by the analysis platform; and, in response to detecting a violation in the quality inspection results, initiating a quality inspection appeal process through the operations planning platform. This application can reduce labor costs and unify, automate, and standardize the quality inspection and appeal process.

Description

Technical Field

[0001] This application relates to the field of automated data processing technology, and in particular to a quality inspection and complaint handling method, apparatus, electronic device, and storage medium. Background Technology

[0002] With the booming development of the internet finance industry, a large number of compliant debt collection businesses have emerged. To ensure the compliance of debt collection agents' work, it is necessary to have stricter requirements on their work processes, behaviors, and customer service scripts. This necessitates reviewing their work content, including recordings of customer calls, work-related text chat content, and behavioral data, in order to facilitate subsequent appeals, training, and rectification of violations.

[0003] Taking voice call data as an example, the traditional quality inspection method is manual inspection. Quality inspectors extract a portion of recordings from a massive database according to specific business rules, listen to them, and then score the recordings based on pre-defined scoring criteria and the inspectors' experience. However, manual quality inspection can only be conducted through sampling, meaning it follows specific sampling rules. This not only results in a low sampling rate and a fixed inspection method, but also means that different inspectors may obtain different results for the same voice call due to differences in their experience, reducing the accuracy of call data quality inspection. Alternatively, ASR (Automatic Speech Recognition) can be used for recognition followed by regularization, but this method has low accuracy and recall, requiring extensive manual review and customer service representative appeals.

[0004] For text-based data and behavioral data, quality inspection is carried out through manual sampling and checks based on user complaints and feedback. This method is labor-intensive and has low accuracy and timeliness. For the appeal process, offline email communication is mainly used, which is inefficient and further increases the difficulty of data analysis. Summary of the Invention

[0005] To address at least one of the problems mentioned in the background section, this application provides a quality inspection and complaint handling method, apparatus, electronic device, and storage medium that can reduce labor costs and standardize, automate, and regulate the quality inspection and complaint handling process.

[0006] The specific technical solutions provided in this application are as follows:

[0007] Firstly, a quality inspection and appeal method is provided, applied to a quality inspection platform, the method comprising:

[0008] Receive quality inspection plan task requests configured by the business planning platform;

[0009] Obtain object data according to the quality inspection plan task request;

[0010] The object data is uploaded to the analysis platform, and the quality inspection results returned by the analysis platform are received.

[0011] In response to the detection of violations in the quality inspection results, an appeal process for the quality inspection report is initiated through the business plan platform.

[0012] Furthermore, the object data includes at least one of voice data, text data, and behavioral data; the analysis platform includes at least one of an AI quality inspection platform and a Sparkling analysis engine; and the step of uploading the object data to the analysis platform and receiving the quality inspection results returned by the analysis platform includes:

[0013] Upload the voice data and / or text data to the AI ​​quality inspection platform, dynamically configure quality inspection semantic points and process quality inspection items for AI quality inspection;

[0014] The behavioral data is then analyzed using the Sparkling analytics engine to perform object behavior parsing.

[0015] Receive the quality inspection results returned by the AI ​​quality inspection and the object behavior analysis.

[0016] Furthermore, before receiving the quality inspection plan task request configured on the business planning platform, the method further includes:

[0017] Configure the quality inspection settings, which include at least one of the following: violation classification, violation behavior, custom quality inspection parameters, and business scenario authorization.

[0018] In response to the detection of a violation in the quality inspection result, the process of initiating a quality inspection report appeal through the business plan platform includes:

[0019] In response to the detection of a violation in the quality inspection configuration in the quality inspection result, an appeal process for the quality inspection order is initiated through the business planning platform.

[0020] Furthermore, after initiating a quality inspection report appeal process through the business plan platform in response to the detection of a violation in the quality inspection result, the method further includes:

[0021] The information on the quality inspection report is verified, and the information on the quality inspection report is entered into the table.

[0022] Assemble the BPM work order parameters based on the information in the quality inspection report, and initiate the BPM process to the BPM system.

[0023] Furthermore, after initiating the BPM process to the BPM system, the method further includes:

[0024] Receive process instance information returned by the BPM system;

[0025] Instance information of the approval process upon landing;

[0026] The process instance information includes at least one of the process instance's identity number and order number.

[0027] Furthermore, after the process instance information is approved upon landing, the method further includes:

[0028] Receive asynchronous messages from the message queue of the approval workflow stage of the BPM system;

[0029] Approval information is appended to the table based on the asynchronous message;

[0030] The approval information includes at least one of the following: approval final status information and approval operation node information.

[0031] Furthermore, after the process instance information is approved upon landing, the method further includes:

[0032] Actively initiate a request to the BPM system to obtain approval information at the approval process stage;

[0033] Receive approval information returned by the BPM system;

[0034] The approval information stated in the table;

[0035] The approval information includes at least one of the following: approval final status information and approval operation node information.

[0036] Secondly, a quality inspection and complaint handling device is provided, the device comprising:

[0037] The communication module is used to receive quality inspection plan task requests configured by the business planning platform;

[0038] The acquisition module is used to acquire object data according to the quality inspection plan task request;

[0039] The quality inspection module is used to upload the object data to the analysis platform and receive the quality inspection results returned by the analysis platform.

[0040] The appeal module is used to initiate an appeal process for the quality inspection report through the business plan platform in response to the detection of violations in the quality inspection results.

[0041] Thirdly, an electronic device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the quality inspection and complaint method.

[0042] Fourthly, a computer-readable storage medium is provided, storing computer-executable instructions for executing the quality inspection and appeal methods.

[0043] The embodiments of this application have the following beneficial effects:

[0044] This application provides a quality inspection and appeal method, apparatus, electronic device, and storage medium that can automatically analyze object data through an analysis platform. If violations are found, an appeal process is automatically initiated, achieving a unified and standardized quality inspection and appeal process. This significantly reduces labor costs, improves the timeliness of quality inspection data, and is more standardized, achieving integrated quality inspection and appeal processes. This improves the accuracy of quality inspection results and the traceability of the overall process, thereby enhancing overall efficiency. It can also uniformly collect and merge quality inspection data, improving the timeliness of data collection. By dynamically configuring quality inspection semantic points, process quality inspection, and other indicators, quality inspection audits can be conducted, allowing for real-time changes to quality inspection indicators and dimensions, improving the accuracy and timeliness of quality inspection results. It can dynamically configure appeal elements; when violations are found in the quality inspection results, an appeal process is automatically initiated to create a quality inspection form, making the appeal process standardized, integrated, and automated, and ensuring traceability. Furthermore, it can synchronously update the approval information and status of the current approval process in real time, synchronizing the approval operation node information of each node until the final approval status information is obtained, ensuring the timeliness of appeals and improving the compliance rate of quality inspection appeals. Attached Figure Description

[0045] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0046] Figure 1 This document shows a general flowchart of the quality inspection and appeal methods provided in the embodiments of this application;

[0047] Figure 2 A detailed flowchart of the AI ​​quality inspection portion of a quality inspection and appeal method according to an embodiment of this application is shown;

[0048] Figure 3 A detailed flowchart of the appeal process portion of a quality inspection and appeal method according to an embodiment of this application is shown;

[0049] Figure 4 This diagram illustrates the structure of the quality inspection and complaint handling device provided in an embodiment of this application.

[0050] Figure 5Exemplary systems that can be used to implement the various embodiments described in this application are shown. Detailed Implementation

[0051] To make the objectives, technical solutions, and advantages of this application clearer, the technical solutions in the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0052] It should be understood that, in the description of this application, unless the context explicitly requires it, the words "comprising," "including," and similar terms throughout the specification and claims should be interpreted as encompassing rather than being exclusive or exhaustive; that is, meaning "including but not limited to."

[0053] It should be noted that the terms "S1," "S2," etc., are used only for descriptive purposes and do not specifically refer to the order or sequence, nor are they intended to limit this application. They are merely for the convenience of describing the method of this application and should not be construed as indicating the sequential order of the steps. Furthermore, the technical solutions of the various embodiments can be combined with each other, but this must be based on the ability of those skilled in the art to implement them. When the combination of technical solutions is contradictory or impossible to implement, it should be considered that such a combination of technical solutions does not exist and is not within the scope of protection claimed in this application.

[0054] Example 1

[0055] This application provides a quality inspection and complaint handling method, applied to a quality inspection platform, referring to... Figure 1 The methods include:

[0056] S1. Receive quality inspection plan task requests configured by the business planning platform;

[0057] S2. Obtain object data according to the quality inspection plan task request;

[0058] S3. Upload the object data to the analysis platform and receive the quality inspection results returned by the analysis platform;

[0059] S4. In response to the detection of non-compliance in the quality inspection results, initiate the quality inspection report appeal process through the business plan platform.

[0060] Specifically, the first step is to configure quality inspection plan tasks on the business planning platform. This configuration includes setting the triggering objects, triggering behaviors, quality inspection strategy rules, inspection actions, and process information. After configuring the quality inspection plan tasks on the business planning platform, the object data of the triggering objects needs to be obtained. This object data is then analyzed through the analysis platform to detect any violations, and the results are obtained and broadcast. If violations are found in the results, the business planning platform initiates a quality inspection appeal process. By adopting this technical solution, a unified and standardized quality inspection and appeal process is achieved, automatically analyzing object data through the analysis platform and automatically initiating an appeal process if violations are found. This significantly reduces labor costs, improves the timeliness of quality inspection data, and enhances standardization. It also integrates quality inspection and appeal processes, improves the accuracy of quality inspection results, the traceability of the overall process, and increases overall efficiency.

[0061] In some implementations, the object data includes at least one of voice data, text data, and behavioral data; the analysis platform includes at least one of an AI quality inspection platform and a Sparkling analysis engine; and S3 includes:

[0062] S31. Upload voice data and / or text data to the AI ​​quality inspection platform, dynamically configure quality inspection semantic points and process quality inspection items for AI quality inspection.

[0063] S32. Parse the object behavior data using the Sparkling analysis engine;

[0064] S33. Receive the quality inspection results returned by AI quality inspection and object behavior analysis.

[0065] Specifically, the data of the triggering object may include voice data, text data, and behavioral data of the object itself. Taking collection agents as an example, voice data includes, but is not limited to, video call data, audio call data, and recording data of collection agents, while text data includes, but is not limited to, SMS data from collection agents' mobile terminals and chat data from mobile terminal applications (such as QQ, WeChat, and WeChat Work). The voice data and / or text data of collection agents are uploaded to an AI quality inspection platform for AI quality inspection. The AI ​​performs ASR translation of voice recordings and quality inspection of recorded text, and can dynamically configure quality inspection semantic points and process inspection items. In contrast, manual sampling inspection has low coverage, low efficiency, and slow timeliness, and potential risks and problems are more difficult to discover and avoid; moreover, the quality inspection effect is affected by the subjectivity of the quality inspectors, making it difficult to achieve a fair and impartial standardized process; resulting in the inability to analyze large amounts of voice or text data, and the accuracy and value of quality inspection work are not high. Through AI quality inspection, the quality inspection engine can be configured efficiently and flexibly to automatically detect text dialogues, voice calls, and work orders, and to conduct full-volume compliance quality inspection, greatly improving the efficiency of quality inspection. For example, by configuring risk warning rules, timely alerts can be issued for customer complaints, arguments, and other incidents, allowing collection agents to avoid high-risk service behaviors. Specifically, by dynamically configuring quality inspection semantic points and process quality inspection indicators, quality inspection audits can be conducted, allowing for real-time changes to the indicators and dimensions of quality inspection, improving the accuracy and timeliness of inspection results. Furthermore, it can accumulate enterprise-standard quality inspection processes, knowledge bases, or best practice case libraries, serving as a knowledge foundation for improving the service level of collection agents, facilitating subsequent regular training, enhancing service effectiveness, and increasing customer NPS (Net Promoter Score).

[0066] Specifically, Sparkling Logic SMARTS is a next-generation decision management and analytics platform, encompassing modules such as decision management, decision modelers, machine learning, dynamic questionnaires, and orchestration. The Sparkling analytics engine provides full lifecycle management of business decisions, from the development and mining of business decisions to the testing and simulation of decision logic, and finally, the deployment of models. It is widely used in industries such as finance, insurance, IoT, and healthcare to manage high-frequency, volatile operational strategies, helping companies significantly improve decision-making efficiency, reduce labor costs, accelerate the iteration of decision models, and greatly shorten product launch cycles. Faced with ever-increasing business applications and complex business requirements, traditional hard-code maintenance methods are no longer sufficient. Financial companies need to respond more quickly to business needs such as credit approval, transaction anti-fraud, and compliance review to improve their industry competitiveness. The Sparkling analytics decision engine extracts complex business logic from the code and manages it through a visual interface, greatly improving the efficiency of business strategy maintenance and accelerating the deployment of business strategies. For example, by using the Sparkling analytics decision engine to analyze the behavioral data of collection agents, it is possible to flexibly conduct behavioral quality checks and analyze the behavioral data to identify violations or irregular operations.

[0067] For example, refer to Figure 2 Taking the application of a quality inspection platform in a debt collection scenario as an example, the core debt collection system generates voice and text data from debt collection agents. The business planning platform creates quality inspection plan tasks / quality inspection data push tasks, and the debt collection engine executes the process to obtain quality inspection data based on the quality inspection plan task request / quality inspection data push task request. First, it calls the core debt collection interface to obtain the generated voice and text data of the debt collection agents. It then uses Java technology to collect and merge the quality inspection data, and then calls the loop interface to upload this quality inspection data for AI loop quality inspection. Finally, it obtains the quality inspection results, calculates the numbers, and broadcasts the results.

[0068] The following is combined Figure 3 This embodiment will be further described as follows:

[0069] In some implementations, prior to S1, the method further includes:

[0070] Configure the quality inspection settings, which include at least one of the following: violation classification, violation behavior, custom quality inspection parameters, and business scenario authorization.

[0071] Based on this, S4 includes:

[0072] S41. In response to the detection of a violation in the quality inspection configuration in the quality inspection results, initiate a quality inspection order appeal process through the business plan platform.

[0073] Specifically, before conducting quality inspection, configuration can be performed to set specific violations for subsequent detection, such as violation categories, behaviors, and operations that trigger violations. Furthermore, configuring the necessary semantic points and process inspection items before AI quality inspection allows for dynamic configuration of these indicators for quality review. The indicators and dimensions of the quality inspection can be changed in real time, enabling multi-dimensional and dynamic AI quality inspection to improve accuracy and timeliness.

[0074] In some implementations, after S4, the method further includes:

[0075] S51. Verify the information on the quality inspection report and record the information on the quality inspection report.

[0076] S52. Assemble BPM work order parameters based on the information in the quality inspection report, and initiate the BPM process to the BPM system.

[0077] Specifically, after quality inspection results are obtained, if violations are found, the system will automatically initiate a quality inspection order appeal process, either by launching a BPMN (Business Process Modeling Notation) process or by having the user manually create the quality inspection order. The initiated quality inspection order then undergoes information verification, and the verification results are then stored in the table. This quality inspection order information includes at least the corresponding transaction number from the business planning platform, which is then returned to the collection platform engine. Based on the quality inspection order information, BPM work order parameters are assembled, including predefined config information, and then the BPM process is initiated to the BPM system. This technical solution allows for dynamic configuration of appeal elements. When violations are found in the quality inspection results, an appeal process is automatically initiated to create a quality inspection order, making the appeal process standardized, integrated, and automated, and ensuring traceability.

[0078] In some implementations, after S52, the method further includes:

[0079] S61. Receive process instance information returned by the BPM system;

[0080] S62. Instance information of the approval process upon landing;

[0081] The process instance information includes at least one of the process instance's identity number and order number.

[0082] Specifically, after internal processing, the BPM system returns process instance information to be synchronized to the quality inspection platform to collect the core approval process instance information. This includes the process instance ID and order number, so as to facilitate the subsequent traceability and status update of the process instance.

[0083] In some implementations, after S62, the method further includes:

[0084] S71. Receive asynchronous messages from the message queue of the BPM system's approval workflow stage;

[0085] S72. Submit approval information to the table based on asynchronous messages;

[0086] The approval information includes at least one of the following: final approval status information and approval operation node information.

[0087] In some implementations, after S62, the method further includes:

[0088] S81. Proactively initiate a request to the BPM system to obtain approval information at the approval process stage;

[0089] S82. Receive approval information returned by the BPM system;

[0090] S83, Approval information in the form;

[0091] The approval information includes at least one of the following: final approval status information and approval operation node information.

[0092] Specifically, when the BPM system enters the approval workflow stage, the quality inspection platform's collection core can receive approval workflow MQ messages, i.e., asynchronous messages sent by the BPM system, to synchronously update the approval information and status of the current approval process. Each node performs review and confirmation. In addition to passively receiving asynchronous messages from the BPM system, the quality inspection platform can also proactively initiate approval information retrieval requests to synchronously update the approval information and status of the current approval process in real time, synchronizing the approval operation node information of each operation node until the final approval status information is obtained, thus standardizing and unifying the appeal process.

[0093] In this embodiment, the system can automatically analyze object data through an analysis platform. If violations are found, an appeal process is automatically initiated, achieving a unified and standardized quality inspection and appeal process. This significantly reduces labor costs, improves the timeliness of quality inspection data, and enhances standardization. It integrates quality inspection and appeal processes, improving the accuracy of quality inspection results and the traceability of the entire process, thereby improving overall efficiency. Furthermore, it can uniformly collect and merge quality inspection data, improving the timeliness of data collection. By dynamically configuring quality inspection semantic points and process quality inspection indicators, quality inspection audits can be conducted, allowing for real-time changes to quality inspection indicators and dimensions, improving the accuracy and timeliness of quality inspection results. It can also dynamically configure appeal elements. When violations are found in the quality inspection results, an appeal process is automatically initiated to create a quality inspection form, making the appeal process standardized, integrated, and automated, and ensuring traceability. Additionally, it can synchronize and update the approval information and status of the current approval process in real time, synchronizing the approval operation node information of each node until the final approval status information is obtained, ensuring the timeliness of appeals and improving the compliance rate of quality inspection appeals.

[0094] Example 2

[0095] Corresponding to the above embodiments, this application also provides a quality inspection and complaint handling device, referring to... Figure 4 The device includes a communication module, an acquisition module, a quality inspection module, and an appeal module.

[0096] The system includes a communication module for receiving quality inspection plan task requests configured by the business planning platform; an acquisition module for acquiring object data according to the quality inspection plan task requests; a quality inspection module for uploading the object data to the analysis platform and receiving the quality inspection results returned by the analysis platform; and an appeal module for initiating a quality inspection order appeal process through the business planning platform in response to the detection of violations in the quality inspection results.

[0097] Furthermore, the object data includes at least one of voice data, text data, and behavioral data, and the analysis platform includes at least one of an AI quality inspection platform and a Sparkling analysis engine. Based on this, the quality inspection module is also used to upload the voice data and / or text data to the AI ​​quality inspection platform, dynamically configure quality inspection semantic points and process quality inspection items for AI quality inspection; the quality inspection module is also used to perform object behavior parsing on the behavioral data through the Sparkling analysis engine; and to receive the quality inspection results returned by the AI ​​quality inspection and the object behavior parsing.

[0098] Furthermore, the device also includes a quality inspection configuration module for configuring quality inspection, wherein the quality inspection configuration includes at least one of the following: violation classification, violation behavior, custom quality inspection parameters, and business scenario authorization. Based on this, the appeal module is also used to initiate a quality inspection order appeal process through the business planning platform in response to the detection of a violation item configured in the quality inspection configuration in the quality inspection result.

[0099] Furthermore, the appeal module is also used to verify the information of the quality inspection form and record the information of the quality inspection form; and to assemble BPM work order parameters based on the information of the quality inspection form and initiate the BPM process to the BPM system.

[0100] Furthermore, the appeal module is also used to receive process instance information returned by the BPM system; and to approve the process instance information. The process instance information includes at least one of the process instance's identification number and order number.

[0101] Furthermore, the appeal module is also used to receive asynchronous messages in the message queue of the BPM system's approval workflow stage; and to append approval information to the table based on the asynchronous messages. The approval information includes at least one of approval final status information and approval operation node information.

[0102] Furthermore, the appeal module is also used to proactively initiate a request to the BPM system to obtain approval information at each stage of the approval process; and to receive approval information returned by the BPM system; the appeal module is also used to append the approval information to the table. The approval information includes at least one of approval final status information and approval operation node information.

[0103] Specific limitations regarding the quality inspection and appeal device can be found in the relevant limitations described in the embodiments of the quality inspection and appeal methods above, and will not be repeated here. Each module in the aforementioned quality inspection and appeal device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device in hardware form, or stored in the memory of a computer device in software form, so that the processor can call and execute the operations corresponding to each module.

[0104] Example 3

[0105] Corresponding to the above embodiments, this application also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, it can implement a quality inspection and complaint method, including the following steps:

[0106] Receive quality inspection plan task requests configured by the business planning platform;

[0107] Obtain object data according to the quality inspection plan task request;

[0108] The object data is uploaded to the analysis platform, and the quality inspection results returned by the analysis platform are received.

[0109] In response to the detection of violations in the quality inspection results, an appeal process for the quality inspection report is initiated through the business plan platform.

[0110] In one embodiment, the object data includes at least one of voice data, text data, and behavioral data, and the analysis platform includes at least one of an AI quality inspection platform and a Sparkling analysis engine. Based on this, when the processor executes the computer program, it can also perform the following steps:

[0111] Upload the voice data and / or text data to the AI ​​quality inspection platform, dynamically configure quality inspection semantic points and process quality inspection items for AI quality inspection;

[0112] The behavioral data is then analyzed using the Sparkling analytics engine to perform object behavior parsing.

[0113] Receive the quality inspection results returned by the AI ​​quality inspection and the object behavior analysis.

[0114] In one implementation, the processor may also perform the following steps when executing a computer program:

[0115] Configure quality inspection, which includes at least one of the following: violation classification, violation behavior, custom quality inspection parameters, and business scenario authorization; and

[0116] In response to the detection of a violation in the quality inspection configuration in the quality inspection result, an appeal process for the quality inspection order is initiated through the business planning platform.

[0117] In one implementation, the processor may also perform the following steps when executing a computer program:

[0118] The information on the quality inspection report is verified, and the information on the quality inspection report is entered into the table.

[0119] Assemble the BPM work order parameters based on the information in the quality inspection report, and initiate the BPM process to the BPM system.

[0120] In one implementation, the processor may also perform the following steps when executing a computer program:

[0121] Receive process instance information returned by the BPM system;

[0122] Instance information of the approval process upon landing;

[0123] The process instance information includes at least one of the process instance's identity number and order number.

[0124] In one implementation, the processor may also perform the following steps when executing a computer program:

[0125] Receive asynchronous messages from the message queue of the approval workflow stage of the BPM system;

[0126] Approval information is appended to the table based on the asynchronous message;

[0127] The approval information includes at least one of the following: approval final status information and approval operation node information.

[0128] In one implementation, the processor may also perform the following steps when executing a computer program:

[0129] Actively initiate a request to the BPM system to obtain approval information at the approval process stage;

[0130] Receive approval information returned by the BPM system;

[0131] The approval information stated in the table;

[0132] The approval information includes at least one of the following: approval final status information and approval operation node information.

[0133] like Figure 5 As shown, in some embodiments, the system can serve as any of the aforementioned electronic devices for quality inspection and complaint handling methods in each of the embodiments. In some embodiments, the system may include one or more computer-readable media (e.g., system memory or NVM / storage device) having instructions and one or more processors (e.g., one or more processors) coupled to the one or more computer-readable media and configured to execute the instructions to implement the module and thus perform the actions described in this application.

[0134] In one embodiment, the system control module may include any suitable interface controller to provide any suitable interface to at least one of the processors(s) and / or any suitable device or component communicating with the system control module.

[0135] The system control module may include a memory controller module to provide an interface to the system memory. The memory controller module may be a hardware module, a software module, and / or a firmware module.

[0136] System memory can be used, for example, to load and store data and / or instructions for the system. In one embodiment, system memory may include any suitable volatile memory, such as suitable DRAM. In some embodiments, system memory may include Double Data Rate Type Quad Synchronous Dynamic Random Access Memory (DDR4 SDRAM).

[0137] In one embodiment, the system control module may include one or more input / output (I / O) controllers to provide interfaces to the NVM / storage device and (one or more) communication interfaces.

[0138] For example, an NVM / storage device can be used to store data and / or instructions. An NVM / storage device may include any suitable non-volatile memory (e.g., flash memory) and / or may include any suitable (one or more) non-volatile storage devices (e.g., one or more hard disk drives (HDDs), one or more optical disc drives (CDs), and / or one or more digital universal optical disc (DVD) drives).

[0139] NVM / storage devices may include storage resources that are physically part of a device on which the system is mounted, or that can be accessed by the device without necessarily being part of it. For example, an NVM / storage device may be accessed over a network via one or more communication interfaces.

[0140] One or more communication interfaces may provide the system with an interface to communicate over one or more networks and / or with any other suitable device. The system may wirelessly communicate with one or more components of a wireless network in accordance with any of the standards and / or protocols in one or more wireless network standards and / or protocols.

[0141] In one embodiment, at least one of the processors may be logically packaged with one or more controllers of the system control module (e.g., a memory controller module). In one embodiment, at least one of the processors may be logically packaged with one or more controllers of the system control module to form a system-in-package (SiP). In one embodiment, at least one of the processors may be integrated with the logic of one or more controllers of the system control module on the same die. In one embodiment, at least one of the processors may be integrated with the logic of one or more controllers of the system control module on the same die to form a system-on-a-chip (SoC).

[0142] In various embodiments, the system may be, but is not limited to, a server, workstation, desktop computing device, or mobile computing device (e.g., laptop computing device, handheld computing device, tablet computer, netbook, etc.). In various embodiments, the system may have more or fewer components and / or different architectures. For example, in some embodiments, the system includes one or more cameras, a keyboard, a liquid crystal display (LCD) screen (including a touchscreen display), a non-volatile memory port, multiple antennas, a graphics chip, an application-specific integrated circuit (ASIC), and a speaker.

[0143] It should be noted that this application can be implemented in software and / or a combination of software and hardware, for example, using an application-specific integrated circuit (ASIC), a general-purpose computer, or any other similar hardware device. In one embodiment, the software program of this application can be executed by a processor to implement the steps or functions described above. Similarly, the software program of this application (including related data structures) can be stored in a computer-readable recording medium, such as RAM memory, magnetic or optical drives, floppy disks, and similar devices. Furthermore, some steps or functions of this application can be implemented in hardware, for example, as circuitry that cooperates with a processor to perform the various steps or functions.

[0144] Furthermore, a portion of this application can be applied as a computer program product, such as computer program instructions, which, when executed by a computer, can invoke or provide the methods and / or technical solutions according to this application through the operation of the computer. Those skilled in the art will understand that the forms in which computer program instructions exist in a computer-readable medium include, but are not limited to, source files, executable files, installation package files, etc. Correspondingly, the ways in which computer program instructions are executed by a computer include, but are not limited to: the computer directly executing the instructions, or the computer compiling the instructions and then executing the corresponding compiled program, or the computer reading and executing the instructions, or the computer reading and installing the instructions and then executing the corresponding installed program. Here, the computer-readable medium can be any available computer-readable storage medium or communication medium accessible to a computer.

[0145] Communication media include media through which communication signals containing, for example, computer-readable instructions, data structures, program modules, or other data are transmitted from one system to another. Communication media can include guided transmission media (such as cables and wires (e.g., optical fibers, coaxial cables, etc.)) and wireless (unguided transmission) media capable of propagating energy waves, such as sound, electromagnetic, RF, microwave, and infrared. Computer-readable instructions, data structures, program modules, or other data can be embodied as modulated data signals in, for example, wireless media (such as carrier waves or similar mechanisms embodied as part of spread spectrum technology). The term "modulated data signal" refers to a signal whose one or more characteristics are altered or set in a manner that encodes information in the signal. Modulation can be analog, digital, or a hybrid modulation technique.

[0146] Herein, one embodiment of this application includes an apparatus comprising a memory for storing computer program instructions and a processor for executing the program instructions, wherein when the computer program instructions are executed by the processor, the apparatus is triggered to run a method and / or technical solution based on the foregoing embodiments of this application.

[0147] Example 4

[0148] Corresponding to the above embodiments, this application also provides a computer-readable storage medium storing computer-executable instructions for performing quality inspection and complaint handling methods, including the following steps:

[0149] Receive quality inspection plan task requests configured by the business planning platform;

[0150] Obtain object data according to the quality inspection plan task request;

[0151] The object data is uploaded to the analysis platform, and the quality inspection results returned by the analysis platform are received.

[0152] In response to the detection of violations in the quality inspection results, an appeal process for the quality inspection report is initiated through the business plan platform.

[0153] In one embodiment, the object data includes at least one of voice data, text data, and behavioral data, and the analysis platform includes at least one of an AI quality inspection platform and a Sparkling analysis engine. Based on this, the computer-executable instructions are further configured to perform the following steps:

[0154] Upload the voice data and / or text data to the AI ​​quality inspection platform, dynamically configure quality inspection semantic points and process quality inspection items for AI quality inspection;

[0155] The behavioral data is then analyzed using the Sparkling analytics engine to perform object behavior parsing.

[0156] Receive the quality inspection results returned by the AI ​​quality inspection and the object behavior analysis.

[0157] In one implementation, the computer-executable instructions are further configured to perform the following steps:

[0158] Configure quality inspection, which includes at least one of the following: violation classification, violation behavior, custom quality inspection parameters, and business scenario authorization; and

[0159] In response to the detection of a violation in the quality inspection configuration in the quality inspection result, an appeal process for the quality inspection order is initiated through the business planning platform.

[0160] In one implementation, the computer-executable instructions are further configured to perform the following steps:

[0161] The information on the quality inspection report is verified, and the information on the quality inspection report is entered into the table.

[0162] Assemble the BPM work order parameters based on the information in the quality inspection report, and initiate the BPM process to the BPM system.

[0163] In one implementation, the computer-executable instructions are further configured to perform the following steps:

[0164] Receive process instance information returned by the BPM system;

[0165] Instance information of the approval process upon landing;

[0166] The process instance information includes at least one of the process instance's identity number and order number.

[0167] In one implementation, the computer-executable instructions are further configured to perform the following steps:

[0168] Receive asynchronous messages from the message queue of the approval workflow stage of the BPM system;

[0169] Approval information is appended to the table based on the asynchronous message;

[0170] The approval information includes at least one of the following: approval final status information and approval operation node information.

[0171] In one implementation, the computer-executable instructions are further configured to perform the following steps:

[0172] Actively initiate a request to the BPM system to obtain approval information at the approval process stage;

[0173] Receive approval information returned by the BPM system;

[0174] The approval information stated in the table;

[0175] The approval information includes at least one of the following: approval final status information and approval operation node information.

[0176] In this embodiment, a computer-readable storage medium may include volatile and non-volatile, removable and non-removable media implemented by any method or technology for storing information such as computer-readable instructions, data structures, program modules or other data. For example, a computer-readable storage medium includes, but is not limited to, volatile memories such as random access memory (RAM, DRAM, SRAM); and non-volatile memories such as flash memory, various read-only memories (ROM, PROM, EPROM, EEPROM), magnetic and ferromagnetic / ferroelectric memories (MRAM, FeRAM); and magnetic and optical storage devices (hard disks, magnetic tapes, CDs, DVDs); or other currently known media or those developed hereafter capable of storing computer-readable information / data for use by a computer system.

[0177] Although preferred embodiments have been described in this application, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments as well as all changes and modifications falling within the scope of the embodiments of this application.

[0178] Obviously, those skilled in the art can make various modifications and variations to this application without departing from the spirit and scope of this application. Therefore, if such modifications and variations fall within the scope of the claims of this application and their equivalents, this application also intends to include such modifications and variations.

Claims

1. A quality inspection and complaint method, characterized in that, Applied to a quality inspection platform, the method includes: Receive quality inspection plan task requests configured by the business planning platform; Obtain object data according to the quality inspection plan task request; The object data is uploaded to the analysis platform, and the quality inspection results returned by the analysis platform are received. In response to the detection of violations in the quality inspection results, an appeal process for the quality inspection report is initiated through the business plan platform. The object data includes at least one of voice data, text data, and behavioral data; the analysis platform includes at least one of an AI quality inspection platform and a Sparkling analysis engine; and uploading the object data to the analysis platform and receiving the quality inspection results returned by the analysis platform includes: The voice data and / or text data are uploaded to the AI ​​quality inspection platform, and the quality inspection semantic points and process quality inspection items are dynamically configured for AI quality inspection. The AI ​​quality inspection includes: ASR translation of the voice recording by AI and quality inspection of the recorded text. The behavioral data is processed by the Sparkling analysis engine to perform object behavior parsing, wherein object behavior parsing includes: parsing the behavioral data and identifying violations or violations. Receive the quality inspection results returned by the AI ​​quality inspection and the object behavior analysis; Before receiving the quality inspection plan task request configured on the business planning platform, the method further includes: Configure the quality inspection settings, which include at least one of the following: violation classification, violation behavior, custom quality inspection parameters, and business scenario authorization. In response to the detection of a violation in the quality inspection result, the process of initiating a quality inspection report appeal through the business plan platform includes: In response to the detection of a violation in the quality inspection configuration in the quality inspection result, a quality inspection order appeal process is initiated through the business planning platform, wherein the quality inspection order appeal process is automatically initiated by the business planning platform; In response to the detection of a violation in the quality inspection result, after initiating a quality inspection report appeal process through the business plan platform, the method further includes: The information on the quality inspection report is verified, and the information on the quality inspection report is entered into the table. Based on the information in the quality inspection report, assemble the BPM work order parameters and initiate the BPM process to the BPM system; Receive process instance information returned by the BPM system; Instance information of the approval process upon landing; The process instance information includes at least one of the process instance's identity number and order number; Actively initiate a request to the BPM system to obtain approval information at the approval process stage; Receive approval information returned by the BPM system; The approval information stated in the table; The approval information includes at least one of the following: approval final status information and approval operation node information.

2. The quality inspection and complaint handling method according to claim 1, characterized in that, After the process instance information for the landing approval is obtained, the method further includes: Receive asynchronous messages from the message queue of the approval workflow stage of the BPM system; Approval information is appended to the table based on the asynchronous message; The approval information includes at least one of the following: approval final status information and approval operation node information.

3. A quality inspection and appeal apparatus for implementing the quality inspection and appeal method according to any one of claims 1-2, characterized in that, The device includes: The communication module is used to receive quality inspection plan task requests configured by the business planning platform; The acquisition module is used to acquire object data according to the quality inspection plan task request; The quality inspection module is used to upload the object data to the analysis platform and receive the quality inspection results returned by the analysis platform. The appeal module is used to initiate an appeal process for the quality inspection report through the business planning platform in response to the detection of a violation in the quality inspection results, wherein the business planning platform automatically initiates the appeal process for the quality inspection report.

4. An electronic device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the quality inspection and appeal method as described in any one of claims 1 to 2.

5. A computer-readable storage medium storing computer-executable instructions, characterized in that, The computer-executable instructions are used to execute the quality inspection and complaint method as described in any one of claims 1 to 2.

Images