Method and system for intelligently matching auditor with task, and electronic equipment

Abstract

The invention provides an auditor and task intelligent matching method and system and electronic equipment, and the method comprises the steps: obtaining the type of a task to be executed by an auditor, obtaining the initial capability information of the auditor, and carrying out the initial static capability classification of the auditor according to the initial capability information of the auditor; after the auditor performs task trial, performing dynamic ability grading on the auditor; and according to the results of the initial static capability grading and the dynamic capability grading, forming a multi-dimensional capability label of the auditor, and matching the auditor with the task type, so that the auditor can be matched with the task type more accurately, the task execution quality and efficiency are improved, and the task execution efficiency is improved. And outputting a compensation point matched with the type of the corresponding task of the auditor according to the matching degree, training the auditor according to the compensation point, and then performing dynamic capability grading and re-matching of the auditor and the type of the task again, so that the evaluation process is repeatedly iterated, and the dynamic capability spirally rises.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent matching of auditors and tasks, and in particular to a method and system for intelligent matching of auditors and tasks, and electronic equipment. Background Art

[0002] Currently, certification bodies select auditors for tasks by searching the auditor information system for matching based on two main keywords, namely level and profession, as static labels of auditors. Obviously, this matching method cannot select fully competent auditors. However, the current situation is that the auditor's ability attribute labels retrieved by the auditor information system only include level and profession, which cannot support the continued selection of professional auditors who are more suitable for task requirements, and cannot improve the accuracy of matching. In addition, there has been no quantitative evaluation method for the matching degree between auditors and tasks, and it is impossible to achieve high matching and automatic selection of auditors.

[0003] Therefore, the prior art needs to be further developed. Summary of the invention

[0004] The purpose of the present invention is to overcome the above-mentioned technical deficiencies and provide a method and system, and electronic device for intelligently matching auditors with tasks to solve the problems existing in the prior art.

[0005] To achieve the above technical objectives, according to a first aspect of the present invention, the present invention provides a method for intelligently matching auditors with tasks, comprising:

[0006] S100, obtaining the type of tasks to be performed by the auditor, and obtaining the initial capability information of the auditor, and performing initial static capability grading on the auditor according to the initial capability information of the auditor;

[0007] S200, dynamic competency grading of auditors after they have been task-tested;

[0008] S300. Form a multi-dimensional capability label for the auditor based on the results of the initial static capability grading and the dynamic capability grading, and match the auditor with the type of the task based on the multi-dimensional capability label for the auditor.

[0009] S400, calculating the matching degree between the auditor and the type of the corresponding task, outputting the compensation point of the auditor and the type of the corresponding task according to the matching degree, and training the auditor according to the compensation point, and then re-classifying the auditor's dynamic ability and re-matching the auditor with the type of the task.

[0010] Specifically, the types of tasks include at least the following three:

[0011] Certification audit tasks, technical service tasks, and technical training tasks.

[0012] Specifically, the initial static capability grading of the auditors according to the initial capability information of the auditors includes:

[0013] The initial capability information of the auditor includes multiple single static capability labels. Based on the multiple single static capability labels of each auditor, the auditor is initially evaluated for capability, and then the auditor is initially statically graded to obtain the initial static capability grading label of each auditor.

[0014] Specifically, after the auditor has completed the task trial, the auditor is dynamically graded for competence, including:

[0015] After the auditor has conducted a task trial, a weight is set corresponding to each preset indicator. The preset indicators include multiple individual dynamic capability labels. Each auditor is scored according to each individual dynamic capability label to obtain the score of each preset indicator corresponding to each auditor. Based on the weight corresponding to each preset indicator and the score, the auditor is comprehensively evaluated for his or her ability, and then the auditor is dynamically graded to obtain a dynamic capability grading label for each auditor.

[0016] Specifically, the multi-dimensional capability label includes:

[0017] Each auditor’s single static capability label, initial static capability grading label, single dynamic capability label, and dynamic capability grading label.

[0018] Specifically, matching the auditor with the type of the task according to the multi-dimensional capability label of the auditor includes:

[0019] Set specific requirements for the multi-dimensional capability labels corresponding to the types of tasks, establish matching principles for the types of tasks and the multi-dimensional capability labels of auditors, and obtain the types of tasks corresponding to each auditor based on the matching principles for the types of tasks and the multi-dimensional capability labels of auditors.

[0020] Specifically, the S400 includes:

[0021] Calculate the matching degree between the auditor and the type of the task corresponding to the auditor, determine whether the matching degree is greater than or equal to a first preset threshold, and determine whether to re-match the task classification corresponding to the auditor based on the determination result.

[0022] Specifically, judging whether to re-match the type of task corresponding to the auditor according to the judgment result includes:

[0023] If the matching degree is greater than or equal to a first preset threshold, it is determined not to re-match the type of task corresponding to the auditor;

[0024] If the matching degree is less than the first preset threshold, it is determined to re-match the type of task corresponding to the auditor, and output the compensation point between the auditor and the type of task corresponding to the auditor. The auditor is trained according to the compensation point, and then the auditor is dynamically graded for capability again and the auditor is matched with the type of task again until the matching degree is greater than or equal to the first preset threshold.

[0025] According to a second aspect of the present invention, a system for intelligently matching auditors with tasks is provided, comprising:

[0026] Acquisition module: used to obtain the types of tasks that the auditor needs to perform and obtain the auditor's initial capability information;

[0027] Control module: used to perform initial static capability grading of auditors based on the initial capability information of the auditors; or to perform dynamic capability grading of auditors after the auditors have performed task trials; or to form a multi-dimensional capability label of the auditors based on the results of the initial static capability grading and the dynamic capability grading, and match the auditors with the types of the tasks based on the multi-dimensional capability label of the auditors; or to calculate the degree of matching between the auditors and the types of their corresponding tasks, output compensation points for matching between the auditors and the types of their corresponding tasks based on the matching degrees, and train the auditors based on the compensation points, and then perform dynamic capability grading on the auditors again and match the auditors with the types of the tasks again.

[0028] According to a third aspect of the present invention, there is provided an electronic device, comprising:

[0029] GPU: Integrates deep learning algorithms and conducts deep learning training when the auditors whose matching degree is greater than or equal to the first preset threshold match the types of tasks to be performed;

[0030] FPGA control module: used to control the input and output units;

[0031] Switch: used to realize information interconnection;

[0032] Input and output unit: performs input and output under FPGA control;

[0033] A memory; and a processor, wherein the memory stores computer-readable instructions, and when the computer-readable instructions are executed by the processor, the above-mentioned method of intelligent matching of auditors and tasks is implemented.

[0034] Beneficial effects:

[0035] The present invention forms a multi-dimensional capability label for the auditor by performing initial static capability grading and dynamic capability grading on the auditor, and matches the auditor with the type of the task. By performing initial static capability grading and dynamic capability grading on the auditor, the auditor can be matched with the type of task more accurately, further improving the quality and efficiency of task execution. The establishment of multi-dimensional capability labels makes the matching process more accurate, and tasks can be reasonably allocated according to the actual situation of the auditor, avoiding the waste of resources caused by capability mismatch. By proposing an evaluation method for the matching degree of the auditor and the task, the matching degree of the auditor and the task is accurately quantified from qualitative, greatly improving the accuracy of the matching, and outputting a compensation point for matching the auditor with the type of the corresponding task according to the matching degree, and training the auditor according to the compensation point, and then performing dynamic capability grading on the auditor again and matching the auditor with the type of the task again, so that the dynamic capability evaluation process is iterated repeatedly, and the dynamic capability spirally rises, which greatly improves the intelligence, usability and reliability of the present invention, and greatly expands the application scenarios of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 is a flow chart of a method for intelligently matching auditors with tasks provided in a specific embodiment of the present invention;

[0037] Figure 2 It is a schematic diagram of the composition of the system for intelligently matching auditors with tasks provided in a specific embodiment of the present invention;

[0038] Figure 3 It is a structural diagram of the overall idea of ​​the auditor's refined hierarchical management model provided in the specific implementation mode of the present invention. DETAILED DESCRIPTION

[0039] In order to enable those skilled in the art to better understand the technical solution of the present invention, the technical solution of the present invention is clearly and completely described below in conjunction with the accompanying drawings of the present invention. Based on the embodiments in this application, other similar embodiments obtained by ordinary technicians in this field without making creative work should all fall within the scope of protection of this application. In addition, the directional words mentioned in the following embodiments, such as "up", "down", "left", "right", etc., are only reference to the directions of the accompanying drawings. Therefore, the directional words used are used to illustrate rather than limit the invention.

[0040] The present invention will be further described below in conjunction with the accompanying drawings and preferred embodiments.

[0041] See also Figure 1 This embodiment provides a method for intelligently matching auditors with tasks, including:

[0042] S100, obtaining the type of tasks to be performed by the auditor, and obtaining the initial capability information of the auditor, and performing initial static capability grading on the auditor according to the initial capability information of the auditor;

[0043] It should be further explained that, before performing S100, a first preset threshold is pre-set, and the present invention does not impose further restrictions on the value of the first preset threshold, as long as the method for intelligent matching of auditors and tasks described in the present invention can be applied.

[0044] Preferably, the present invention sets the first preset threshold value to 80%. The above setting greatly improves the accuracy of matching, and greatly improves the intelligence, usability and reliability of the present invention.

[0045] Specifically, the types of tasks include at least the following three:

[0046] Certification audit tasks, technical service tasks, and technical training tasks.

[0047] Specifically, the initial static capability grading of the auditors according to the initial capability information of the auditors includes:

[0048] The initial capability information of the auditor includes multiple single static capability labels. Based on the multiple single static capability labels of each auditor, the auditor is initially evaluated for capability, and then the auditor is initially statically graded to obtain the initial static capability grading label of each auditor.

[0049] It is understandable that each individual static competency label of the existing initial competency information of the newly hired auditor is evaluated. The individual static competency label can select the auditor's existing professional work experience, academic qualifications and professional titles, and each auditor is initially graded according to the above individual static competency label.

[0050] S200, dynamic competency grading of auditors after they have been task-tested;

[0051] It is understandable that after the initial grading of each auditor, different training programs are formulated according to the corresponding initial static capability grading, corresponding professional training is carried out, and then task trials are carried out. After multiple rounds of task trials, comprehensive capability evaluation is carried out and dynamic capability grading is performed for each auditor.

[0052] Specifically, after the auditor has completed the task trial, the auditor is dynamically graded for competence, including:

[0053] After the auditor has conducted a task trial, a weight is set corresponding to each preset indicator. The preset indicators include multiple individual dynamic capability labels. Each auditor is scored according to each individual dynamic capability label to obtain the score of each preset indicator corresponding to each auditor. Based on the weight corresponding to each preset indicator and the score, the auditor is comprehensively evaluated for his or her ability, and then the auditor is dynamically graded to obtain a dynamic capability grading label for each auditor.

[0054] It should be noted here that after multiple rounds of task trials, auditors will be subject to comprehensive competence evaluation. The preset indicators include personal quality, professional experience, professional ability, auditing ability, auditing performance, etc. Each preset indicator includes multiple single dynamic competence labels. For example, personal quality includes physical fitness, work attitude, task response, service awareness and other single dynamic competence labels. Similarly, auditors are scored according to each single dynamic competence label under each preset indicator to obtain the score of each preset indicator. The score is multiplied by the weight corresponding to each preset indicator to obtain the dynamic competence score of each auditor. Each auditor is graded according to the dynamic competence score to obtain the dynamic competence grading label of each auditor.

[0055] S300. Form a multi-dimensional capability label for the auditor based on the results of the initial static capability grading and the dynamic capability grading, and match the auditor with the type of the task based on the multi-dimensional capability label for the auditor.

[0056] Specifically, the multi-dimensional capability label includes:

[0057] Each auditor’s single static capability label, initial static capability grading label, single dynamic capability label, and dynamic capability grading label.

[0058] Furthermore, the multi-dimensional capability labels of each auditor are added to the auditor information database file to achieve detailed personnel portraits. When facing different types of tasks, the auditor information database can automatically retrieve accurate auditor portraits with multi-dimensional capability labels and quickly achieve accurate matching of auditors.

[0059] Specifically, matching the auditor with the type of the task according to the multi-dimensional capability label of the auditor includes:

[0060] Set specific requirements for the multi-dimensional capability labels corresponding to the types of tasks, establish matching principles for the types of tasks and the multi-dimensional capability labels of auditors, and obtain the types of tasks corresponding to each auditor based on the matching principles for the types of tasks and the multi-dimensional capability labels of auditors.

[0061] It is understandable that the types of tasks include multiple sub-task categories. For example, the certification audit tasks include major projects, new-era equipment construction quality management system level evaluation, equipment contracting, supervision audit, etc. Each sub-task classification needs to set its corresponding multi-dimensional capability label requirements. The corresponding single static capability label and single dynamic capability label requirements can be set according to the actual task type or special requirements, and finally the task type corresponding to each auditor is obtained.

[0062] S400, calculating the matching degree between the auditor and the type of the corresponding task, outputting the compensation point of the auditor and the type of the corresponding task according to the matching degree, and training the auditor according to the compensation point, and then re-classifying the auditor's dynamic ability and re-matching the auditor with the type of the task.

[0063] Specifically, the S400 includes:

[0064] Calculate the matching degree between the auditor and the type of the task corresponding to the auditor, determine whether the matching degree is greater than or equal to a first preset threshold, and determine whether to re-match the task classification corresponding to the auditor based on the determination result.

[0065] Specifically, judging whether to re-match the type of task corresponding to the auditor according to the judgment result includes:

[0066] If the matching degree is greater than or equal to a first preset threshold, it is determined not to re-match the type of task corresponding to the auditor;

[0067] If the matching degree is less than the first preset threshold, it is determined to re-match the type of task corresponding to the auditor, and output the compensation point between the auditor and the type of task corresponding to the auditor. The auditor is trained according to the compensation point, and then the auditor is dynamically capable of being graded again and the auditor is matched again with the type of task until the matching degree is greater than or equal to the first preset threshold.

[0068] What needs to be explained here is that, based on the principle of closed-loop feedback adjustment of automatic control, through the evaluation of dynamic capabilities, based on the compensation points, that is, the places where the auditor is insufficient in the types of tasks performed during the matching process, adjustment and compensation are made, which is linked to the human resources training system to achieve the inadequacy of comprehensive evaluation through targeted training and on-site trials to form new dynamic capabilities. When entering the comprehensive evaluation stage of dynamic capabilities, the dynamic capability evaluation process is iterated repeatedly, and the dynamic capabilities spiral upward.

[0069] The supplement of compensation points is linked to the human resources training system, and targeted training courses are selected in the training system. After the task trial, it is evaluated again to form a closed-loop iterative process. Subsequent improvements can not only be theoretical training of the course, but also other methods can be selected, such as digital simulation training platform.

[0070] It can be understood that the matching degree can be calculated by taking the satisfaction evaluation of the enterprise as a user after the audit, the evaluation of the audit file after the audit, and the evaluation of the auditor's profession selected before the audit and the profession of the product scope as evaluation indicators, and calculating the matching degree between the auditor and the type of the corresponding task. For example, taking the above evaluation indicators as an example, the calculation method of the matching degree is as follows:

[0071] (1) Satisfaction evaluation of the enterprise as a user after the audit (weight 40%)

[0072] Satisfied and very satisfied (100 points), good (80 points), average (60 points), dissatisfied (40 points);

[0073] (2) Evaluation of the audit file after the audit is completed (weight 35%)

[0074] Excellent (100 points), good (80 points), fair (60 points), poor (40 points);

[0075] (3) Evaluation of the auditor’s specialty and the product scope’s specialty selected before the audit (weight 25%)

[0076] All auditors are first-class professionals (100 points); 90% or more of the auditors in the audit group are first-class professionals (90 points); 80% or more of the auditors in the audit group are first-class professionals (80 points); 70% or more of the auditors in the audit group are first-class professionals (70 points); 60% or more of the auditors in the audit group are first-class professionals (60 points); 50% or more of the auditors in the audit group are first-class professionals (50 points); No auditors in the audit group are first-class professionals (40 points);

[0077] The calculation formula of matching degree R is as follows:

[0078] R = (X1 + X2 + X3) / 100;

[0079] Among them, X1 is the product of the satisfaction evaluation score of the enterprise as a user after the audit and its weight, X2 is the product of the evaluation score of the audit file after the audit and its weight, and X3 is the product of the evaluation score of the auditor's profession and the product scope's profession selected before the audit and its weight;

[0080] The present invention preferably sets the first preset threshold to 80%. When the matching degree is greater than or equal to 80%, the match is judged to be relatively accurate and no re-matching is required. When the matching degree is less than 80%, the matching accuracy is judged to be poor and it is necessary to re-examine whether the evaluation of each single static capability label and single dynamic capability label of the corresponding auditor is reasonable, and then re-match until the matching degree is greater than or equal to the first preset threshold, thereby forming a closed-loop control and further improving the matching degree between the auditor and the task type.

[0081] See also Figure 3 The working principle of the present invention is described below by using specific examples:

[0082] The present invention relates to a method for intelligently matching auditors with tasks, and the matching degree can reach more than 80%. It mainly solves the matching of auditors sent by certification bodies and audit tasks related to certified enterprises, establishes a system with high matching degree between auditors and audit and certification tasks from multiple dimensions, and proposes a matching degree evaluation method. Through the established system and method, suitable auditors are automatically selected from thousands of auditors to complete the task of audit and certification of enterprises by the certification body. This method is applicable to quality management systems, environmental management systems, occupational health and safety management systems, etc., preferably quality management systems, etc.

[0083] A comprehensive auditor profiling method based on the combination of dynamic and static "task classification + capability grading" is adopted to form a multi-dimensional capability label for auditors. The capability grading means that the auditor's capabilities change from the static capability grading at the initial employment to the dynamic capability grading after comprehensive evaluation of task application. The multi-dimensional capability label consists of four types of labels: initial static capability grading label, single static capability label, dynamic capability grading label, and single dynamic capability label.

[0084] The types of tasks are mainly in three technical areas, including: certification audit tasks, technical service tasks and technical training tasks.

[0085] The specific process is as follows: for newly employed auditors, static initial grading is carried out according to the auditors' existing professional experience and capabilities. The same level is divided into three levels: A, B, and C. A general training program for the corresponding category is formulated to carry out initial professional training, and then a task trial is carried out. The initial professional training is also continuously carried out during the task trial. The principle of static capability grading is to be capability-oriented and implement professional grading. The same type of profession is divided into three levels: A, B, and C according to the strength of the auditor's profession. A professional grading catalog for auditors is established, mainly based on professional work experience, academic qualifications, and professional titles. The reason for static capability grading is that these three grading details are basically static at the beginning of a stage. The specific standards are shown in Table 1.

[0086] Table 1 Static grading index system for the same type of professional ability

[0087]

[0088] This initial classification refines the professional level of auditors of the same profession, which not only helps auditors to better match tasks, but also helps auditors to improve their professional level in specific fields in a more systematic way. In Table 1, first-line experience, that is, experience in product design, development, process, and production, these people are very familiar with the product, and are familiar with each process of product formation. They are familiar with the technical requirements, control points, common problems, and solutions and prevention methods of each process, so they can grasp the key points and key points in the audit, conduct in-depth and thorough audits, and can find strong problems, which is very helpful for the improvement of the organization and is very beneficial for deepening the audit; second-line experience, that is, experience focusing on management, whether it is the quality control department personnel of the organization or the factory representative, they all supervise and manage the development and production process of the product, are familiar with the product and process, but focus on management; third-line experience, compared with first-line and second-line experience, is not so closely related to the product, or planning, scheduling, measurement, testing, or leadership, user department, local inspection, etc., have a certain understanding of the product, but not very profound.

[0089] Based on the initial static competence classification of auditors, the training program mainly includes general courses and graded courses. General courses are courses related to what auditors should know and audit ability, while graded courses are mainly for supplementary learning of the shortcomings of levels A, B, and C. For example, level A (first-line experience) mainly supplements management courses, level B (second-line experience) mainly supplements professional knowledge, and level C supplements both management and professional courses to achieve multi-level improvement and development. The initial static competence classification of auditors forms the initial static competence classification labels of auditors in the static dimension, and also forms three individual static competence labels such as professional work experience, academic qualifications, and professional titles.

[0090] After multiple rounds of task trials, a comprehensive capability evaluation is conducted. According to the dynamic capability grading principle based on key indicators such as audit performance, the auditors are divided into four levels: I, II, III, and IV. Multi-dimensional capability labels such as performance, quality, and expertise are formed for each auditor, and added to the auditor information database archive to achieve a detailed profile of the personnel. When faced with tasks in different technical fields, the auditor information database automatically retrieves accurate auditor portraits with multi-dimensional capability labels to quickly achieve accurate matching of auditors, as shown in Table 3. In this process, the auditors' capability shortcomings can be found based on the results of the comprehensive capability evaluation and the execution of various types of tasks, and targeted training programs can be customized to carry out professional training for capability improvement, thereby achieving rapid capability improvement.

[0091] The principle of dynamic capability grading is result-oriented and implements comprehensive capability grading. Through annual comprehensive evaluation, full-time and part-time auditors are divided into four levels: 1, 11, III, and IV, as shown in Table 2. The final score of dynamic capability is obtained by multiplying the score of each indicator in Table 3 by the corresponding weight, and then the auditors are divided into four levels according to the final score of dynamic capability. Among them, auditors evaluated as level IV will not continue to be selected for tasks, and will be eliminated through interviews.

[0092] Table 2 Dynamic ability classification content of the same type of major

[0093]

[0094] Table 3 Comprehensive evaluation principles for dynamic capability classification (total score 100)

[0095]

[0096]

[0097] from Figure 3 The contents of multiple dimensions of the auditor's multi-dimensional capability label can be seen in Table 4. Under the hierarchical management model based on the auditor's multi-dimensional capability label, the matching principles of tasks in the three major technical fields are defined, as shown in Table 4. From the task matching principles in Table 4, it can be seen that under the refined management model of auditor grading based on multi-dimensional capability labels, professional auditors with different capabilities can be identified and distinguished. On the one hand, more suitable auditors can be selected according to different types of tasks and different scenarios. On the other hand, the role of leading the collaborative development of the team is fully played. Class A and Class I auditors in the same profession lead other levels of auditors of Class B and C to form an audit group. Through on-site "teaching, helping and guiding", the team's capabilities are effectively improved, which is more conducive to the establishment of a talent echelon.

[0098] Table 4 Task classification and auditor multi-dimensional ability label matching principles

[0099]

[0100]

[0101] Based on the above-mentioned auditor classification and grading principles, as well as the principle of task matching, the certification body has formulated a detailed implementation plan to carry out multiple rounds of application verification work in three major technical fields.

[0102] Take the second-stage audit of a certain enterprise to establish a GJB system as an example. The application scope of this enterprise is mainly microwave power amplifiers (including software). When selecting auditors, the previous auditor information system with only a single level and static professional label was used to manually compare the results of auditor selection with the current audit information system that has established multi-dimensional capability label classification and grading. The old system selected auditors with microwave device and software majors. However, the auditor with multiple professional scopes has the longest working years and is best at other majors than microwave device and software. The new system selected auditors whose main major is microwave device and whose second major is software. Therefore, from the perspective of professional selection, the new system is more accurate.

[0103] Taking a 4-person review team as an example, according to the matching calculation method, the matching degree is as follows:

[0104] ① After the audit, the company's satisfaction evaluation as a user (weight 40%)

[0105] Evaluation: Very satisfied (40 points);

[0106] ② Evaluation of the audit file after the audit is completed (weight 35%)

[0107] Evaluation: Good (28 points);

[0108] ③ Evaluation of the auditor’s profession and product scope selected before the audit (weight 25%)

[0109] The audit team consists of 4 people, including 3 first-level professional auditors and 1 second-level professional auditor.

[0110] Score: 15 points;

[0111] Get the matching degree R,

[0112] R = (40 + 28 + 15) / 100 = 83%;

[0113] It should be noted here that the present invention forms a multi-dimensional capability label for the auditor by performing initial static capability grading and dynamic capability grading on the auditor, and matches the auditor with the type of the task. By performing initial static capability grading and dynamic capability grading on the auditor, the auditor can be matched with the task type more accurately, further improving the quality and efficiency of task execution. The establishment of multi-dimensional capability labels makes the matching process more accurate, and tasks can be reasonably allocated according to the actual situation of the auditor, avoiding the waste of resources caused by capability mismatch. By proposing an evaluation method for the matching degree of the auditor and the task, the matching degree of the auditor and the task is accurately quantified from qualitative, greatly improving the accuracy of the matching, and outputting the compensation point of the auditor matching the type of the corresponding task according to the matching degree, and training the auditor according to the compensation point, and then performing dynamic capability grading on the auditor again and matching the auditor with the type of the task again, so that the dynamic capability evaluation process is iterated repeatedly, and the dynamic capability spirally rises, which greatly improves the intelligence, usability and reliability of the present invention, and greatly expands the application scenarios of the present invention.

[0114] See also Figure 2 This embodiment provides a system for matching auditors with tasks, the system comprising:

[0115] Acquisition module 100: used to acquire the type of tasks to be performed by the auditor and to acquire the initial capability information of the auditor;

[0116] Control module 200: used to perform initial static capability grading of the auditor based on the initial capability information of the auditor; or to perform dynamic capability grading of the auditor after the auditor has performed a task trial; or to form a multi-dimensional capability label of the auditor based on the results of the initial static capability grading and the dynamic capability grading, and match the auditor with the type of the task based on the multi-dimensional capability label of the auditor; or to calculate the degree of matching between the auditor and the type of its corresponding task, output a compensation point for matching the auditor with the type of its corresponding task based on the matching degree, and train the auditor based on the compensation point, and then perform dynamic capability grading on the auditor again and match the auditor with the type of the task again.

[0117] It should be noted here that the present invention forms a multi-dimensional capability label for the auditor by performing initial static capability grading and dynamic capability grading on the auditor, and matches the auditor with the type of the task. By performing initial static capability grading and dynamic capability grading on the auditor, the auditor can be matched with the task type more accurately, further improving the quality and efficiency of task execution. The establishment of multi-dimensional capability labels makes the matching process more accurate, and tasks can be reasonably allocated according to the actual situation of the auditor, avoiding the waste of resources caused by capability mismatch. By proposing an evaluation method for the matching degree of the auditor and the task, the matching degree of the auditor and the task is accurately quantified from qualitative, greatly improving the accuracy of the matching, and outputting the compensation point of the auditor matching the type of the corresponding task according to the matching degree, and training the auditor according to the compensation point, and then performing dynamic capability grading on the auditor again and matching the auditor with the type of the task again, so that the dynamic capability evaluation process is iterated repeatedly, and the dynamic capability spirally rises, which greatly improves the intelligence, usability and reliability of the present invention, and greatly expands the application scenarios of the present invention.

[0118] In a preferred embodiment, the present application further provides an electronic device, the electronic device comprising:

[0119] GPU: Integrating deep learning algorithms, deep learning training is performed when the auditors with a matching degree greater than or equal to the first preset threshold are matched with the types of tasks to be performed. This can achieve forward and reverse deep learning and matching degree calculations. On the one hand, it is the matching of auditor capabilities with tasks; on the other hand, by selecting matching cases with a matching degree higher than 80%, deep learning training can generate capability requirements for the training and development of current auditors, which can also be used for the recruitment capability requirements of newly selected auditors;

[0120] Switch: used to realize information interconnection, the switch includes RJ45 hardware interface;

[0121] Input-output unit: under the control of FPGA, performs input and output, further improving the interaction efficiency between input and output and electronic devices; further, the input-output unit is a comprehensive integrated input-output unit, including multiple input-output devices such as scanners, cameras, microphones, optical drives, printers, etc.).

[0122] A memory; and a processor, wherein the memory stores computer-readable instructions, and when the computer-readable instructions are executed by the processor, the method for intelligently matching auditors with tasks is implemented. The computer device can be broadly defined as a server, a terminal, or any other electronic device with necessary computing and / or processing capabilities. In one embodiment, the computer device may include a processor, a memory, a network interface, a communication interface, etc. connected via a system bus. The processor of the computer device can be used to provide necessary computing, processing, and / or control capabilities. The memory of the computer device may include a non-volatile storage medium and an internal memory. An operating system, a computer program, etc. may be stored in or on the non-volatile storage medium. The internal memory can provide an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The network interface and the communication interface of the computer device can be used to connect and communicate with external devices via a network. When the computer program is executed by the processor, the steps of the method of the present invention are executed.

[0123] It is understandable that through the use of deep learning artificial intelligence algorithms by GPU, through continuous learning and training of high-matching cases, the requirements for different types of high-matching auditors are output, and the carrier is a CD; at the same time, it calculates whether the number of auditors currently required meets the requirement of a matching degree higher than 80%. If the number or quality of existing auditors does not meet the requirement of a matching degree higher than 80%, the corresponding conclusion should be output, and then connected to human resource planning to output the training needs of existing personnel (based on the task situation), as well as the number, major, work background, experience, academic qualifications and other requirements of newly recruited personnel.

[0124] The present invention may be implemented as a computer-readable storage medium having a computer program stored thereon, which causes the steps of the method of an embodiment of the present invention to be executed when executed by a processor. In one embodiment, the computer program is distributed on a plurality of computer devices or processors coupled to a network so that the computer program is stored, accessed and executed in a distributed manner by one or more computer devices or processors. A single method step / operation, or two or more method steps / operations, may be performed by a single computer device or processor or by two or more computer devices or processors. One or more method steps / operations may be performed by one or more computer devices or processors, and one or more other method steps / operations may be performed by one or more other computer devices or processors. One or more computer devices or processors may perform a single method step / operation, or perform two or more method steps / operations.

[0125] It should be noted here that the present invention forms a multi-dimensional capability label for the auditor by performing initial static capability grading and dynamic capability grading on the auditor, and matches the auditor with the type of the task. By performing initial static capability grading and dynamic capability grading on the auditor, the auditor can be matched with the task type more accurately, further improving the quality and efficiency of task execution. The establishment of multi-dimensional capability labels makes the matching process more accurate, and tasks can be reasonably allocated according to the actual situation of the auditor, avoiding the waste of resources caused by capability mismatch. By proposing an evaluation method for the matching degree of the auditor and the task, the matching degree of the auditor and the task is accurately quantified from qualitative, greatly improving the accuracy of the matching, and outputting the compensation point of the auditor matching the type of the corresponding task according to the matching degree, and training the auditor according to the compensation point, and then performing dynamic capability grading on the auditor again and matching the auditor with the type of the task again, so that the dynamic capability evaluation process is iterated repeatedly, and the dynamic capability spirally rises, which greatly improves the intelligence, usability and reliability of the present invention, and greatly expands the application scenarios of the present invention.

[0126] The various technical features described above can be combined arbitrarily. Although all possible combinations of these technical features are not described, any combination of these technical features should be considered to be covered by this specification as long as there is no contradiction in such combination.

[0127] The specific implementation of the present invention described above does not constitute a limitation on the protection scope of the present invention. Any other corresponding changes and modifications made based on the technical concept of the present invention should be included in the protection scope of the claims of the present invention.

Claims

1. A method for intelligently matching auditors with tasks, characterized in that: include: S100, obtaining the type of tasks to be performed by the auditor, and obtaining the initial capability information of the auditor, and performing initial static capability grading on the auditor according to the initial capability information of the auditor; S200, dynamic competency grading of auditors after they have been task-tested; S300, forming a multi-dimensional capability label of the auditor according to the results of the initial static capability grading and the dynamic capability grading, and matching the auditor with the type of the task according to the multi-dimensional capability label of the auditor; S400, calculating the matching degree between the auditor and the type of the corresponding task, outputting the compensation point of the auditor and the type of the corresponding task according to the matching degree, and training the auditor according to the compensation point, and then re-classifying the auditor's dynamic ability and re-matching the auditor with the type of the task.

2. The method for intelligently matching auditors with tasks according to claim 1, characterized in that: The types of tasks include at least the following three: Certification audit tasks, technical service tasks, and technical training tasks.

3. The method for intelligently matching auditors with tasks according to claim 1, characterized in that: The initial static capability grading of the auditors according to the initial capability information of the auditors includes: The initial capability information of the auditor includes multiple single static capability labels. Based on the multiple single static capability labels of each auditor, the auditor is initially evaluated for capability, and then the auditor is initially statically graded to obtain the initial static capability grading label of each auditor.

4. The method for intelligently matching auditors with tasks according to claim 3, characterized in that: After the auditor has completed the task trial, the auditor is dynamically graded, including: After the auditor has conducted a task trial, a weight is set corresponding to each preset indicator. The preset indicators include multiple individual dynamic capability labels. Each auditor is scored according to each individual dynamic capability label to obtain the score of each preset indicator corresponding to each auditor. Based on the weight corresponding to each preset indicator and the score, the auditor is comprehensively evaluated for his or her ability, and then the auditor is dynamically graded to obtain a dynamic capability grading label for each auditor.

5. The method for intelligently matching auditors with tasks according to claim 4, characterized in that: The multi-dimensional capability tags include: Each auditor’s single static capability label, initial static capability grading label, single dynamic capability label, and dynamic capability grading label.

6. The method for intelligently matching auditors with tasks according to claim 5, characterized in that: The matching of the auditor with the type of the task according to the multi-dimensional capability label of the auditor includes: Set specific requirements for the multi-dimensional capability labels corresponding to the types of tasks, establish matching principles for the types of tasks and the multi-dimensional capability labels of auditors, and obtain the types of tasks corresponding to each auditor based on the matching principles for the types of tasks and the multi-dimensional capability labels of auditors.

7. The method for intelligently matching auditors with tasks according to claim 6, characterized in that: The S400 includes: Calculate the matching degree between the auditor and the type of the task corresponding to the auditor, determine whether the matching degree is greater than or equal to a first preset threshold, and determine whether to re-match the task classification corresponding to the auditor based on the determination result.

8. The method for intelligently matching auditors with tasks according to claim 7, characterized in that: The determining whether to re-match the task classification corresponding to the auditor according to the determination result includes: If the matching degree is greater than or equal to a first preset threshold, it is determined not to re-match the type of task corresponding to the auditor; If the matching degree is less than the first preset threshold, it is determined to re-match the type of task corresponding to the auditor, and output the compensation point between the auditor and the type of task corresponding to the auditor. The auditor is trained according to the compensation point, and then the auditor is dynamically capable of being graded again and the auditor is matched again with the type of task until the matching degree is greater than or equal to the first preset threshold.

9. A system for intelligently matching auditors with tasks, characterized in that: include: Acquisition module: used to obtain the types of tasks that the auditor needs to perform and obtain the auditor's initial capability information; Control module: used to perform initial static capability grading of auditors based on the initial capability information of the auditors; or to perform dynamic capability grading of auditors after the auditors have performed task trials; or to form a multi-dimensional capability label of the auditors based on the results of the initial static capability grading and the dynamic capability grading, and match the auditors with the types of the tasks based on the multi-dimensional capability label of the auditors; or to calculate the degree of matching between the auditors and the types of their corresponding tasks, output compensation points for matching between the auditors and the types of their corresponding tasks based on the matching degrees, and train the auditors based on the compensation points, and then perform dynamic capability grading on the auditors again and match the auditors with the types of the tasks again.

10. An electronic device, characterized in that: include: GPU: Integrates deep learning algorithms and conducts deep learning training when the auditors whose matching degree is greater than or equal to the first preset threshold match the types of tasks to be performed; FPGA control module: used to control the input and output units; Switch: used to realize information interconnection; Input and output unit: performs input and output under FPGA control; A memory; and a processor, wherein the memory stores computer-readable instructions, and when the computer-readable instructions are executed by the processor, the method for intelligently matching auditors with tasks according to any one of claims 1 to 8 is implemented.

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