Project team employee-suitable-for-post recommendation method and device

Abstract

The invention relates to the technical field of data analysis and application, in particular to a project team post-suitable employee recommendation method and device, and the method comprises the steps: receiving team demand information of project building and employee information of to-be-evaluated employees, and the team demand information at least comprises target post information; according to the employee information of the to-be-assessed employee, performing matching from a post label model associated with a target post to obtain ability label information of the to-be-assessed employee; according to the ability label information of the to-be-assessed employee, calculating to obtain an appropriate post matching degree corresponding to the to-be-assessed employee; and according to the target post information and the post-suitable matching degree corresponding to the to-be-evaluated employee, determining post-suitable employee recommendation information. According to the method, the employees suitable for the job can be automatically recommended, and the problems of difficult employee recommendation and low efficiency during existing project team establishment are solved.

Description

Technical Field

[0001] The present invention relates to the field of data analysis and application technology, and in particular to a method and device for recommending suitable employees for a project team. Background Art

[0002] With the intensification of market competition and the growing demand for projects, forming the right team for projects has become a key trend for companies to improve their competitiveness and achieve their strategic goals. However, as technology applications become increasingly complex, the matching between project requirements and employee skills becomes more difficult. How to recommend suitable employees to the team has become a major challenge facing companies.

[0003] In the existing technology, internal employees of an enterprise are mainly recommended based on human experience, or recruitment information is issued to screen qualified personnel from a large number of job seekers. It is difficult to quickly match suitable personnel through these methods. For example, recommending internal employees of an enterprise based on human experience may lead to problems such as mismatch between people and positions and human factors affecting the fairness of competition. Screening qualified personnel from job seekers may face problems such as low efficiency in matching personnel and failure of recruited personnel to meet project requirements. Summary of the invention

[0004] The present invention provides a method and device for recommending suitable employees for a project team, which are used to solve the problems of difficulty and low efficiency in recommending employees when forming an existing project team.

[0005] In order to solve the above technical problems, a first aspect of this document provides a method for recommending suitable employees for a project team, the method comprising:

[0006] Receiving team requirement information for project formation and employee information of employees to be evaluated, wherein the team requirement information at least includes target position information;

[0007] According to the employee information of the employee to be evaluated, the ability label information of the employee to be evaluated is obtained by matching from the position label model associated with the target position;

[0008] Calculate the job matching degree of the employee to be evaluated based on the ability label information of the employee to be evaluated;

[0009] Determine the recommended information of suitable employees according to the target position information and the job matching degree of the employee to be evaluated;

[0010] The position label model associated with the target position includes:

[0011] Multi-level capability labels with cascading relationships and corresponding weights, the level of the lowest-level capability label, and the standard coefficient of the highest-level capability label.

[0012] As a further embodiment of this invention, the position label model associated with the position is pre-constructed in the following manner, including:

[0013] Determine a job label model with multi-level capability labels based on the historical work data and historical evaluation data of employees related to the job;

[0014] Dividing the lowest level capability label in the job label model into intervals to obtain the level of the lowest level capability label;

[0015] According to the AHP hierarchical analysis method, weights are assigned to the competence labels at each level of the job label model to obtain a weighted job label model;

[0016] The assigned position label model is determined as the position label model associated with the position.

[0017] As a further embodiment of the present invention, after determining the assigned position label model as the position label model associated with the position, the method includes:

[0018] Obtain the pilot employee information of each position in the pilot project team and the number of employees at each level with the highest level capability label preset for each position;

[0019] According to the pilot employee information of the position in the pilot project team, the capability label information of the pilot employee is obtained by matching from the position label model associated with the position;

[0020] Calculate the level of the highest level of the pilot employee's capability label according to the capability label information of the pilot employee;

[0021] According to the level of the highest competency label of the pilot employee, count the number of employees of each level of the highest competency label that the position already has;

[0022] Compare the number of employees of each level with the highest level competence label of each position and the number of employees of each level with the highest level competence label preset for each position to obtain the number of difference employees;

[0023] If the number of different employees does not meet the preset conditions, the position label model associated with the position is re-determined.

[0024] As a further embodiment of the present invention, the competence label information of the employee to be evaluated includes: competence labels of each level and corresponding weights of the employee to be evaluated, the level of the lowest competence label, and the standard coefficient of the highest competence label of the employee to be evaluated;

[0025] The step of calculating the job matching degree of the employee to be evaluated according to the ability label information of the employee to be evaluated includes:

[0026] According to the level of the N-level competence label of the employee to be evaluated and the weight of the N-level competence label, the level of the N-1-level competence label is calculated, where N is a positive integer greater than 2, and the larger the N, the lower the level;

[0027] Calculate the calculation coefficient of the highest level ability label of the employee to be evaluated according to the level of the highest level ability label of the employee to be evaluated and the weight of the highest level ability label;

[0028] The job matching degree corresponding to the employee to be evaluated is determined according to the calculation coefficient of the highest-level ability label of the employee to be evaluated and the standard coefficient of the highest-level ability label.

[0029] As a further embodiment of the present invention, determining the job matching degree corresponding to the employee to be evaluated according to the calculation coefficient of the highest level ability label of the employee to be evaluated and the standard coefficient of the highest level ability label includes:

[0030] Comparing the calculated coefficient of the highest level competency label of the employee to be evaluated with the standard coefficient of the highest level competency label;

[0031] When the calculation coefficients of the highest-level competence labels of the employee to be evaluated are all greater than or equal to the standard coefficients of the highest-level competence labels, the job matching degree corresponding to the employee to be evaluated is calculated using the following formula:

[0032] Job matching degree = A / B;

[0033] When the calculation coefficient of at least one of the highest-level competence label coefficients of the employee to be evaluated is less than the standard coefficient of the corresponding highest-level competence label, the job matching degree corresponding to the employee to be evaluated is calculated using the following formula: B i ≤A i When B i -A i =0;

[0034] Wherein, A represents the sum of the calculation coefficients of the highest level competence labels of the employees to be evaluated, B represents the sum of the standard coefficients of the highest level competence labels of the employees to be evaluated, n represents the number of the highest level competence labels of the employees to be evaluated, and A i represents the calculation coefficient of the i-th highest level capability label, B i Represents the standard coefficient of the i-th highest level capability label.

[0035] As a further embodiment of the present invention, determining the recommended information of suitable employees according to the target position information and the suitable matching degree of the employee to be evaluated includes:

[0036] Screen out employees to be evaluated whose job matching degree meets the preset threshold;

[0037] The selected employees to be evaluated are sorted according to their job matching degree to obtain a list of employee job matching degrees;

[0038] Obtaining the number of people required for the target position according to the target position information;

[0039] According to the headcount requirement of the target position and the employee job matching list, the recommendation information of the suitable employees is determined.

[0040] A second aspect of the present invention provides a device for recommending suitable employees for a project team, the device comprising:

[0041] A receiving module, used to receive team requirement information for project formation and employee information of employees to be evaluated, wherein the team requirement information at least includes target position information;

[0042] A matching module, used to match the employee information of the employee to be evaluated from the position label model associated with the target position to obtain the ability label information of the employee to be evaluated;

[0043] A calculation module, used to calculate the job matching degree corresponding to the employee to be evaluated according to the ability label information of the employee to be evaluated;

[0044] A suitable employee recommendation module is used to determine suitable employee recommendation information based on the target job information and the suitable job matching degree corresponding to the employee to be evaluated;

[0045] The position label model associated with the target position includes:

[0046] Multi-level capability labels with cascading relationships and corresponding weights, the level of the lowest-level capability label, and the standard coefficient of the highest-level capability label.

[0047] A third aspect of the present invention provides a computer device, including a memory, a processor, and a computer program stored in the memory, wherein when the computer program is executed by the processor, the computer program executes instructions of the method for recommending suitable employees for a project team as described in any of the aforementioned embodiments.

[0048] A fourth aspect of the present invention provides a computer storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor of a computer device, the computer program executes instructions of the method for recommending suitable employees for a project team as described in any of the aforementioned embodiments.

[0049] A fifth aspect of the present invention provides a computer program product, which includes a computer program, and when the computer program is executed by a processor of a computer device, it executes instructions of the method for recommending suitable employees for a project team as described in any of the aforementioned embodiments.

[0050] The method and device for recommending suitable employees for a project team provided in this article calculate the matching degree of people and positions according to different conditions based on the information of internal employees of the enterprise when the enterprise project team is formed, and can obtain reasonable personnel matching results for the enterprise project, so as to recommend highly suitable project members when the enterprise project team is formed, and solve the problem of difficulty in recommending employees when the project team is formed; at the same time, by calculating the matching degree in an automated way and forming the recommendation information of suitable employees, the efficiency of employee recommendation when the enterprise project team is formed is improved.

[0051] In order to make the above and other purposes, features and advantages of this article more obvious and easy to understand, the following specifically cites preferred embodiments and describes them in detail with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] In order to more clearly illustrate the technical solutions in the embodiments of this article or the prior art, the drawings required for use in the embodiments or the prior art descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of this article. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0053] Figure 1 The flowchart of the method for recommending suitable employees for a project team in the embodiment of this article is shown;

[0054] Figure 2 The association relationship diagram between some labels of the job label model of the embodiment of this article is shown;

[0055] Figure 3 A flowchart of constructing a job label model associated with a job in an embodiment of this invention is shown;

[0056] Figure 4 A flowchart of a job label model test for job association in an embodiment of this invention is shown;

[0057] Figure 5 The embodiment of this invention shows a flow chart of calculating the job matching degree corresponding to the employee to be evaluated according to the ability label information of the employee to be evaluated;

[0058] Figure 6 The flowchart of determining the recommended information of suitable employees according to the target position information and the suitable matching degree of the employees to be evaluated in the embodiment of this article is shown;

[0059] Figure 7The structure diagram of the device for recommending suitable employees for the project team of the embodiment of this article is shown;

[0060] Figure 8 A computer device structure diagram of an embodiment of this invention is shown.

[0061] Description of the accompanying symbols:

[0062] 710, receiving module;

[0063] 720, matching module;

[0064] 730. Calculation module;

[0065] 740. Module for recommending suitable employees;

[0066] 802. Computer equipment;

[0067] 804, processor;

[0068] 806. Memory;

[0069] 808, driving mechanism;

[0070] 810, input / output module;

[0071] 812. Input device;

[0072] 814. Output device;

[0073] 816. Presentation equipment;

[0074] 818. Graphical user interface;

[0075] 820, network interface;

[0076] 822, communication link;

[0077] 824. Communication bus. DETAILED DESCRIPTION

[0078] The following will be combined with the drawings in the embodiments of this article to clearly and completely describe the technical solutions in the embodiments of this article. Obviously, the described embodiments are only part of the embodiments of this article, not all of the embodiments. Based on the embodiments of this article, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of this article.

[0079] It should be noted that the terms "first", "second", etc. in the specification and claims of this article and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of this article described here can be implemented in an order other than those illustrated or described here. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, device, product or equipment that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or equipment.

[0080] This specification provides method operation steps as described in the embodiments or flow charts, but more or fewer operation steps may be included based on routine or non-creative work. The order of steps listed in the embodiments is only one way of executing the order of many steps and does not represent the only execution order. When the system or device product is executed in practice, it can be executed in the order of the method shown in the embodiments or the drawings or in parallel.

[0081] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the acquisition, transmission, storage, use and processing of relevant data shall comply with the relevant laws, regulations and standards of relevant countries and regions.

[0082] It should be noted that in the embodiments of the present application, certain software, components, models and other existing solutions in the industry may be mentioned, and they should be regarded as exemplary. Their purpose is only to illustrate the feasibility of implementing the technical solution of the present application, but it does not mean that the applicant has or will necessarily use the solution.

[0083] It should be noted that, to facilitate understanding of the technical content of this article, in some of the embodiments mentioned later in this article, a multi-level capability label consisting of three levels is used as an example. The first-level capability label, second-level capability label, and third-level capability label that appear all represent some labels in the multi-level capability label consisting of three levels, among which the first-level capability label corresponds to the highest-level capability label, the second-level capability label corresponds to the middle-level capability label, and the third-level capability label corresponds to the lowest-level capability label.

[0084] In one embodiment of the present invention, a method for recommending suitable employees for a project team is provided, which is used to solve the problem of difficulty and low efficiency in recommending employees when forming an existing project team.

[0085] Specifically, Figure 1 As shown in the figure, the project team's recommended employee methods include:

[0086] Step 110, receiving team requirement information for project formation and employee information of employees to be evaluated, wherein the team requirement information at least includes target position information;

[0087] Step 120, according to the employee information of the employee to be evaluated, matching the ability label information of the employee to be evaluated from the position label model associated with the target position;

[0088] Step 130, calculating the job matching degree corresponding to the employee to be evaluated according to the ability label information of the employee to be evaluated;

[0089] Step 140, determining the recommended information of suitable employees according to the target job information and the suitable job matching degree of the employee to be evaluated;

[0090] When an enterprise project team is formed, this embodiment calculates the person-job matching degree based on the information of the internal employees of the enterprise, and can obtain reasonable personnel matching results for the enterprise project, thereby recommending highly suitable project members when the enterprise project team is formed, solving the problem of difficulty in recommending employees when the project team is formed; at the same time, by calculating the matching degree in an automated manner and forming the recommendation information of suitable employees, the efficiency of employee recommendation when the enterprise project team is formed is improved.

[0091] In some embodiments of this document, team requirement information includes required positions for the team, target position information, team structure information, etc.; target position information includes position title, position ID, initial screening conditions for the position, number of people required for the position, etc.; employee information of employees to be evaluated includes personal experience, work experience, scope of work, work quality, project experience, project quality, personal qualifications, personal practice, etc.

[0092] In some embodiments of this invention, the positions required by the team include project manager, demand analyst, software architect, development engineer, database administrator, etc. Some positions and their initial screening conditions are shown in Table 1 below:

[0093] Table 1

[0094]

[0095]

[0096] In some embodiments of this document, the project manager qualification requirement in the initial screening conditions for the project manager position is to have a second-level project manager qualification; the technical field requirement in the initial screening conditions for the development engineer position is to include JAVA, and the busyness requirement is that no more than 3 parallel tasks are being processed; the database technology stack level requirement in the initial screening conditions for the database administrator position is that the database technology stack level reaches level 3.

[0097] In some embodiments of this invention, the job label model associated with the target job includes multi-level capability labels with cascading relationships and corresponding weights, the level of the lowest-level capability label, and the standard coefficient of the highest-level capability label. For the convenience of explanation, a partial association relationship of the multi-level capability labels consisting of three levels is shown, such as Figure 2 As shown; among them, the first-level capability label corresponds to the highest-level capability label, the second-level capability label corresponds to the middle-level capability label between the highest-level and lowest-level capability labels, and the third-level capability label corresponds to the lowest-level capability label.

[0098] In some embodiments of the present invention, the ability labels include general ability labels and position ability labels. The general ability labels can be common to all positions, wherein the first-level general ability labels include communication ability, learning ability, execution ability, responsibility, initiative, etc., and the first-level position ability labels are divided into different labels according to different positions; the employee basic data corresponding to each first-level ability label is analyzed to obtain a third-level ability label representing the employee basic data, and the second-level ability label is obtained by aggregating the third-level ability labels. When the third-level ability label cannot be aggregated, the third-level ability label is directly adjusted to the second-level ability label.

[0099] In some embodiments of the present invention, the basic data of employees corresponding to the execution ability label in the first-level general ability label, such as the task completion punctuality rate and the problem solving time, are used as the third-level general ability label, and are aggregated to obtain the corresponding second-level general ability label - work execution status; the basic data of employees corresponding to the communication ability in the first-level general ability label, such as the number of led projects, the level of led projects, and the complexity of led projects, are used as the third-level general ability label, and are aggregated to obtain the corresponding second-level general ability label - work communication experience.

[0100] In some embodiments of this invention, the first-level job competency label of the development engineer position includes professional basic knowledge, demand analysis ability, architecture design ability, and development ability. The employee basic data corresponding to the development competency label includes the number of tasks, the number of git change lines, the number of applications involved, the number of systems involved, the defect rate, and the production event rate. As the third-level job competency label, the corresponding second-level general competency label is aggregated to obtain work experience (number of tasks, number of git change lines), scope of work (number of applications involved, number of systems involved), and work quality (defect rate, production event rate). The competency label of the development engineer position includes but is not limited to the above content.

[0101] In some embodiments of the present invention, enterprise employees are screened according to initial screening conditions of the position to obtain employee information of employees to be evaluated corresponding to the position, and after receiving the employee information of the employees to be evaluated, the position label model associated with the position name or position ID is matched to calculate the ability label information of the employees to be evaluated, and the job matching degree corresponding to the employees to be evaluated is calculated based on the ability label information of the employees to be evaluated, and the recommendation information of suitable employees is determined in combination with the job matching degree and the target position information.

[0102] In one embodiment of this invention, Figure 3 As shown, the position label model associated with the position is pre-built in the following ways, including:

[0103] Step 310, determining a position label model with multi-level capability labels based on historical work data and historical evaluation data of employees related to the position;

[0104] Step 320, dividing the lowest level capability label in the job label model into intervals to obtain the level of the lowest level capability label;

[0105] Step 330, weighting the competence labels at each level of the job label model according to the AHP analytic hierarchy process to obtain a weighted job label model;

[0106] Step 340: determine the assigned position label model as the position label model associated with the position.

[0107] This embodiment constructs a job label model associated with positions, and divides the lowest-level ability labels in the model into intervals to obtain different levels, so that the abilities corresponding to the lowest-level ability labels of different employees can be distinguished. The model labels are weighted through the AHP hierarchical analysis method to distinguish the importance of labels at the same level and obtain a reasonable job label model for the target position.

[0108] In some embodiments of the present invention, the historical work data of position-related employees include but are not limited to the number of led projects, the level of led projects, the complexity of led projects, the on-time rate of task completion, the time to solve problems, the data of relevant knowledge websites or competition data inside and outside the company, the number of tasks, the number of git change lines, the number of applications involved, the number of systems involved, the defect rate, the production event rate and other basic data. The historical evaluation data is the score of the historical work data. The first-level capability label of the position is obtained according to the historical work data of the position-related employees, and then the second-level capability label and the third-level capability label are obtained according to the method of the above embodiment.

[0109] In some embodiments of the present invention, the three-level capability label is divided into intervals to obtain the levels of the three-level capability label. The employee information of the employee to be evaluated is mapped to different levels of the three-level capability label to distinguish the employee's capabilities. The interval division methods include but are not limited to the following:

[0110] (1) Enumeration method: For example, if a position has relevant certificates, the value can be directly enumerated as yes / no, divided into level 0 and level 1. For example, if an employee has education background, the value can be directly enumerated as college / bachelor's degree / master's degree / doctorate, divided into level 0, level 1, level 2 and level 3.

[0111] (2) Equal-value method: For continuous data, such as the number of tasks and the number of git changes, the data can be divided based on 1 / 5, 2 / 5, 3 / 5, and 4 / 5 of the highest value among all employees, resulting in five segments: [0, 1 / 5 highest value), [1 / 5 highest value, 2 / 5 highest value), [2 / 5 highest value, 3 / 5 highest value), [3 / 5 highest value, 4 / 5 highest value), and [4 / 5 highest value, 5 / 5 highest value], which are divided into level 0, level 1, level 2, level 3, and level 4.

[0112] (3) Average method: For continuous data, such as the number of tasks and the number of git changes, the average value of all employees can be calculated. At this time, based on the average value / 2, the average value, the data is divided into three sections: [0, average value / 2), [average value / 2, average value), and [average value, highest value], which are divided into level 0, level 1, and level 2.

[0113] (4) Median method: For continuous data, such as the number of tasks and the number of git changes, the median of all employees can be calculated. At this time, the data is divided into three sections based on median / 2, median: [0, median / 2), [median / 2, median), and [median, highest value], which are divided into level 0, level 1, and level 2.

[0114] (5) Fixed value method: The numerical value corresponding to the full-level standard of a certain data item is obtained through evaluation, and this numerical value is used to replace the highest value in methods (2), (3), and (4) to obtain the corresponding grade classification.

[0115] In some embodiments of this invention, weights are assigned to the competence labels of the job label model according to the AHP hierarchical analysis method. The weight assignment method of competence labels at all levels is the same. The following is the weight assignment process of the first-level competence label of job A:

[0116] (1) Construct a basic pairwise comparison matrix B. For position A, corresponding to the five first-level competency labels A1-A5, n pairwise comparison matrices B are obtained through n internal experts or managers of the enterprise: B1, B2, …, B n ; The contents of the pairwise comparison matrix B1 are shown in Table 2 below:

[0117] Table 2

[0118]

[0119]

[0120] The meanings of the above table are shown in Table 3 below:

[0121] Table 3

[0122] Factor i is better than factor j Quantization value Equally important 1 Slightly important 3 Strong and important 5 Strongly important 7 Extremely important 9 The middle value of two adjacent judgments 2，4，6，8

[0123] (2) Construct the final pairwise comparison matrix R. n Stored as array B1, B2, ..., B n , by the majority method from the array B1, B2, ..., B n Filter the data to obtain the final pairwise comparison matrix R. The process is as follows:

[0124] ① Construction<key,value> Data structure in the form of map;

[0125] ②Traverse all arrays B and add each to the map If all key values ​​in the map are not equal to Then add Enter the map; if there is a key value equal to Then the corresponding value increases by 1; is the key value, B i is the i-th B array, (j,k) represents the value of the j-th row and k-th column of the array;

[0126] ③ Find the Key value corresponding to the maximum value in the map as the i-th value of the final pairwise comparison matrix R. If there are multiple corresponding Key values, correct them by using the mean method or other methods, which are not limited in this article.

[0127] ④ Perform steps ②-③ for all values ​​of all arrays B to obtain the final pairwise comparison matrix R. The content of the pairwise comparison matrix R is shown in Table 4 below:

[0128] Table 4

[0129]

[0130]

[0131] (3) Weight calculation. Calculate the maximum eigenvalue and weight vector of the pairwise comparison matrix R. The maximum eigenvalue is 5.073, and the weight vector is (0.2636, 0.4758, 0.0538, 0.0981, 0.1087) T ,The calculated consistency index is 0.018. From the table, we know that the random consistency index is 1.12, so the consistency ratio is 0.016, so the consistency test is passed.

[0132] Through the above steps, the weights of the first-level capability labels A1-A5 are obtained as 0.2636, 0.4758, 0.0538, 0.0981, and 0.1087.

[0133] In one embodiment of this invention, Figure 4 As shown, after the assigned job label model is determined as the job label model associated with the job, it includes:

[0134] Step 410, obtaining pilot employee information of each position in the pilot project team and the number of employees at each level with the highest level capability label preset for each position;

[0135] Step 420, according to the pilot employee information of the position in the pilot project team, the capability label information of the pilot employee is matched from the position label model associated with the position;

[0136] Step 430: Calculate the level of the highest level capability label of the pilot employee according to the capability label information of the pilot employee.

[0137] Step 440, according to the level of the highest level competence label of the pilot employee, count the number of employees of each level of the highest level competence label existing in the position;

[0138] Step 450, comparing the number of employees of each level with the highest level competence label of each position and the number of employees of each level with the highest level competence label preset for each position, to obtain the number of employees with differences;

[0139] Step 460: If the number of employees with the difference does not meet the preset condition, the position label model associated with the position is re-determined.

[0140] This embodiment obtains the distribution of the number of people at each level of the highest-level capability label for each position in the pilot project team by matching the position label model, compares it with the preset distribution number to evaluate the model effect, and continuously iterates and optimizes the model until the preset conditions are met.

[0141] In some embodiments of the present invention, a pilot project team is formed through pilot employees, work data of the pilot project team over a period of time is collected, and updated employee information of each pilot employee in the pilot project team is obtained. After matching the position label model associated with the position, the first-level capability label level of each pilot employee in the pilot project team is calculated, and the first-level capability label level of each pilot employee in the pilot project team is rounded. The rounding method can be rounding down or other methods, which are not limited in this article; after rounding, the number of people with each level of the first-level capability labels in each position in the pilot project team is obtained by statistics, for example, the pilot employees are all distributed at levels 2 / 3 / 4, and the corresponding number of people is A1 / A2 / A3.

[0142] The updated employee information of each pilot employee in the pilot project team is evaluated by enterprise experts or managers. According to the pilot employee grade distribution obtained by the above calculation, the pilot employees are also divided into levels 2 / 3 / 4, and the number of people at each level of the preset first-level capability label for each position in the pilot project team is obtained, and the corresponding number is B1 / B2 / B3.

[0143] By comparing the number of people distributed at each level of the existing first-level capability label with the number of people distributed at each level of the preset first-level capability label, we can get the difference in the number of employees. The difference in the number of employees at levels 2 / 3 / 4 is C1 / C2 / C3, respectively, where C1 = |A1-B1|, C2 = |A2-B2|, C3 = |A3-B3|, and “||” represents the absolute value.

[0144] At this time, we get D = (C1 + C2 + C3) / (A1 + A2 + A3), and judge whether D meets the preset condition. The preset condition can be 0.15 (that is, the ratio of the number of difference employees to the total number of pilot employees of the pilot project team is 15%). When D is less than the preset condition of 0.15, it is satisfied. The preset condition can also be other values, which are not limited in this article. When D does not meet the preset condition, the job label model associated with the position will be re-classified into three-level capability labels, or the model will be adjusted in combination with the data source rules of the actual optimization model, and the number of people distributed at each level of the existing first-level capability labels will be recalculated, and it will be continuously iterated until D meets the preset condition. The way to re-classify the levels includes but is not limited to the following:

[0145] (1) Adjustment of interval value methods, such as changing the median method to the mean method or adopting the fixed value method.

[0146] (2) Adjustment of the interval value selection method: For example, instead of using the median or median / 2 as the value boundaries, a more flexible set of multiple percentage medians can be used as the boundaries.

[0147] In the subsequent application of the model, the above method can also be used for real-time optimization to continuously improve the model performance.

[0148] In one embodiment of this invention, Figure 5 As shown, according to the ability label information of the employee to be evaluated, the job matching degree corresponding to the employee to be evaluated is calculated, including:

[0149] Step 510, calculating the level of the N-1 level capability label according to the level of the N level capability label of the employee to be evaluated and the weight of the N level capability label, where N is a positive integer greater than 2, and the larger N is, the lower the level is;

[0150] Step 520, calculating a calculation coefficient of the highest level capability label of the employee to be evaluated according to the level of the highest level capability label of the employee to be evaluated and the weight of the highest level capability label;

[0151] Step 530, determining the job matching degree corresponding to the employee to be evaluated according to the calculation coefficient of the highest level ability label of the employee to be evaluated and the standard coefficient of the highest level ability label.

[0152] This embodiment calculates the calculation coefficient of the highest-level ability label layer by layer through the level of the lowest-level ability label of the employee to be evaluated and the weight of the lowest-level ability label, and determines the job matching degree corresponding to the evaluated employee based on the calculation coefficient of the highest-level ability label and the standard coefficient of the highest-level ability label, thereby obtaining reference information for recommending suitable employees.

[0153] In some embodiments of the present invention, the competence label information of the employee to be evaluated includes: competence labels of each level and corresponding weights of the employee to be evaluated, the level of the lowest level competence label, and the standard coefficient of the highest level competence label of the employee to be evaluated.

[0154] In some embodiments of the present invention, the weight of the first-level capability label 1 of an employee to be evaluated is α1, and the first-level capability label 1 corresponds to the second-level capability label 1, the second-level capability label 2, and the second-level capability label 3.

[0155] The weight of the second-level capability label 1 is β1, the weight of the second-level capability label 2 is β2, and the weight of the second-level capability label 3 is β3. The second-level capability label 1 corresponds to the third-level capability label 1, the third-level capability label 2, and the third-level capability label 3.

[0156] The level of the third-level capability label 1 is E1, the level of the third-level capability label 2 is E2, the level of the third-level capability label 3 is E3, the weight of the third-level capability label 1 is γ1, the weight of the third-level capability label 2 is γ2, and the weight of the third-level capability label 3 is γ3.

[0157] The level of the second-level capability label 1 is calculated as W1 = E1 × γ1 + E2 × γ2 + E3 × γ3. Similarly, the level of the second-level capability label 2 is W2, and the level of the second-level capability label 3 is W3. The level of the first-level capability label 1 is calculated as Q1 = W1 × β1 + W2 × β2 + W3 × β3. The calculation coefficient of the first-level capability label 1 is A1 = Q1 × α1. Similarly, the calculation coefficients of other first-level capability labels can also be obtained. The standard coefficient of the first-level capability label 1 is pre-set by enterprise experts or managers after evaluation. The standard coefficient of the first-level capability label 1 here is B1.

[0158] In one embodiment of the present invention, determining the job matching degree corresponding to the employee to be evaluated according to the calculation coefficient of the highest level ability label of the employee to be evaluated and the standard coefficient of the highest level ability label includes:

[0159] Step 531, comparing the calculation coefficient of the highest level competence label of the employee to be evaluated with the standard coefficient of the highest level competence label;

[0160] Step 532: When the calculation coefficients of the highest-level competence labels of the employee to be evaluated are all greater than or equal to the standard coefficients of the highest-level competence labels, the job matching degree corresponding to the employee to be evaluated is calculated using the following formula:

[0161] Job matching degree = A / B;

[0162] Step 533: When the calculation coefficient of at least one of the highest-level competence label coefficients of the employee to be evaluated is less than the standard coefficient of the corresponding highest-level competence label, the job matching degree corresponding to the employee to be evaluated is calculated using the following formula: When B i -A i =0;

[0163] Wherein, A represents the sum of the calculation coefficients of the highest level competence labels of the employees to be evaluated, B represents the sum of the standard coefficients of the highest level competence labels of the employees to be evaluated, n represents the number of the highest level competence labels of the employees to be evaluated, and A i represents the calculation coefficient of the i-th highest level capability label, B i Represents the standard coefficient of the i-th highest level capability label.

[0164] This embodiment compares the calculation coefficient of the highest-level capability label and the standard coefficient of the highest-level capability label to obtain two matching degree calculation formulas, which are applicable to two different situations:

[0165] When the calculation coefficients of all the highest-level ability labels of the employee to be evaluated meet (are greater than or equal to) the corresponding standard coefficients, it is considered that all the qualities and abilities of the employee meet the requirements, and the job matching degree of the employee can reach 100% or above. At this time, the job matching degree is calculated by the calculation method of job matching degree = A / B.

[0166] If the calculation coefficient of a certain highest-level competency label of an employee to be evaluated does not meet (is less than) the corresponding standard coefficient, it is considered that some of the employee's qualities and abilities do not meet the requirements, and the employee's job matching degree cannot reach 100%. The calculation method of job matching degree is to calculate the value of B i ≤A i When B i -A i =0; B i >A i When B i -A i>0; therefore, The job matching degree obtained must be less than 100%.

[0167] In some embodiments of the present invention, the standard coefficients of the first-level capability label corresponding to position 1 are a1=2.00, a2=1.50, a3=1.80, a4=2.10, and a5=2.20; the standard coefficients of the first-level capability label corresponding to the employee 1 to be evaluated in position 1 are b1=2.25, b2=1.80, b3=2.12, b4=2.46, and b5=2.33; the standard coefficients of the first-level capability label corresponding to the employee 2 to be evaluated in position 1 are c1=3.17 and c2=1.51 , c3=1.54, c4=2.24, c5=2.32; the first-level competence label standard coefficients corresponding to the employee 3 to be evaluated in position 1 are d1=1.76, d2=3.63, d3=2.41, d4=1.88, d5=2.26; all the qualities and abilities of employee 1 meet the requirements, and the suitable job matching degree is calculated by the method of suitable job matching degree=A / B, and the suitable job matching degree of employee 1 is obtained as 1.1417 (114.17%); some qualities and abilities of employees 2 and 3 do not meet the requirements, Calculated in this way, the job matching degree of employee 2 = 0.9729 (97.29%), and the job matching degree of employee 3 = 0.9521 (95.21%).

[0168] In one embodiment of this invention, Figure 6 As shown, according to the target position information and the job matching degree corresponding to the employee to be evaluated, the recommended information of the suitable employee is determined, including:

[0169] Step 610, screening out the employees to be evaluated whose job matching degree meets the preset threshold;

[0170] Step 620, sorting the screened employees to be evaluated according to their job matching degree to obtain an employee job matching degree list;

[0171] Step 630, obtaining the number of people required for the target position according to the target position information;

[0172] Step 640: Determine the recommended information of the suitable employees according to the headcount requirement of the target position and the employee suitable job matching list.

[0173] This embodiment screens and sorts the employees to be evaluated according to their job matching degrees to obtain a job matching degree list, and automatically recommends employees according to the number of people required for users to choose, which greatly improves the efficiency of employee recommendation when forming a project team.

[0174] In some embodiments of this document, the preset threshold that the job matching degree needs to meet can be selected according to actual needs and is not limited in this document. When an employee's degree is below the preset threshold, it is considered unreasonable to regard the employee as a project member and is not recommended.

[0175] In some embodiments of this article, the number of people required for position 2 is 3. At this time, the job matching list of position 2 can retain the number of recommended employees in proportion. The ratio can be 1:2, 1:3, 1:4, etc., which is not limited in this article. It can also be set according to user needs and selected according to actual conditions. This article does not limit it.

[0176] In some embodiments of the present invention, the employees in the job matching degree list are arranged in descending order according to the job matching degree, and the recommendation information of suitable employees is determined based on the number of job requirements. The recommendation information of suitable employees includes the recommended employee number, ID, name, gender, age, personal experience, work experience, scope of work, work quality, project experience, project quality, personal qualifications, personal practice and other information.

[0177] Based on the same inventive concept, this article also provides a device for recommending suitable employees for a project team, as described in the following embodiments. Since the principle of solving the problem by the device for recommending suitable employees for a project team is similar to that of the method for recommending suitable employees for a project team, the implementation of the device for recommending suitable employees for a project team can refer to the method for recommending suitable employees for a project team, and the repeated parts will not be repeated.

[0178] Specifically, Figure 7 As shown, the recommended devices for suitable employees for the project team include:

[0179] A receiving module 710 is used to receive team requirement information for project formation and employee information of employees to be evaluated, wherein the team requirement information at least includes target position information;

[0180] A matching module 720 is used to match the employee information of the employee to be evaluated from the position label model associated with the target position to obtain the ability label information of the employee to be evaluated;

[0181] A calculation module 730 is used to calculate the job matching degree corresponding to the employee to be evaluated according to the ability label information of the employee to be evaluated;

[0182] The suitable employee recommendation module 740 is used to determine the suitable employee recommendation information according to the target job information and the suitable job matching degree corresponding to the employee to be evaluated;

[0183] The position label model associated with the target position includes:

[0184] Multi-level capability labels with cascading relationships and corresponding weights, the level of the lowest-level capability label, and the standard coefficient of the highest-level capability label.

[0185] When an enterprise project team is formed, this embodiment calculates the person-job matching degree based on the information of the internal employees of the enterprise, and can obtain reasonable personnel matching results for the enterprise project, thereby recommending highly suitable project members when the enterprise project team is formed, solving the problem of difficulty in recommending employees when the project team is formed; at the same time, by calculating the matching degree in an automated manner and forming the recommendation information of suitable employees, the efficiency of employee recommendation when the enterprise project team is formed is improved.

[0186] The method and device for recommending suitable employees for a project team provided in this article calculate the matching degree of people and positions according to different conditions based on the information of internal employees of the enterprise when the enterprise project team is formed, and can obtain reasonable personnel matching results for the enterprise project, so as to recommend highly suitable project members when the enterprise project team is formed, and solve the problem of difficulty in recommending employees when the project team is formed; at the same time, by calculating the matching degree in an automated way and forming the recommendation information of suitable employees, the efficiency of employee recommendation when the enterprise project team is formed is improved.

[0187] In one embodiment of the present invention, a computer device is also provided for implementing the method described in any of the above embodiments, such as Figure 8 The schematic diagram of the structure of the node of the embodiment of this article is shown. In this embodiment, the structure of the node in the side chain network and the node in the main chain network is described, which may include a relay node, a decision maker node or other functional nodes. The node is referred to as a computer device in this embodiment. The computer device 802 may include one or more processors 804, such as one or more central processing units (CPUs), and each processing unit may implement one or more hardware threads. The computer device 802 may also include any memory 806, which is used to store any kind of information such as code, settings, data, etc. Non-limiting, for example, the memory 806 may include any one or more combinations of the following: any type of RAM, any type of ROM, flash memory device, hard disk, optical disk, etc. More generally, any memory can use any technology to store information. Further, any memory can provide volatile or non-volatile retention of information. Further, any memory can represent a fixed or removable component of the computer device 802. In one case, when the processor 804 executes an associated instruction stored in any memory or a combination of memories, the computer device 802 can perform any operation of the associated instruction. The computer device 802 also includes one or more drive mechanisms 808 for interacting with any storage, such as a hard disk drive mechanism, an optical disk drive mechanism, etc.

[0188] The computer device 802 may also include an input / output module 810 (I / O) for receiving various inputs (via input devices 812) and for providing various outputs (via output devices 814). A specific output mechanism may include a presentation device 816 and an associated graphical user interface (GUI) 818. In other embodiments, the input / output module 810 (I / O), the input device 812, and the output device 814 may not be included, and the computer device 802 may be used as a computer device in a network. The computer device 802 may also include one or more network interfaces 820 for exchanging data with other devices via one or more communication links 822. One or more communication buses 824 couple the components described above together.

[0189] The communication link 822 may be implemented in any manner, for example, through a local area network, a wide area network (e.g., the Internet), a point-to-point connection, etc., or any combination thereof. The communication link 822 may include any combination of hardwired links, wireless links, routers, gateway functions, name servers, etc. governed by any protocol or combination of protocols.

[0190] Corresponds to Figure 1 , Figure 3-Figure 6 The method in this article also provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the steps of the above method are executed.

[0191] The embodiment of the present invention also provides a computer readable instruction, wherein when the processor executes the instruction, the program therein causes the processor to execute the following Figure 1 , Figure 3-Figure 6 The method shown.

[0192] It should be understood that in the various embodiments of this document, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this document.

[0193] It should also be understood that in the embodiments of this article, the term "and / or" is only a description of the association relationship of the associated objects, indicating that three relationships may exist. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " in this article generally indicates that the associated objects before and after are in an "or" relationship.

[0194] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computer software, or a combination of the two. In order to clearly illustrate the interchangeability of hardware and software, the composition and steps of each example have been generally described in terms of function in the above description. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this article.

[0195] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0196] In the several embodiments provided herein, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic, for example, the division of the units is only a logical function division, and there may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interfaces, devices or units, or can be electrical, mechanical or other forms of connection.

[0197] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the embodiments of this article.

[0198] In addition, each functional unit in each embodiment of this invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above integrated unit may be implemented in the form of hardware or in the form of software functional unit.

[0199] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this article is essentially or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including a number of instructions to enable a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of this article. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk and other media that can store program codes.

[0200] Specific embodiments are used in this article to illustrate the principles and implementation methods of this article. The description of the above embodiments is only used to help understand the methods and core ideas of this article. At the same time, for general technicians in this field, according to the ideas of this article, there will be changes in the specific implementation methods and application scopes. In summary, the content of this specification should not be understood as a limitation on this article.

Claims

1. A method for recommending suitable employees for a project team, characterized in that: include: Receiving team requirement information for project formation and employee information of employees to be evaluated, wherein the team requirement information at least includes target position information; According to the employee information of the employee to be evaluated, the ability label information of the employee to be evaluated is obtained by matching from the position label model associated with the target position; Calculate the job matching degree of the employee to be evaluated based on the ability label information of the employee to be evaluated; Determine the recommended information of suitable employees according to the target position information and the job matching degree of the employee to be evaluated; The position label model associated with the target position includes: Multi-level capability labels with cascading relationships and corresponding weights, the level of the lowest-level capability label, and the standard coefficient of the highest-level capability label.

2. The method according to claim 1, characterized in that The position label model associated with the position is pre-built in the following ways, including: Determine a job label model with multi-level capability labels based on the historical work data and historical evaluation data of employees related to the job; Dividing the lowest level capability label in the job label model into intervals to obtain the level of the lowest level capability label; According to the AHP hierarchical analysis method, weights are assigned to the competence labels at each level of the job label model to obtain a weighted job label model; The assigned position label model is determined as the position label model associated with the position.

3. The method according to claim 2, characterized in that After determining the assigned position label model as the position label model associated with the position, the method includes: Obtain the pilot employee information of each position in the pilot project team and the number of employees at each level with the highest level capability label preset for each position; According to the pilot employee information of the position in the pilot project team, the capability label information of the pilot employee is obtained by matching from the position label model associated with the position; Calculate the level of the highest level of the pilot employee's capability label according to the capability label information of the pilot employee; According to the level of the highest competency label of the pilot employee, count the number of employees of each level of the highest competency label that the position already has; Compare the number of employees of each level with the highest level competence label of each position and the number of employees of each level with the highest level competence label preset for each position to obtain the number of difference employees; If the number of employees with the difference does not meet the preset conditions, the position label model associated with the position is re-determined.

4. The method according to claim 1, characterized in that The competency label information of the employee to be evaluated includes: competency labels of each level and corresponding weights of the employee to be evaluated, the level of the lowest competency label, and the standard coefficient of the highest competency label of the employee to be evaluated; The step of calculating the job matching degree of the employee to be evaluated according to the ability label information of the employee to be evaluated includes: According to the level of the N-level competence label of the employee to be evaluated and the weight of the N-level competence label, the level of the N-1-level competence label is calculated, where N is a positive integer greater than 2, and the larger the N, the lower the level; Calculate the calculation coefficient of the highest level ability label of the employee to be evaluated according to the level of the highest level ability label of the employee to be evaluated and the weight of the highest level ability label; The job matching degree corresponding to the employee to be evaluated is determined according to the calculation coefficient of the highest-level ability label of the employee to be evaluated and the standard coefficient of the highest-level ability label.

5. The method according to claim 4, characterized in that The determining the job matching degree corresponding to the employee to be evaluated according to the calculation coefficient of the highest level ability label of the employee to be evaluated and the standard coefficient of the highest level ability label includes: Comparing the calculated coefficient of the highest level competency label of the employee to be evaluated with the standard coefficient of the highest level competency label; When the calculation coefficients of the highest-level competence labels of the employee to be evaluated are all greater than or equal to the standard coefficients of the highest-level competence labels, the job matching degree corresponding to the employee to be evaluated is calculated using the following formula: Job matching degree = A / B; When the calculation coefficient of at least one of the highest-level competence label coefficients of the employee to be evaluated is less than the standard coefficient of the corresponding highest-level competence label, the job matching degree corresponding to the employee to be evaluated is calculated using the following formula: B i ≤A i When B i -A i =0; Wherein, A represents the sum of the calculation coefficients of the highest level competence labels of the employees to be evaluated, B represents the sum of the standard coefficients of the highest level competence labels of the employees to be evaluated, n represents the number of the highest level competence labels of the employees to be evaluated, and A i represents the calculation coefficient of the i-th highest level capability label, B i Represents the standard coefficient of the i-th highest level capability label.

6. The method according to claim 1, characterized in that The step of determining the recommended information of suitable employees according to the target position information and the suitable matching degree of the employee to be evaluated includes: Screen out employees to be evaluated whose job matching degree meets the preset threshold; The selected employees to be evaluated are sorted according to their job matching degree to obtain a list of employee job matching degrees; Obtaining the number of people required for the target position according to the target position information; According to the headcount requirement of the target position and the employee job matching list, the recommendation information of the suitable employees is determined.

7. A device for recommending suitable employees for a project team, characterized in that: include: A receiving module, used to receive team requirement information for project formation and employee information of employees to be evaluated, wherein the team requirement information at least includes target position information; A matching module, used to match the employee information of the employee to be evaluated from the position label model associated with the target position to obtain the ability label information of the employee to be evaluated; A calculation module, used to calculate the job matching degree corresponding to the employee to be evaluated according to the ability label information of the employee to be evaluated; A suitable employee recommendation module is used to determine suitable employee recommendation information based on the target job information and the suitable job matching degree corresponding to the employee to be evaluated; The position label model associated with the target position includes: Multi-level capability labels with cascading relationships and corresponding weights, the level of the lowest-level capability label, and the standard coefficient of the highest-level capability label.

8. A computer 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, the method according to any one of claims 1 to 6 is implemented.

9. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor of a computer device, the method according to any one of claims 1 to 6 is implemented.

10. A computer program product, comprising a computer program, characterized in that: When the computer program is executed by a processor of a computer device, the method according to any one of claims 1 to 6 is implemented.

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