Human resource allocation method and device

Abstract

The present application provides a method and apparatus for allocating human resources, which can be used in the field of artificial intelligence technology. The method comprises: obtaining a project data group for each of a plurality of first personnel to be assigned; determining an evaluation result for each first personnel to be assigned based on each project data group and a preset personnel evaluation model, and selecting the first personnel to be assigned with an excellent evaluation result as the second personnel to be assigned; and determining a target personnel to be assigned to the target development project from among the second personnel to be assigned based on the daily project workload of the target development project and the standard daily workload of each second personnel to be assigned. The present application can improve the accuracy and efficiency of human resource allocation, thereby improving the efficiency and accuracy of project development.

Description

Technical Field

[0001] The present application relates to the field of artificial intelligence technology, and in particular to a method and device for allocating human resources. Background Art

[0002] With the rapid development of computer technology, financial institutions are increasingly relying on computer software to meet relevant business needs. The demand for software development is increasing, and more and more software developers are needed.

[0003] Currently, large financial institutions have a large number of project demands and generally cooperate with outsourcing companies to recruit a large number of external developers to carry out software development work. However, the development quality of external developers varies greatly and is difficult to evaluate. In addition, the skills and business proficiency of developers required for each project are different. For a new project, how to quickly recommend suitable candidates from a large number of external developers to achieve rapid pipeline development is an urgent problem that needs to be solved in the software development of large financial institutions. Summary of the Invention

[0004] In response to the problems in the prior art, the present application proposes a human resource allocation method and device, which can improve the accuracy and efficiency of human resource allocation, and thus improve the efficiency and accuracy of project development.

[0005] In order to solve the above technical problems, this application provides the following technical solutions:

[0006] In a first aspect, the present application provides a method for allocating human resources, comprising:

[0007] Obtaining respective project data groups of a plurality of first to-be-assigned personnel;

[0008] Determine the evaluation results of each first candidate for assignment based on each project data group and a preset personnel evaluation model, and select the first candidate for assignment with an excellent evaluation result as the second candidate for assignment;

[0009] According to the daily project task volume of the target development project and the standard daily workload of each second person to be assigned, the target person to be assigned to the target development project is determined from among the second persons to be assigned.

[0010] Furthermore, before determining the evaluation result of each first to-be-assigned person according to each project data group and the preset person evaluation model, the method further includes:

[0011] Obtaining a historical sample set, the historical sample set including: multiple groups of historical project data and actual evaluation results corresponding to each group of historical project data;

[0012] The historical sample set is used to train the gradient boosting decision tree model to obtain the personnel evaluation model.

[0013] Furthermore, before the step of calculating the daily workload of the target development project and the standard daily workload of each second person to be assigned, the method further includes:

[0014] From the preset personnel portrait data table, the standard daily workload corresponding to the personnel number of each second person to be assigned is obtained, and each group of project data groups includes: the personnel number of the corresponding first person to be assigned.

[0015] Furthermore, before the step of calculating the daily workload of the target development project and the standard daily workload of each second person to be assigned, the method further includes:

[0016] According to the coding start time, coding end time and total project task volume of the target development project, the project daily task volume of the target development project is obtained.

[0017] Furthermore, determining the target personnel to be assigned to the target development project from the second personnel to be assigned based on the daily project workload of the target development project and the standard daily workload of each second personnel to be assigned includes:

[0018] Sort the second candidates for assignment from high to low according to their standard daily workload, and accumulate their standard daily workloads in order until the accumulated result is greater than or equal to the project daily workload;

[0019] Each second person to be assigned corresponding to the accumulated result is used as the target person.

[0020] In a second aspect, the present application provides a human resources allocation device, comprising:

[0021] A collection module, used for obtaining project data groups of respective first personnel to be assigned;

[0022] An evaluation module is used to determine the evaluation result of each first person to be assigned based on each group of project data and a preset personnel evaluation model, and select the first person to be assigned with an excellent evaluation result as the second person to be assigned;

[0023] The allocation module is used to determine the target personnel to be allocated to the target development project from the second personnel to be allocated according to the project daily task volume of the target development project and the standard daily workload of each second personnel to be allocated.

[0024] Furthermore, the human resources allocation device further includes:

[0025] An acquisition module is used to acquire a historical sample set, the historical sample set including: multiple groups of historical project data groups and actual evaluation results corresponding to each group of historical project data groups;

[0026] The training module is used to apply the historical sample set to train the gradient boosting decision tree model to obtain the personnel evaluation model.

[0027] Furthermore, the human resources allocation device further includes:

[0028] The workload acquisition module is used to obtain the standard daily workload corresponding to the personnel number of each second person to be assigned from the preset personnel portrait data table. Each group of project data groups contains: the personnel number of the corresponding first person to be assigned.

[0029] In a third aspect, the present application provides an electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the human resource allocation method is implemented when the processor executes the program.

[0030] In a fourth aspect, the present application provides a computer-readable storage medium having computer instructions stored thereon, which implement the human resource allocation method when the instructions are executed.

[0031] It can be seen from the above technical solution that the present application provides a method and device for allocating human resources. The method includes: obtaining a plurality of project data groups of respective first personnel to be assigned; determining the evaluation results of each first personnel to be assigned based on each project data group and a preset personnel evaluation model, and using the first personnel to be assigned with excellent evaluation results as the second personnel to be assigned; determining the target personnel to be assigned to the target development project from each second personnel to be assigned based on the project daily task volume of the target development project and the standard daily workload of each second personnel to be assigned, which can improve the accuracy and efficiency of human resource allocation, and thus improve the efficiency and accuracy of project development; specifically, based on the artificial intelligence model, it can improve the accuracy of human resource allocation, and can provide intelligent It can help you to quickly and efficiently form a project human resources team; quantify personnel information from multiple aspects such as basic information, attitude, ability, performance, growth and behavior, establish labels, build character portraits, comprehensively portray the performance output of each person, and evaluate the workload that each developer can complete in a day, which can provide a basis for intelligent and precise management of personnel; through the size of the project and the time required to complete it can intelligently and accurately allocate personnel and form a development team; it can improve the degree of automation of developer pool management and project team formation, which can greatly reduce the workload of developer pool management and project team formation, thereby saving the cost of project team formation and project development. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without any creative work.

[0033] Figure 1 This is a first flow chart of the human resources allocation method in an embodiment of the present application;

[0034] Figure 2 is a second flow chart of the human resources allocation method in an embodiment of the present application;

[0035] Figure 3 3 is a schematic diagram of a third flow chart of the human resources allocation method in an embodiment of the present application;

[0036] Figure 4 This is a schematic diagram of the structure of the human resources allocation device in an embodiment of the present application;

[0037] Figure 5 This is a schematic block diagram of the system structure of the electronic device 9600 according to an embodiment of the present application. DETAILED DESCRIPTION

[0038] In order to enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this application will be clearly and completely described below in conjunction with the drawings in the embodiments of this application. Obviously, the described embodiments are only part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of this application.

[0039] In order to solve the above-mentioned problems in the prior art, the present application considers providing a human resource allocation method and device, which cleans and extracts data related to historical project requirements and trains the historical data through the GBDT gradient boosting tree model. For subsequent new project requirements, the established model can be used to recommend corresponding external developers. At the same time, by evaluating the capabilities of each external developer, a project development team can be automatically formed according to the project scale.

[0040] Based on this, in order to improve the accuracy and efficiency of human resource allocation, and thus improve the efficiency and accuracy of project development, an embodiment of the present application provides a human resource allocation device, which can be a server or a client device. The client device can include a smartphone, a tablet electronic device, a network set-top box, a portable computer, a desktop computer, a personal digital assistant (PDA), an in-vehicle device, and a smart wearable device. The smart wearable device can include smart glasses, smart watches, and smart bracelets.

[0041] In practical applications, the human resource allocation portion can be performed on the server side as described above, or all operations can be completed on the client device. The specific selection can be based on the processing capabilities of the client device and the limitations of the user's usage scenario. This application does not impose any restrictions on this. If all operations are completed on the client device, the client device may also include a processor.

[0042] The client device may include a communication module (i.e., a communication unit) that can establish a communication connection with a remote server to implement data transmission with the server. The server may include a server on the task scheduling center side, and in other implementation scenarios, may also include a server on an intermediate platform, such as a server on a third-party server platform that has a communication link with the task scheduling center server. The server may include a single computer device, a server cluster consisting of multiple servers, or a server structure of a distributed device.

[0043] The server and the client device may communicate using any suitable network protocol, including network protocols not yet developed on the date of filing this application. Examples of such network protocols include TCP / IP, UDP / IP, HTTP, and HTTPS. Furthermore, examples of such network protocols include RPC (Remote Procedure Call Protocol) and REST (Representational State Transfer) protocols, which are used on top of the aforementioned protocols.

[0044] It should be noted that the human resource allocation device disclosed in this application can be used in the field of financial technology, and can also be used in any field other than the field of financial technology. The application field of the human resource allocation device disclosed in this application is not limited.

[0045] The details are described in detail through the following embodiments.

[0046] In order to improve the accuracy and efficiency of human resource allocation, and thus improve the efficiency and accuracy of project development, this embodiment provides a human resource allocation method in which the execution subject is a human resource allocation device, and the human resource allocation device includes but is not limited to a server, such as Figure 1 As shown, the method specifically includes the following contents:

[0047] Step 100: Obtain project data groups of respective multiple first personnel to be assigned.

[0048] Specifically, based on the project requirements of the target development project, the project data groups of each first person to be assigned can be automatically collected from each project-related system. Each project data group can include: personnel number, project name of the target development project, project application, professional key project level, policy supervision project level, urgency level, business direction, responsible department, business value, task volume and priority data; the personnel number whose work arrangement is marked as unassigned can be obtained from the preset personnel portrait data table, and the external developer corresponding to the personnel number can be used as the first person to be assigned. The personnel number is a unique identifier of the first person to be assigned, which can be a randomly generated string of characters used to distinguish different first people to be assigned.

[0049] Step 200: Determine the evaluation result of each first person to be assigned based on each project data group and a preset personnel evaluation model, and select the first person to be assigned with an excellent evaluation result as the second person to be assigned.

[0050] Specifically, project data sets can be input into a pre-trained personnel evaluation model. Each project data set will output an evaluation result, with recommended project data sets and evaluation results corresponding one to one. If the evaluation result is excellent, the first candidate to be assigned, corresponding to the project data set, is suitable for the target development project. If the evaluation result is good, the first candidate to be assigned, corresponding to the project data set, is unsuitable for the target development project. The second candidate to be assigned can be an external developer who also received an excellent evaluation result.

[0051] Step 300: Determine the target personnel to be assigned to the target development project from among the second personnel to be assigned based on the project daily task volume of the target development project and the standard daily workload of each second personnel to be assigned.

[0052] Specifically, the project daily task load can be the daily task load required for the target development project; the standard daily workload can be the daily workload that the first candidate can complete. Pre-assigned personnel information can be quantified from multiple perspectives, including basic information, attitude, capabilities, effectiveness, growth, and behavior, to create labels and construct character profiles. This comprehensively characterizes performance and output, and assesses the daily workload that each external developer can complete. The target development project can be a financial trading software development project.

[0053] For example, each project type has a specific scale. For example, if an international settlement project has a scale of 100 function points and one person is assigned to complete it in five days, that person's daily workload is 20 function points. Because individual work capabilities vary, the estimated daily workload for each person may vary. Based on expert experience, we can quantify individual information from multiple perspectives, including basic information, attitude, capabilities, effectiveness, growth, and behavior, and create labels for evaluation.

[0054] In order to further improve the reliability of the personnel evaluation model, and thus improve the reliability of the subsequent application of the reliable personnel evaluation model to evaluate the first person to be assigned, see Figure 2 In one embodiment of the present application, before step 200, the method further includes:

[0055] Step 021: Obtain a historical sample set, which includes: multiple groups of historical project data groups and actual evaluation results corresponding to each group of historical project data groups.

[0056] Specifically, the actual evaluation result is excellent or good; the historical project data group includes: personnel number, project name of the historical development project, project application, professional key project level, policy supervision project level, urgency level, business direction, responsible department, business value, workload, priority and other feature data; for a historical development project, each external developer participating in the historical development project will have a set of historical project data groups, and the developer's participation in the historical development project will be evaluated to obtain the actual evaluation result to evaluate whether the external developer is suitable for participating in the historical development project. The historical project demand data can be processed including feature extraction, feature dimensionality reduction, feature null value processing, target value conversion and other data processing to obtain the historical sample set.

[0057] Step 022: Apply the historical sample set to train the gradient boosting decision tree model to obtain the personnel evaluation model.

[0058] Specifically, 80% of the data can be randomly extracted from the historical sample set as the training set and 20% of the data as the validation set. The training set data is used to train the GBDT gradient boosting tree model, and the validation set data is substituted into the trained model to predict the results. The prediction results of the validation set are obtained, and the prediction results are divided by the target results to get the accuracy.

[0059] Accuracy = predicted result / target result. A threshold for accuracy, such as 90%, is set. If the model's accuracy doesn't reach this threshold, training is repeated until the model reaches the target. This completes the modeling process and yields the personnel evaluation model. Subsequent projects can use the personnel evaluation model to determine the suitability of external developers for the project, predicting whether the external developer's participation evaluation score is excellent or good.

[0060] To further improve the reliability of human resource allocation, see Figure 3 In one embodiment of the present application, before step 300, the method further includes:

[0061] Step 021: From the preset personnel portrait data table, obtain the standard daily workload corresponding to the personnel number of each second person to be assigned, and each group of project data groups contains: the personnel number of the corresponding first person to be assigned.

[0062] Specifically, the preset personnel portrait data table may include: the correspondence between the personnel number, work arrangement identifier and standard daily workload of the first person to be assigned, and may pre-quantify personnel information from multiple angles such as basic information, attitude, ability, efficiency, growth and behavior to establish labels, construct character portraits, comprehensively portray efficiency output, and evaluate the workload that each external developer can complete in a day as the standard daily workload of the external developer, and store it in the personnel portrait data table.

[0063] In order to further improve the reliability of human resource allocation, in one embodiment of the present application, before step 300, the following steps are further included:

[0064] Step 022: Obtain the daily task volume of the target development project according to the coding start time, coding end time and total project task volume of the target development project.

[0065] Specifically, the daily task volume of the target development project can be obtained according to the following formula:

[0066] The time of the coding phase (days) = coding end time - coding start time;

[0067] Project daily task volume = total project task volume / coding phase time (days).

[0068] The total project workload can be broken down into requirement items based on requirements. Requirement items are requirements that have business value and can produce business results, encompassing complete end-to-end business scenarios and the smallest scope that can be independently put into production. Requirement items are broken down based on business objectives and are the smallest units that meet business expectations, connect business and technology, and can independently schedule release plans. These are then evaluated using the DELPHI evaluation method. Alternatively, the project's functional points, or total workload, can be pre-set based on actual circumstances.

[0069] In order to further improve the accuracy of human resource allocation and save labor costs, in one embodiment of the present application, step 300 includes:

[0070] Step 301: Sort the second personnel to be assigned from high to low according to their standard daily workload, and accumulate the standard daily workload of the second personnel to be assigned in order until the accumulated result is greater than or equal to the project daily task volume.

[0071] Step 302: taking each second person to be assigned corresponding to the accumulated result as the target person.

[0072] Specifically, based on the daily workload of the target development project (i.e., the project daily workload), calculate how many people are needed and what type of people are needed. Then, select them in order of their daily project workload, from high to low. The total daily workload of the team = the standard daily workload of person 1 + the standard daily workload of person 2, ... + the standard daily workload of person n. When the project daily workload <= the total daily workload of the team, the personnel selection is complete.

[0073] For example, the second group of personnel to be assigned are sorted from high to low according to the standard daily workload as follows: personnel 1, personnel 2...personnel n; if personnel 1's standard daily workload + personnel 2's standard daily workload +... + personnel k's standard daily workload = A, A < project daily workload, personnel 1's standard daily workload + personnel 2's standard daily workload +... + personnel (k+1)'s standard daily workload = B, B ≥ project daily workload, then personnel 1 to personnel (k+1) will be assigned to the target development project.

[0074] To further illustrate this solution, after step 300, the following steps may also be included:

[0075] 1) In the preset personnel portrait data table, the work arrangement identifier corresponding to the target personnel is marked as arranged work. When new projects come in the future, the external personnel who have been arranged to work will no longer be included in the recommended basic data during the project coding time period.

[0076] 2) Evaluate the performance of external developers in the project: During the project development process, each external developer performs differently. After the development is completed, the external developer's participation in the project can be evaluated from multiple aspects such as the amount of work completed, defect density, number of lines of code submitted, number of code submissions, and number of production problems. This can be used to assess whether the external developer is suitable for participating in the project. If the performance is excellent, it will be rated as excellent; if the performance is not good, it will be rated as good.

[0077] 3) Transfer personnel evaluation data to the project dataset: The personnel evaluation results from the previous step are combined with project feature data, processed, and transferred to the historical sample dataset to serve as training sample data for subsequent model self-learning. Since this project has been completed, these personnel are marked as unassigned in the profile data table and can participate in human resources allocation for the next new project.

[0078] From the software level, in order to improve the accuracy and efficiency of human resource allocation, and thus improve the efficiency and accuracy of project development, this application provides an embodiment of a human resource allocation device for implementing all or part of the content of the human resource allocation method, see Figure 4 , the human resources allocation device specifically includes the following contents:

[0079] The acquisition module 10 is used to obtain the project data groups of each of the plurality of first personnel to be assigned.

[0080] The evaluation module 20 is used to determine the evaluation result of each first person to be assigned based on each group of project data and a preset personnel evaluation model, and select the first person to be assigned with an excellent evaluation result as the second person to be assigned.

[0081] The allocation module 30 is configured to determine a target person to be allocated to the target development project from among the second persons to be allocated according to the daily project workload of the target development project and the standard daily workload of each second person to be allocated.

[0082] In one embodiment of the present application, the human resources allocation device further includes:

[0083] The acquisition module is used to acquire a historical sample set, which includes: multiple groups of historical project data groups and actual evaluation results corresponding to each group of historical project data groups.

[0084] The training module is used to apply the historical sample set to train the gradient boosting decision tree model to obtain the personnel evaluation model.

[0085] In one embodiment of the present application, the human resources allocation device further includes:

[0086] The workload acquisition module is used to obtain the standard daily workload corresponding to the personnel number of each second person to be assigned from the preset personnel portrait data table. Each group of project data groups contains: the personnel number of the corresponding first person to be assigned.

[0087] The embodiment of the human resource allocation device provided in this specification can be specifically used to execute the processing flow of the embodiment of the above human resource allocation method. Its functions are not described in detail here, and reference can be made to the detailed description of the embodiment of the above human resource allocation method.

[0088] From the above description, it can be seen that the human resource allocation method and device provided by this application can improve the accuracy and efficiency of human resource allocation, and thus improve the efficiency and accuracy of project development; specifically, based on the artificial intelligence model, it can improve the accuracy of human resource allocation, and can realize the formation of intelligent and fast project human resource teams; quantify personnel information from multiple aspects such as basic information, attitude, ability, efficiency, growth and behavior, establish labels, construct character portraits, comprehensively portray the efficiency output of each person, and evaluate the workload that each developer can complete in a day, which can provide a basis for intelligent and precise management of personnel; according to the size of the project and the time required to complete it, it can intelligently and accurately allocate personnel and form a development team; it can improve the degree of automation of developer pool management and project team formation, and can greatly reduce the workload of developer pool management and project team formation, thereby saving the cost of project team formation and project development.

[0089] From a hardware perspective, in order to improve the accuracy and efficiency of human resource allocation, and thereby improve the efficiency and accuracy of project development, the present application provides an embodiment of an electronic device for implementing all or part of the human resource allocation method. The electronic device specifically includes the following:

[0090] A processor, a memory, a communications interface, and a bus; wherein the processor, memory, and communications interface communicate with each other via the bus; the communications interface is used to transmit information between the human resources allocation apparatus and related devices such as user terminals; the electronic device may be a desktop computer, a tablet computer, a mobile terminal, etc., but this embodiment is not limited thereto. In this embodiment, the electronic device may be implemented with reference to the embodiments for implementing the human resources allocation method and the embodiments for implementing the human resources allocation apparatus, the contents of which are incorporated herein and any repetitions are omitted.

[0091] Figure 5 Schematic block diagram of the system structure of the electronic device 9600 according to an embodiment of the present application. Figure 5 As shown, the electronic device 9600 may include a central processing unit 9100 and a memory 9140; the memory 9140 is coupled to the central processing unit 9100. It is worth noting that the Figure 5 is exemplary; other types of structures may also be used to supplement or replace this structure to implement telecommunication functions or other functions.

[0092] In one or more embodiments of the present application, the human resources allocation function may be integrated into the central processing unit 9100. The central processing unit 9100 may be configured to perform the following control:

[0093] Step 100: Obtain project data groups of respective multiple first personnel to be assigned.

[0094] Step 200: Determine the evaluation result of each first person to be assigned based on each project data group and a preset personnel evaluation model, and select the first person to be assigned with an excellent evaluation result as the second person to be assigned.

[0095] Step 300: Determine the target personnel to be assigned to the target development project from among the second personnel to be assigned based on the project daily task volume of the target development project and the standard daily workload of each second personnel to be assigned.

[0096] It can be seen from the above description that the electronic device provided by the embodiments of the present application can improve the accuracy and efficiency of human resource allocation, thereby improving the efficiency and accuracy of project development.

[0097] In another embodiment, the human resource allocation device may be configured separately from the central processing unit 9100. For example, the human resource allocation device may be configured as a chip connected to the central processing unit 9100, and the human resource allocation function is implemented under the control of the central processing unit.

[0098] like Figure 5 As shown, the electronic device 9600 may further include: a communication module 9110, an input unit 9120, an audio processor 9130, a display 9160, and a power supply 9170. It is worth noting that the electronic device 9600 does not necessarily have to include Figure 5 In addition, the electronic device 9600 may also include all components shown in Figure 5 For components not shown, reference may be made to the prior art.

[0099] like Figure 5 As shown, the central processing unit 9100 is sometimes also referred to as a controller or operation control, and may include a microprocessor or other processor device and / or logic device. The central processing unit 9100 receives input and controls the operation of various components of the electronic device 9600.

[0100] Memory 9140 can be, for example, one or more of a cache, flash memory, hard drive, removable media, volatile memory, non-volatile memory, or other suitable devices. It can store the aforementioned failure-related information and also store programs that execute the relevant information. The CPU 9100 can execute the programs stored in memory 9140 to implement information storage or processing.

[0101] The input unit 9120 provides input to the central processing unit 9100. The input unit 9120 may be, for example, a keypad or touch input device. The power supply 9170 is used to provide power to the electronic device 9600. The display 9160 is used to display objects such as images and text. The display may be, for example, an LCD display, but is not limited thereto.

[0102] The memory 9140 may be a solid-state memory, such as a read-only memory (ROM), a random access memory (RAM), or a SIM card. Alternatively, it may be a memory that retains information even when power is off, can be selectively erased, and is provided with more data. Examples of such memory are sometimes referred to as EPROMs. The memory 9140 may also be some other type of device. The memory 9140 includes a buffer memory 9141 (sometimes referred to as a buffer). The memory 9140 may include an application / function storage unit 9142 for storing application programs and function programs or processes for executing the operation of the electronic device 9600 by the central processing unit 9100.

[0103] The memory 9140 may also include a data storage unit 9143 for storing data, such as contacts, digital data, pictures, sounds, and / or any other data used by the electronic device. The driver storage unit 9144 of the memory 9140 may include various driver programs for communication functions of the electronic device and / or for executing other functions of the electronic device (such as messaging applications, address book applications, etc.).

[0104] The communication module 9110 is a transmitter / receiver 9110 that transmits and receives signals via an antenna 9111. The communication module (transmitter / receiver) 9110 is coupled to the central processor 9100 to provide input signals and receive output signals, which may be the same as in a conventional mobile communication terminal.

[0105] Based on different communication technologies, multiple communication modules 9110 can be provided in the same electronic device, such as a cellular network module, a Bluetooth module, and / or a wireless local area network module. The communication module (transmitter / receiver) 9110 is also coupled to a speaker 9131 and a microphone 9132 via an audio processor 9130 to provide audio output via the speaker 9131 and receive audio input from the microphone 9132, thereby implementing common telecommunication functions. The audio processor 9130 may include any suitable buffer, decoder, amplifier, etc. Furthermore, the audio processor 9130 is also coupled to the central processing unit 9100, enabling local recording via the microphone 9132 and playback of stored audio via the speaker 9131.

[0106] As can be seen from the above description, the electronic device provided by the embodiments of the present application can improve the accuracy and efficiency of human resource allocation, thereby improving the efficiency and accuracy of project development.

[0107] The embodiments of the present application also provide a computer-readable storage medium capable of implementing all steps of the human resource allocation method in the above embodiments. The computer-readable storage medium stores a computer program. When the computer program is executed by a processor, the computer program implements all steps of the human resource allocation method in the above embodiments. For example, when the processor executes the computer program, the following steps are implemented:

[0108] Step 100: Obtain project data groups of respective multiple first personnel to be assigned.

[0109] Step 200: Determine the evaluation result of each first person to be assigned based on each project data group and a preset personnel evaluation model, and select the first person to be assigned with an excellent evaluation result as the second person to be assigned.

[0110] Step 300: Determine the target personnel to be assigned to the target development project from among the second personnel to be assigned based on the project daily task volume of the target development project and the standard daily workload of each second personnel to be assigned.

[0111] It can be seen from the above description that the computer-readable storage medium provided in the embodiments of the present application can improve the accuracy and efficiency of human resource allocation, thereby improving the efficiency and accuracy of project development.

[0112] In this application, the various embodiments of the above method are described in a progressive manner. The same or similar parts between the various embodiments can be referred to each other. Each embodiment focuses on the differences from other embodiments. For related parts, please refer to the partial description of the method embodiment.

[0113] Those skilled in the art will appreciate that the embodiments of the present application can be provided as methods, systems, or computer program products. Therefore, the present application can adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application can adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code.

[0114] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the steps in the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0115] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0116] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0117] Specific embodiments are used in this application to illustrate the principles and implementation methods of this application. The description of the above embodiments is only used to help understand the method and core ideas of this application. At the same time, for those skilled in the art, according to the ideas of this application, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as limiting this application.

Claims

1. A method for allocating human resources, characterized in that: include: Obtaining respective project data groups of a plurality of first to-be-assigned personnel; Based on each project data set and the preset personnel evaluation model, the evaluation results of each first-line candidate for assignment are determined, and the first-line candidate with excellent evaluation results is selected as the second-line candidate for assignment. Each project data set includes: personnel number, project name of the target development project, project application, professional key project level, policy supervision project level, urgency level, business direction, responsible department, business value, task volume and priority data; Determine the target personnel to be assigned to the target development project from among the second personnel to be assigned based on the daily project workload of the target development project and the standard daily workload of each second personnel to be assigned; The step of determining the target personnel to be assigned to the target development project from the second personnel to be assigned based on the daily project workload of the target development project and the standard daily workload of each second personnel to be assigned includes: Sort the second candidates for assignment from high to low according to their standard daily workload, and accumulate their standard daily workloads in order until the accumulated result is greater than or equal to the project daily workload; Each second person to be assigned corresponding to the accumulated result is used as the target person; Before determining the evaluation result of each first to-be-assigned person according to each project data group and the preset person evaluation model, the method further includes: From the historical sample set, 80% of the data is randomly selected as the training set and 20% of the data is used as the validation set. The GBDT gradient boosting tree model is trained using the training set data. The validation set data is substituted into the trained model to predict the results. The prediction results of the validation set are obtained and divided by the target result to obtain the accuracy rate. An accuracy threshold is set. If the accuracy corresponding to the model does not reach the accuracy threshold, the training is repeated until the accuracy corresponding to the model reaches the accuracy threshold, and the model building work is completed to obtain the personnel evaluation model.

2. The human resource allocation method according to claim 1, characterized in that: Before the daily task volume of the target development project and the standard daily workload of each second person to be assigned, it also includes: From the preset personnel portrait data table, the standard daily workload corresponding to the personnel number of each second person to be assigned is obtained, and each group of project data groups includes: the personnel number of the corresponding first person to be assigned.

3. The human resource allocation method according to claim 1, characterized in that: Before the daily task volume of the target development project and the standard daily workload of each second person to be assigned, it also includes: According to the coding start time, coding end time and total project task volume of the target development project, the project daily task volume of the target development project is obtained.

4. A human resources allocation device, characterized in that: include: A collection module, used for obtaining project data groups of respective first personnel to be assigned; An evaluation module is used to determine the evaluation results of each first candidate for assignment based on each project data group and a preset personnel evaluation model, and select the first candidate for assignment with an excellent evaluation result as the second candidate for assignment. Each project data group includes: personnel number, project name of the target development project, project application, professional key project level, policy supervision project level, urgency level, business direction, responsible department, business value, task volume and priority data; An allocation module, configured to determine a target person to be allocated to the target development project from among the second persons to be allocated based on the daily project workload of the target development project and the standard daily workload of each second person to be allocated; The step of determining the target personnel to be assigned to the target development project from the second personnel to be assigned based on the daily project workload of the target development project and the standard daily workload of each second personnel to be assigned includes: Sort the second candidates for assignment from high to low according to their standard daily workload, and accumulate their standard daily workloads in order until the accumulated result is greater than or equal to the project daily workload; Each second person to be assigned corresponding to the accumulated result is used as the target person; The human resources allocation device is further used to: From the historical sample set, 80% of the data is randomly selected as the training set and 20% of the data is used as the validation set. The GBDT gradient boosting tree model is trained using the training set data. The validation set data is substituted into the trained model to predict the results. The prediction results of the validation set are obtained and divided by the target result to obtain the accuracy rate. An accuracy threshold is set. If the accuracy corresponding to the model does not reach the accuracy threshold, the training is repeated until the accuracy corresponding to the model reaches the accuracy threshold, and the model building work is completed to obtain the personnel evaluation model.

5. The human resources allocation device according to claim 4, characterized in that: Also includes: The workload acquisition module is used to obtain the standard daily workload corresponding to the personnel number of each second person to be assigned from the preset personnel portrait data table. Each group of project data groups contains: the personnel number of the corresponding first person to be assigned.

6. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the program, the human resource allocation method according to any one of claims 1 to 3 is implemented.

7. A computer-readable storage medium having computer instructions stored thereon, characterized in that: When the instructions are executed, the human resources allocation method according to any one of claims 1 to 3 is implemented.

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