CN112488658A - Task portrait construction algorithm, device, terminal and storage medium for digital human resource management - Google Patents
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Abstract
A task portrait construction algorithm, a device, a terminal and a storage medium for digital human resource management comprise the following steps: step 1: the constrained task condition initialization module is used for updating the task label; step 2: the task log data are collected in real time, and classification management and high concurrency access of the task data are achieved; and step 3: calculating the probability and the result of the task to be processed through a Bayesian model; and 4, step 4: acquiring all tasks to be processed, and selecting target workers; and 5: acquiring a sample set corresponding to a target worker; step 6: and storing the real-time task image output by calculation.
Description
Technical Field
The embodiment of the invention relates to the field of databases and big data, in particular to a task portrait construction algorithm, a device, a terminal and a storage medium for digital human resource management.
Background
With the development of computer technology, more and more technologies (big data, distributed, Blockchain, artificial intelligence, etc.) are applied in the management field. Human resources are also undergoing a deep revolution in digitization as an important component of enterprise management. By means of big data technology, data information generated by staff working behaviors, results and the like can be tracked, integrated and analyzed better, the human resource management is supported to be shifted from historical analysis to predictive analysis, working task requirements are simulated, adaptive talents are mined, talent markets are built in enterprises, department barriers are broken, a task resource sharing platform is established, suitable people are guaranteed to do suitable tasks, staff sharing and leadership hanging are achieved, and the cooperation partnership between the staff and the enterprises is really established. .
The user portrait is a tagged user model abstracted according to information such as social attributes, living habits and consumption behaviors of users, the core work of constructing the user portrait is to label the user with tags, and the tags are highly refined feature identifications obtained by analyzing user information.
Based on the user representation, the invention derives a task representation. The task portrait describes objective forms and typical characteristics of a full life cycle (task generation, task dispatching, task order receiving, task execution, task completion evaluation and evaluation result application) of the task through a series of standard and quantized labels, and the task is displayed objectively and stereoscopically, so that a user can recognize and judge the task most intuitively and accurately.
The prior task portrait has a plurality of defects, mainly including the unsound label of the task portrait, the unclear algorithm rule and the effective realization of the application landing of the task portrait without combining the big data technology.
Disclosure of Invention
In order to solve the problems in the prior art, the invention provides a task portrait construction algorithm, a device, a terminal and a storage medium for digitalized human resource management.
The technical scheme adopted by the invention for solving the technical problems is as follows:
a task portrait construction algorithm for digital human resource management comprises the following steps:
step 1: the constrained task condition initialization module is used for updating the task label;
step 2: the task log data are collected in real time, and classification management and high concurrency access of the task data are achieved;
and step 3: calculating the probability and the result of the task to be processed through a Bayesian model;
and 4, step 4: acquiring all tasks to be processed, and selecting target workers;
and 5: acquiring a sample set corresponding to a target worker;
step 6: and storing the real-time task image output by calculation.
A task portrait construction device is applied to a terminal, the task portrait can be applied to the whole process of task management, and the realization path is as follows: making a task portrait → task sending → task receiving → task executing → task acceptance and evaluation → task evaluation result application; wherein the content of the first and second substances,
task portrait making: on the basis of task labels, analyzing the service requirements of the tasks (determining what the tasks are, what the tasks are successful and who the tasks can do), and selecting corresponding label dimensions and labels to form task images;
task "dispatch" and task "order-receiving": the task supports 'directional dispatching' and 'open order grabbing', namely a task portrait can be appointed by a task publisher as a 'receiving person' and can also be brought into a resource sharing pool, and through the 'open competition field' mode, the department barrier is broken, multiple parties are allowed to grab orders, open competition is allowed, and people are hung in a hostage uncovered list;
and (3) task execution: the 'receiver' performs full-flow monitoring and data recording in the task execution process, and provides sufficient process data deposition for task evaluation;
and (3) task evaluation: after the task is executed, the task publisher evaluates the task completion condition according to the principle of who sends and checks, wherein the task completion condition comprises the evaluation of the efficiency, benefit and quality of task completion and the evaluation of the ability attitude shown by an executor in the process;
task portrayal application: the task sketch can be applied to a multivariate and flexible human resource management service scene according to actual needs, the task sketch is used as a medium, the working requirements are met, the talent capability is shown, the management decision is supported, and the like, and the application scenes are four in the following manner:
1) matching human and ren;
the task portrait can be appointed to receive a person by a task publisher, and can also be brought into a resource sharing pool, and through an open competition field mode, the department barrier is broken, multiple parties are allowed to compete, the competition is open, and the hung commander is uncovered;
2) iteration of the talent portrait;
during and after the task execution process, following the principle of who sends and receives, the task publisher evaluates the task completion condition, and the evaluation result and the like automatically enrich and iterate talent portrayal of performers;
3) linking the post portrait;
the 'task experience' (including the self condition of the task, the completion condition of the task, the personal ability attitude and the like) can be used as a screening dimension of the post portrait in the future and matched with the corresponding dimension of the talent portrait, so that the post matching accuracy is improved;
4) linking individual performance;
the task completion process and quality are recorded through the whole task evaluation process; the evaluation result can be used as a supplementary bonus of the performance assessment score of the individual year, so that the staff is encouraged to undertake tasks, and the staff is more and more.
A terminal, the terminal comprising: a memory, a processor, and a task image construction program stored on the memory and executable on the processor, the task image construction program when executed by the processor implementing the steps of the task image construction algorithm of any of claims 1 to 7.
A storage medium having stored thereon a task representation construction program, the task representation construction program when executed by a processor implementing the steps of the task representation construction algorithm of any one of claims 1 to 7.
The invention also has the following additional technical features:
the technical scheme of the invention is further specifically optimized as follows: in the step 1, a constraint task condition initialization module is responsible for setting a default value before a system is started, a modeling class is preset as a task statistic value, a component class is preset as a task experience value, and a strong rule is used for judging, identifying and dividing an input value, wherein the strong rule refers to a condition rule which is set by a program and needs to be met, the input value is user attribute, behavior and characteristics with statistical information, the task label information is initially judged according to whether the strong rule is set or not, and a task label different from the preset default value is identified and is simultaneously updated.
The technical scheme of the invention is further specifically optimized as follows: step 2, a real-time task data acquisition module acquires task log data in real time and analyzes the acquired task log data to form a task data acquisition link; real-time data forwarding, namely dividing the acquired task log data according to the task data acquisition link and the task data type to form an ordered task message queue; the collected task log data is used as a Kafka message source and is placed in a Kafka message queue, and the layers are decoupled and forwarded by using an asynchronous communication mechanism of the Kafka message queue, so that the classification management and the high-concurrency access of the task data are realized.
The technical scheme of the invention is further specifically optimized as follows: and step 3, when the task to be processed arrives, taking the priority attribute as an input variable of the Bayesian model, respectively calculating the probability of accepting the task to be processed and the probability of not accepting the task to be processed by the target worker according to the Bayesian model, and obtaining a prediction result of whether the target worker can accept the task to be processed according to the probabilities.
The technical scheme of the invention is further specifically optimized as follows: step 4, acquiring all tasks to be processed in the area to be completed within the current time period to be completed; acquiring the total completion difficulty of all tasks to be processed and the completion difficulty of each task to be processed; and selecting a target worker from all workers according to the total difficulty of completing all tasks to be processed and the images of all workers.
The technical scheme of the invention is further specifically optimized as follows: step 5, acquiring a sample set corresponding to the target staff, wherein the samples in the sample set are task data browsed by the target staff, and each task data comprises at least two attributes; the method comprises the steps of distinguishing positive samples and negative samples in a sample set according to a preset rule, taking at least two attributes as sample attributes, and determining the priority attribute of a target worker by constructing a classification regression tree, wherein the priority attribute is the most important attribute to the target worker in the at least two attributes.
The technical scheme of the invention is further specifically optimized as follows: and 6, storing the real-time task portrait output by the calculation by the database writing module for the client to inquire and return data according to specific service conditions, and simultaneously performing application caching on the real-time task data inquired in a short term for a short-term high-frequency inquiry task.
Compared with the prior art, the invention has the advantages that:
1. the method is used for global configuration, and can automatically take over when the model is abnormal, so that the system availability is ensured;
2. when the service changes, the system can be hot started under the condition of not restarting the system, the configuration can take effect when next scheduling is carried out, and when the service changes frequently, the system fault tolerance is ensured by complementing the standby configuration;
3. when the data volume changes greatly or the time span is long, the model is automatically updated, and new historical data are used for generating features;
4. integrating a plurality of database insertion engines to support a user-defined database writing mode;
5. establishing a task label, and defining a task portrait in an all-round way in the form of the label, wherein the task portrait comprises three aspects of task attributes, task requirements and competency characteristics, and a foundation of model application is formed;
6. based on task portraits and data in a terminal, the task portraits and talent portraits are accurately matched through technology, intelligent talent screening and recommendation are realized, a fair competition mechanism is established, and the ecology of 'toping and hanging commander' task 'sending' and 'receiving' is created;
7. a terminal clearly records the task execution process behaviors and result data, establishes a task big data warehouse of employees to establish a comprehensive and dynamic iterative data analysis system, and supports the application of task portrayal in the scenes of personnel matching and employee personal performance evaluation.
Additional aspects and advantages of the invention will be set forth in part in the description which follows and, in part, will be obvious from the description, or may be learned by practice of the invention.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a schematic structural view of the present invention;
FIG. 2 is a logic diagram of a task image construction device according to the present invention;
FIG. 3 is a schematic diagram of a task evaluation scoring model according to the present invention.
Detailed Description
Exemplary embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings, in order that the present disclosure may be more fully understood and fully conveyed to those skilled in the art. While the exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the invention is not limited to the embodiments set forth herein.
A task portrait construction algorithm for digital human resource management comprises the following steps:
step 1: the constrained task condition initialization module is used for updating the task label;
the system comprises a constraint task condition initialization module, a module and a module, wherein the constraint task condition initialization module is responsible for setting a default value before the system is started, presetting a modeling class as a task statistic value, presetting a component class as a task experience value, and judging, identifying and dividing an input value by using a strong rule, wherein the strong rule refers to a condition rule which is set by a program and must be met, the input value is user attribute, behavior and characteristic with statistical information, the task label information is initially judged according to whether the strong rule is set, and a task label different from the preset default value is identified and is updated at the same time;
step 2: the task log data are collected in real time, and classification management and high concurrency access of the task data are achieved;
the real-time task data acquisition module is used for acquiring task log data in real time and analyzing the acquired task log data to form a task data acquisition link; real-time data forwarding, namely dividing the acquired task log data according to the task data acquisition link and the task data type to form an ordered task message queue; the collected task log data is used as a Kafka message source and is placed in a Kafka message queue, and an asynchronous communication mechanism of the Kafka message queue is used for decoupling and forwarding the layers, so that the classification management and the high-concurrency access of the task data are realized;
and step 3: calculating the probability and the result of the task to be processed through a Bayesian model;
when the task to be processed arrives, the priority attribute is used as an input variable of a Bayesian model, the probabilities that the target worker receives and does not receive the task to be processed are respectively calculated according to the Bayesian model, and a prediction result of whether the target worker can receive the task to be processed is obtained according to the probabilities;
and 4, step 4: acquiring all tasks to be processed, and selecting target workers;
acquiring all tasks to be processed in a to-be-completed area within a current to-be-completed time period; acquiring the total completion difficulty of all tasks to be processed and the completion difficulty of each task to be processed; selecting target workers from all workers according to the total completion difficulty of all tasks to be processed and the images of all workers;
and 5: acquiring a sample set corresponding to a target worker;
acquiring a sample set corresponding to a target worker, wherein samples in the sample set are task data browsed by the target worker, and each task data comprises at least two attributes; distinguishing positive samples and negative samples in a sample set according to a preset rule, taking at least two attributes as sample attributes, and determining the priority attribute of the target worker by constructing a classification regression tree, wherein the priority attribute is the most important attribute to the target worker in the at least two attributes;
step 6: storing the real-time task image output by calculation;
and the database writing module stores the calculated and output real-time task portrait for the client to inquire and return data according to specific service conditions, and meanwhile, application caching is carried out on the real-time task data inquired in a short term for a short-term high-frequency inquiry task.
A task portrait construction device is applied to a terminal, the task portrait can be applied to the whole process of task management, and the realization path is as follows: making a task portrait → task sending → task receiving → task executing → task acceptance and evaluation → task evaluation result application; wherein the content of the first and second substances,
task portrait making: on the basis of task labels, analyzing the service requirements of the tasks (determining what the tasks are, what the tasks are when the tasks are successful and who the tasks can do), selecting corresponding label dimensions and labels, and forming a post image;
task "dispatch" and task "order-receiving": the task supports 'directional dispatching' and 'open order grabbing', namely a task portrait can be appointed by a task publisher as a 'receiving person' and can also be brought into a resource sharing pool, and through the 'open competition field' mode, the department barrier is broken, multiple parties are allowed to grab orders, open competition is allowed, and people are hung in a hostage uncovered list;
and (3) task execution: the 'receiver' performs full-flow monitoring and data recording in the task execution process, and provides sufficient process data deposition for task evaluation;
and (3) task evaluation: after the task is executed, the task publisher evaluates the task completion condition according to the principle of who sends and checks, wherein the task completion condition comprises the evaluation of the efficiency, benefit and quality of task completion and the evaluation of the ability attitude shown by an executor in the process;
task portrayal application: the task sketch can be applied to a multivariate and flexible human resource management service scene according to actual needs, the task sketch is used as a medium, the working requirements are met, the talent capability is shown, the management decision is supported, and the like, and the application scenes are four in the following manner:
1) matching human and ren;
the task portrait can be appointed to receive a person by a task publisher, and can also be brought into a resource sharing pool, and through an open competition field mode, the department barrier is broken, multiple parties are allowed to compete, the competition is open, and the hung commander is uncovered;
2) iteration of the talent portrait;
during and after the task execution process, following the principle of who sends and receives, the task publisher evaluates the task completion condition, and the evaluation result and the like automatically enrich and iterate talent portrayal of performers;
3) linking the post portrait;
the 'task experience' (including the self condition of the task, the completion condition of the task, the personal ability attitude and the like) can be used as a screening dimension of the post portrait in the future and matched with the corresponding dimension of the talent portrait, so that the post matching accuracy is improved;
4) linking individual performance;
the task completion process and quality are recorded through the whole task evaluation process; the evaluation result can be used as a supplementary bonus of the performance assessment score of the individual year, so that the staff is encouraged to undertake tasks, and the staff is more and more.
A terminal, the terminal comprising: the processor is used for executing the task image construction algorithm, and the task image construction algorithm is realized by the task image construction program.
A storage medium having a task image construction program stored thereon, the task image construction program when executed by a processor implementing the steps of the task image construction algorithm.
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention are clearly and completely described above with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are a part of the embodiments of the present invention, but not all of the embodiments. The components of embodiments of the present invention generally described and illustrated in the figures herein may be arranged and designed in a wide variety of different configurations.
Thus, the above detailed description of the embodiments of the invention presented in the drawings is not intended to limit the scope of the invention as claimed, but is merely representative of selected embodiments of the invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Claims (10)
1. A task portrait construction algorithm for digital human resource management is characterized by comprising the following steps:
step 1: the constrained task condition initialization module is used for updating the task label;
step 2: the task log data are collected in real time, and classification management and high concurrency access of the task data are achieved;
and step 3: calculating the probability and the result of the task to be processed through a Bayesian model;
and 4, step 4: acquiring all tasks to be processed, and selecting target workers;
and 5: acquiring a sample set corresponding to a target worker;
step 6: and storing the real-time task image output by calculation.
2. The task image construction algorithm for digitalized human resource management according to claim 1, wherein: in the step 1, a constraint task condition initialization module is responsible for setting a default value before a system is started, a modeling class is preset as a task statistic value, a component class is preset as a task experience value, and a strong rule is used for judging, identifying and dividing an input value, wherein the strong rule refers to a condition rule which is set by a program and needs to be met, the input value is user attribute, behavior and characteristics with statistical information, the task label information is initially judged according to whether the strong rule is set or not, and a task label different from the preset default value is identified and is simultaneously updated.
3. The task image construction algorithm for digitalized human resource management according to claim 1, wherein:
step 2, a real-time task data acquisition module acquires task log data in real time and analyzes the acquired task log data to form a task data acquisition link; real-time data forwarding, namely dividing the acquired task log data according to the task data acquisition link and the task data type to form an ordered task message queue; the collected task log data is used as a Kafka message source and is placed in a Kafka message queue, and the layers are decoupled and forwarded by using an asynchronous communication mechanism of the Kafka message queue, so that the classification management and the high-concurrency access of the task data are realized.
4. The task image construction algorithm for digitalized human resource management according to claim 1, wherein:
and step 3, when the task to be processed arrives, taking the priority attribute as an input variable of the Bayesian model, respectively calculating the probability of accepting the task to be processed and the probability of not accepting the task to be processed by the target worker according to the Bayesian model, and obtaining a prediction result of whether the target worker can accept the task to be processed according to the probabilities.
5. The task image construction algorithm for digitalized human resource management according to claim 1, wherein:
step 4, acquiring all tasks to be processed in the area to be completed within the current time period to be completed; acquiring the total completion difficulty of all tasks to be processed and the completion difficulty of each task to be processed; and selecting a target worker from all workers according to the total difficulty of completing all tasks to be processed and the images of all workers.
6. The task image construction algorithm for digitalized human resource management according to claim 1, wherein:
step 5, acquiring a sample set corresponding to the target staff, wherein the samples in the sample set are task data browsed by the target staff, and each task data comprises at least two attributes; the method comprises the steps of distinguishing positive samples and negative samples in a sample set according to a preset rule, taking at least two attributes as sample attributes, and determining the priority attribute of a target worker by constructing a classification regression tree, wherein the priority attribute is the most important attribute to the target worker in the at least two attributes.
7. The task image construction algorithm for digitalized human resource management according to claim 1, wherein:
and 6, storing the real-time task portrait output by the calculation by the database writing module for the client to inquire and return data according to specific service conditions, and simultaneously performing application caching on the real-time task data inquired in a short term for a short-term high-frequency inquiry task.
8. A task portrait construction device is characterized in that the task portrait construction device is applied to a terminal, the task portrait can be applied to the whole process of task management, and the realization path is as follows: making a task portrait → task sending → task receiving → task executing → task acceptance and evaluation → task evaluation result application; wherein the content of the first and second substances,
task portrait making: analyzing the service requirement of the task on the basis of the task label, and selecting a corresponding label dimension and a label to form a task image;
task "dispatch" and task "order-receiving": the task supports 'directional dispatching' and 'open order grabbing', namely a task portrait can be appointed by a task publisher as a 'receiving person' and can also be brought into a resource sharing pool, and through the 'open competition field' mode, the department barrier is broken, multiple parties are allowed to grab orders, open competition is allowed, and people are hung in a hostage uncovered list;
and (3) task execution: the 'receiver' performs full-flow monitoring and data recording in the task execution process, and provides sufficient process data deposition for task evaluation;
and (3) task evaluation: after the task is executed, the task publisher evaluates the task completion condition according to the principle of who sends and checks, wherein the task completion condition comprises the evaluation of the efficiency, benefit and quality of task completion and the evaluation of the ability attitude shown by an executor in the process;
task portrayal application: the task sketch can be applied to a multivariate and flexible human resource management service scene according to actual needs, the task sketch is used as a medium, the working requirements are met, the talent capability is shown, the management decision is supported, and the like, and the application scenes are four in the following manner:
1) matching human and ren;
the task portrait can be appointed to receive a person by a task publisher, and can also be brought into a resource sharing pool, and through an open competition field mode, the department barrier is broken, multiple parties are allowed to compete, the competition is open, and the hung commander is uncovered;
2) iteration of the talent portrait;
during and after the task execution process, following the principle of who sends and receives, the task publisher evaluates the task completion condition, and the evaluation result and the like automatically enrich and iterate talent portrayal of performers;
3) linking the post portrait;
the 'task experience' can be used as a screening dimension of the post portrait in the future and matched with the corresponding dimension of the talent portrait, so that the accuracy of post matching is improved;
4) linking individual performance;
the task completion process and quality are recorded through the whole task evaluation process; the evaluation result can be used as a supplementary bonus of the performance assessment score of the individual year, so that the staff is encouraged to undertake tasks, and the staff is more and more.
9. A terminal, characterized in that the terminal comprises: a memory, a processor, and a task image construction program stored on the memory and executable on the processor, the task image construction program when executed by the processor implementing the steps of the task image construction algorithm of any of claims 1 to 7.
10. A storage medium having stored thereon a task image construction program, the task image construction program when executed by a processor implementing the steps of the task image construction algorithm of any of claims 1 to 7.
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| CN116029684A (en) * | 2023-02-23 | 2023-04-28 | 国投人力资源服务有限公司 | Analysis method and system for measuring matching degree of workers |
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| CN109784625A (en) * | 2018-12-10 | 2019-05-21 | 南京南瑞信息通信科技有限公司 | A kind of work order intelligence distributing method based on personnel ability's analysis |
| CN111445204A (en) * | 2020-03-23 | 2020-07-24 | 珠海格力电器股份有限公司 | Work order processing method and device, storage medium and terminal |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN109784625A (en) * | 2018-12-10 | 2019-05-21 | 南京南瑞信息通信科技有限公司 | A kind of work order intelligence distributing method based on personnel ability's analysis |
| CN111445204A (en) * | 2020-03-23 | 2020-07-24 | 珠海格力电器股份有限公司 | Work order processing method and device, storage medium and terminal |
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