Talent data processing method and device based on big data model

Abstract

The invention relates to the technical field of data security, in particular to a talent data processing method and device based on a big data model, and the method comprises the steps: collecting the working variable data of a target talent object in a working scene; based on the work variable data of the corresponding work type of the target talent object, according to a potential judgment model, evaluating the potential existence range of the emergency of the target talent object under the corresponding work type; environment information of the target talent object and feature information about the environment are collected, and according to the potential transformation probability model, a potential emergency transformation range is determined within the evaluated potential existence range; and determining a potential emergency conversion range of an emergency of the target talent object under the corresponding working type, and proposing a current rectification scheme. According to the method, the incidence relation between the safety potential of each current-state project in various different scenes and the occurrence of emergencies can be fully mined, and the practical evaluation result and rectification scheme are provided.

Description

Technical Field

[0001] The present invention relates to the field of data security, and in particular to a talent data processing method and device based on a big data model. Background Art

[0002] In recent years, the flow of talents has been relatively active, and Chinese companies are also facing new problems in talent management. In many industries, the phenomenon of talent loss is becoming more and more serious, and the job-hopping of key talents will have a great negative impact on the development of enterprises. Analyzing the main factors of talent loss and reducing recruitment costs have become urgent tasks for many companies. When key core talents have the intention to change jobs, companies can predict in advance and formulate a complete solution to greatly reduce operating losses. Enterprise managers need to use certain tools and methods to predict the risk of talent job-hopping so that they can take timely response measures.

[0003] Within the enterprise, how to reasonably manage the employees and their functions is a difficult problem in the current environment. The existing management model still tends to be traditional management, lacking changes under the new intelligent manufacturing concept. Traditional human resource management has drawbacks. This management model will reduce or even lose the employees' sense of identification with the enterprise, which may lead to an increase in the job hopping rate and the development of the enterprise is worrying. Summary of the invention

[0004] In order to solve the problems existing in the above-mentioned prior art, the present invention provides a talent data processing method and device based on a big data model, which can fully explore the correlation between the safety potential of each current status project in various different scenarios and the occurrence of emergencies, and put forward practical evaluation results and rectification plans.

[0005] According to a first aspect of the present invention, the present invention claims protection for a talent data processing method based on a big data model, comprising:

[0006] Collect work variable data of target talent objects in historical work scenarios, current work scenarios, and planned work scenarios, wherein the historical work scenarios are target talent objects that have resigned in the past, the current work scenarios are target talent objects that are currently employed, and the planned work scenarios are target talent objects that are potentially leaving;

[0007] Based on the work variable data of the target talent object's corresponding work type, according to the potential judgment model, evaluate the potential existence range of emergencies that may occur to the target talent object in the corresponding work type;

[0008] Collecting the environmental information and characteristic information about the environment of the target talent object, and determining the potential emergency event conversion range based on the potential existence range evaluated according to the potential conversion probability model;

[0009] Based on the potential emergency conversion scope of emergencies occurring to the evaluated target talent objects, determine the potential emergency conversion scope of emergencies occurring to the target talent objects in the corresponding job types, and propose a current rectification plan.

[0010] Furthermore, the process of establishing the potential judgment model is as follows:

[0011] Collect historical work variable data of target talents in the historical stages of corresponding work types;

[0012] Collect the current job variable data of the target talent in the current stage under the corresponding job type;

[0013] Collect the planned work variable data of the target talent in the planning stage under the corresponding work type;

[0014] According to the work variable data of the target talent in different stages of the corresponding work type, establish a historical conversion evaluation function for the work variable data in the historical work scenario, establish a current conversion evaluation function for the work variable data in the current work scenario, and establish a planned conversion evaluation function for the work variable data in the planned work scenario;

[0015] Based on the historical conversion evaluation function, the current conversion evaluation function and the planned conversion evaluation function, a potential determination model is obtained to evaluate the work variable data of the target talent object converted over time under the corresponding work type;

[0016] Based on the work variable data of the corresponding work type obtained by evaluation, and according to the expression of the probability of emergency occurrence evaluated, the potential existence range of emergency events occurring to the target talent object in the corresponding work type is obtained.

[0017] Furthermore, the process of establishing the potential conversion probability model is as follows:

[0018] Determine the environment of the target talent object, and based on the environmental information of the target talent object, collect historical work information, current work information, and planned work information related to the environmental information of the target talent object;

[0019] Based on the historical work information, current work information and planned work information, the historical conversion evaluation function, the current conversion evaluation function and the planned conversion evaluation function are substituted to update the preset algorithms in different conversion evaluation functions;

[0020] Based on the updated historical conversion evaluation function, current conversion evaluation function and planned conversion evaluation function, a potential conversion probability model is obtained, and the evaluation is modified to obtain the work variable data of the target talent object converted over time under the corresponding work type;

[0021] Based on the work variable data of the corresponding work type obtained by the revised evaluation, the potential existence range is revised according to the expression of the probability of the emergency occurring in the evaluation, so as to obtain the potential emergency conversion range of the target talent object when an emergency occurs in the corresponding work type.

[0022] Furthermore, the probability expression of evaluating the occurrence of an emergency is:

[0023]

[0024] Among them, H 1 is the probability range of emergencies in historical work scenarios, h1 is the work variable data evaluated in historical work scenarios, t1 is the current time in historical work scenarios, g 1 [(h1) t1 is the preset function in the historical working scenario; H 2 is the probability range of an emergency in the current work scenario, h2 is the work variable data evaluated in the current work scenario, and t2 is the current time g in the current work scenario. 2 [(h2) t2 ] is the preset function in the current working scenario; H 3 is the probability range of an emergency under the current work scenario, h3 is the work variable data evaluated under the current work scenario, and t3 is the current time g under the planned work scenario. 3 [(h3) t3 It is the preset function for the planned working scenario.

[0025] Furthermore, the potential emergency event conversion scope of the target talent object based on the evaluation of the emergency event occurs, determines the potential emergency event conversion scope of the target talent object under the corresponding job type, and proposes a current rectification plan, which specifically includes:

[0026] Collect the historical potential emergency event conversion range of the target talent object's emergency events at different current times under historical work scenarios, the current potential emergency event conversion range of the emergency events at different current times under current work scenarios, and the planned potential emergency event conversion range of the emergency events at different current times under planned work scenarios;

[0027] Set the historical probability threshold range of emergencies occurring in historical working scenarios, the current probability threshold range of emergencies occurring in current working scenarios, and the planned probability threshold range of emergencies occurring in planned working scenarios;

[0028] If the historical potential emergency event conversion range falls within the historical probability threshold range, the current time is set as the current threshold in the historical working scenario; if the current potential emergency event conversion range falls within the current probability threshold range, the current time is set as the current threshold in the current working scenario; if the planned potential emergency event conversion range falls within the planned probability threshold range, the current time is set as the current threshold in the planned working scenario;

[0029] Based on the obtained current threshold value of the corresponding job type, provide the target talent with the best current time under the corresponding job type;

[0030] The historical work scenario refers to the target talent objects that have resigned historically, the current work scenario refers to the target talent objects that are currently employed, and the planned work scenario refers to the target talent objects that may resign.

[0031] According to a second aspect of the present invention, the present invention claims protection for a talent data processing device based on a big data model, comprising:

[0032] The information collection module is used to collect the work variable data of the target talent in the historical work scenarios, current work scenarios and planned work scenarios;

[0033] A historical information processing module, used to process the work variable data of the corresponding work type, and obtain the potential existence range of emergencies of the target talent object under the corresponding work type;

[0034] The current information processing module is used to process the environmental information of the target talent object and the characteristic information about the environment, and obtain the potential emergency event conversion range of the target talent object in the corresponding work type;

[0035] The feedback module is used to propose a current rectification plan based on the potential emergency event conversion scope of the target talent object when an emergency event occurs in the corresponding work type.

[0036] Furthermore, the establishment process of the potential determination model is as follows:

[0037] Collect historical work variable data of target talents in the historical stages of corresponding work types;

[0038] Collect the current job variable data of the target talent in the current stage under the corresponding job type;

[0039] Collect the planned work variable data of the target talent in the planning stage under the corresponding work type;

[0040] According to the work variable data of the target talent in different stages of the corresponding work type, establish a historical conversion evaluation function for the work variable data in the historical work scenario, establish a current conversion evaluation function for the work variable data in the current work scenario, and establish a planned conversion evaluation function for the work variable data in the planned work scenario;

[0041] Based on the historical conversion evaluation function, the current conversion evaluation function and the planned conversion evaluation function, a potential determination model is obtained to evaluate the work variable data of the target talent object converted over time under the corresponding work type;

[0042] Based on the work variable data of the corresponding work type obtained by evaluation, and according to the expression of the probability of emergency occurrence evaluated, the potential existence range of emergency events occurring to the target talent object in the corresponding work type is obtained.

[0043] Furthermore, the establishment process of the potential conversion probability model is as follows:

[0044] Determine the environment of the target talent object, and based on the environmental information of the target talent object, collect historical work information, current work information, and planned work information related to the environmental information of the target talent object;

[0045] Based on the historical work information, current work information and planned work information, the historical conversion evaluation function, the current conversion evaluation function and the planned conversion evaluation function are substituted to update the preset algorithms in different conversion evaluation functions;

[0046] Based on the updated historical conversion evaluation function, current conversion evaluation function and planned conversion evaluation function, a potential conversion probability model is obtained, and the evaluation is modified to obtain the work variable data of the target talent object converted over time under the corresponding work type;

[0047] Based on the work variable data of the corresponding work type obtained by the revised evaluation, the potential existence range is revised according to the expression of the probability of the emergency occurring in the evaluation, so as to obtain the potential emergency conversion range of the target talent object when an emergency occurs in the corresponding work type.

[0048] Furthermore, the probability expression of evaluating the occurrence of an emergency is:

[0049]

[0050] Among them, H 1 is the probability range of emergencies in historical work scenarios, h1 is the work variable data evaluated in historical work scenarios, t1 is the current time in historical work scenarios, g 1 [(h1) t1 is the preset function in the historical working scenario; H 2is the probability range of an emergency in the current work scenario, h2 is the work variable data evaluated in the current work scenario, and t2 is the current time g in the current work scenario. 2 [(h2) t2 ] is the preset function in the current working scenario; H 3 is the probability range of an emergency under the current work scenario, h2 is the work variable data evaluated under the current work scenario, and t3 is the current time g under the planned work scenario. 3 [(h3) t3 It is the preset function for the planned working scenario.

[0051] Furthermore, the potential emergency event conversion scope of the target talent object based on the evaluation of the emergency event occurs, determines the potential emergency event conversion scope of the target talent object under the corresponding job type, and proposes a current rectification plan, which specifically includes:

[0052] Collect the historical potential emergency event conversion range of the target talent object's emergency events at different current times under historical work scenarios, the current potential emergency event conversion range of the emergency events at different current times under current work scenarios, and the planned potential emergency event conversion range of the emergency events at different current times under planned work scenarios;

[0053] Set the historical probability threshold range of emergencies occurring in historical working scenarios, the current probability threshold range of emergencies occurring in current working scenarios, and the planned probability threshold range of emergencies occurring in planned working scenarios;

[0054] If the historical potential emergency event conversion range falls within the historical probability threshold range, the current time is set as the current threshold in the historical working scenario; if the current potential emergency event conversion range falls within the current probability threshold range, the current time is set as the current threshold in the current working scenario; if the planned potential emergency event conversion range falls within the planned probability threshold range, the current time is set as the current threshold in the planned working scenario;

[0055] Based on the obtained current threshold value of the corresponding job type, provide the target talent with the best current time under the corresponding job type;

[0056] The historical work scenario refers to the target talent objects that have resigned historically, the current work scenario refers to the target talent objects that are currently employed, and the planned work scenario refers to the target talent objects that may resign.

[0057] The present invention relates to the field of data security technology, and specifically to a talent data processing method and device based on a big data model, which collects work variable data of a target talent object in a work scenario; based on the work variable data of the target talent object corresponding to the work type, evaluates the potential existence range of emergencies of the target talent object under the corresponding work type according to a potential judgment model; collects environmental information of the target talent object and characteristic information about the environment, and determines the potential emergency conversion range based on the evaluated potential existence range according to a potential conversion probability model; determines the potential emergency conversion range of emergencies of the target talent object under the corresponding work type, and proposes a current rectification plan. The present invention can fully explore the correlation between the safety potential of each current state project under various different scenarios and the occurrence of emergencies, and proposes practical evaluation results and rectification plans. BRIEF DESCRIPTION OF THE DRAWINGS

[0058] Figure 1 This is a workflow diagram of a talent data processing method based on a big data model according to the present invention;

[0059] Figure 2 A second workflow diagram of a talent data processing method based on a big data model according to the present invention;

[0060] Figure 3 A third workflow diagram of a talent data processing method based on a big data model according to the present invention;

[0061] Figure 4 The present invention relates to a structural module diagram of a talent data processing device based on a big data model. DETAILED DESCRIPTION

[0062] According to the first embodiment of the present invention, referring to the attached Figure 1 The present invention claims a talent data processing method based on a big data model, comprising:

[0063] Collect work variable data of target talent objects in historical work scenarios, current work scenarios, and planned work scenarios, wherein the historical work scenarios are target talent objects that have resigned in the past, the current work scenarios are target talent objects that are currently employed, and the planned work scenarios are target talent objects that are potentially leaving;

[0064] Based on the work variable data of the target talent object's corresponding work type, according to the potential judgment model, evaluate the potential existence range of emergencies that may occur to the target talent object in the corresponding work type;

[0065] Collecting the environmental information and characteristic information about the environment of the target talent object, and determining the potential emergency event conversion range based on the potential existence range evaluated according to the potential conversion probability model;

[0066] Based on the potential emergency conversion scope of emergencies occurring to the evaluated target talent objects, determine the potential emergency conversion scope of emergencies occurring to the target talent objects in the corresponding job types, and propose a current rectification plan.

[0067] Among them, in this embodiment, based on the current process, environmental conditions and management organization, combined with standard specifications, safety potential historical database, emergency cases and expert experience, the safety potential that may arise in the current process is pre-identified, and predefined safety potential items are set. According to the risk level of the predefined safety potential items and in accordance with unified quantification rules, the predefined safety potential items are quantified to form a safety potential list.

[0068] Specifically, the target talent objects collected in this embodiment may be historical work scenarios, current work scenarios, and planned work scenarios. Correspondingly, different work parameter indicators need to be collected in different scenarios for potential identification analysis.

[0069] In the above historical work scenario, for the target talent who has left the company in the past, the historical work variable data refers to the work plan indicator data, the degree of fit of the work completion schedule plan, and the work acceptance quality data;

[0070] When in the current work scenario, for the target talent object in employment, the current work variable data refers to the work plan indicator data and the degree of fit of the work completion progress plan;

[0071] When in the planned work scenario, for potential target talent objects for resignation, the planned work variable data refers to the work plan indicator data.

[0072] Furthermore, the process of establishing the potential judgment model is as follows:

[0073] Collect historical work variable data of target talents in the historical stages of corresponding work types;

[0074] Collect the current job variable data of the target talent in the current stage under the corresponding job type;

[0075] Collect the planned work variable data of the target talent in the planning stage under the corresponding work type;

[0076] According to the work variable data of the target talent in different stages of the corresponding work type, establish a historical conversion evaluation function for the work variable data in the historical work scenario, establish a current conversion evaluation function for the work variable data in the current work scenario, and establish a planned conversion evaluation function for the work variable data in the planned work scenario;

[0077] Based on the historical conversion evaluation function, the current conversion evaluation function and the planned conversion evaluation function, a potential determination model is obtained to evaluate the work variable data of the target talent object converted over time under the corresponding work type;

[0078] Based on the work variable data of the corresponding work type obtained by evaluation, and according to the expression of the probability of emergency occurrence evaluated, the potential existence range of emergency events occurring to the target talent object in the corresponding work type is obtained.

[0079] Among them, in this embodiment, historical work variable data refers to work plan indicator data, work completion schedule compliance, and work acceptance quality data, and the work plan indicator data at least include work type, work cycle, work schedule, output data, work equipment type, work equipment quantity, and work equipment indicators; the work completion schedule compliance includes at least the deviation of the completion degree of the work after daily decomposition compared with the work schedule; the work acceptance quality data includes at least the deviation between the actual work output and the output data, the deviation between the actual work cycle and the work cycle, and the work equipment wear and tear.

[0080] The types of work include at least: overseas assignment, external reception, research and development, and administrative work;

[0081] The potential scope of emergencies that may occur to the target talent under the corresponding work type, the potential scope of expatriate work at least includes the number of expatriates, diseases of expatriates, environmental weather of expatriates, and preparatory measures for expatriates;

[0082] The potential scope of external reception work at least includes the types of external reception business, the number of external reception business, the frequency of external reception business, the characteristics of external reception business customers, and the working environment of external reception business;

[0083] The potential scope of R&D work category at least includes R&D business type, R&D business quantity, R&D business customer characteristics, and R&D business work environment;

[0084] The potential scope of administrative work includes at least human resources work, financial work, and security work.

[0085] Further, see Figure 2 , the establishment process of the potential conversion probability model is:

[0086] Determine the environment of the target talent object, and based on the environmental information of the target talent object, collect historical work information, current work information, and planned work information related to the environmental information of the target talent object;

[0087] Based on the historical work information, current work information and planned work information, the historical conversion evaluation function, the current conversion evaluation function and the planned conversion evaluation function are substituted to update the preset algorithms in different conversion evaluation functions;

[0088] Based on the updated historical conversion evaluation function, current conversion evaluation function and planned conversion evaluation function, a potential conversion probability model is obtained, and the evaluation is modified to obtain the work variable data of the target talent object converted over time under the corresponding work type;

[0089] Based on the work variable data of the corresponding work type obtained by the revised evaluation, the potential existence range is revised according to the expression of the probability of the emergency occurring in the evaluation, so as to obtain the potential emergency conversion range of the target talent object when an emergency occurs in the corresponding work type.

[0090] Among them, in this embodiment, the environmental information of the working process at least includes the working area, the wind speed of the workplace, the working environment temperature, and the working environment humidity.

[0091] In the potential emergency conversion scope of the target talent object in the corresponding work type, the emergency events of the outbound work category include at least: personnel accidents, personnel unplanned trips, personnel violations and crimes;

[0092] Emergency events related to external reception work include at least: unexpected contents of external reception business plan, conflicts between personnel and customers;

[0093] Emergencies related to R&D work include at least: environmental hazards and risks to personnel health;

[0094] Administrative work-related emergencies include at least: employee disputes, financial risks, and security risks.

[0095] Furthermore, the probability expression of evaluating the occurrence of an emergency is:

[0096]

[0097] Among them, H 1 is the probability range of emergencies in historical work scenarios, h1 is the work variable data evaluated in historical work scenarios, t1 is the current time in historical work scenarios, g 1 [(h1) t1 is the preset function in the historical working scenario; H 2 is the probability range of an emergency in the current work scenario, h2 is the work variable data evaluated in the current work scenario, and t2 is the current time g in the current work scenario. 2 [(h2) t2 ] is the preset function in the current working scenario; H 3is the probability range of an emergency under the current work scenario, h2 is the work variable data evaluated under the current work scenario, and t3 is the current time g under the planned work scenario. 3 [(h3) t3 It is the preset function for the planned working scenario.

[0098] Further, see Figure 3 , the transformation scope of the potential emergencies of the target talent object based on the evaluation, determine the transformation scope of the potential emergencies of the target talent object under the corresponding work type, and propose the current rectification plan, which specifically includes:

[0099] Collect the historical potential emergency event conversion range of the target talent object's emergency events at different current times under historical work scenarios, the current potential emergency event conversion range of the emergency events at different current times under current work scenarios, and the planned potential emergency event conversion range of the emergency events at different current times under planned work scenarios;

[0100] Set the historical probability threshold range of emergencies occurring in historical working scenarios, the current probability threshold range of emergencies occurring in current working scenarios, and the planned probability threshold range of emergencies occurring in planned working scenarios;

[0101] If the historical potential emergency event conversion range falls within the historical probability threshold range, the current time is set as the current threshold in the historical working scenario; if the current potential emergency event conversion range falls within the current probability threshold range, the current time is set as the current threshold in the current working scenario; if the planned potential emergency event conversion range falls within the planned probability threshold range, the current time is set as the current threshold in the planned working scenario;

[0102] Based on the obtained current threshold value of the corresponding job type, the best current time of the corresponding job type is provided to the target talent.

[0103] The historical work scenario refers to the target talent objects that have resigned historically, the current work scenario refers to the target talent objects that are currently employed, and the planned work scenario refers to the target talent objects that may resign.

[0104] According to the second embodiment of the present invention, referring to Figure 4 The present invention claims protection for a talent data processing device based on a big data model, comprising:

[0105] The information collection module is used to collect the work variable data of the target talent in the historical work scenarios, current work scenarios and planned work scenarios;

[0106] A historical information processing module, used to process the work variable data of the corresponding work type, and obtain the potential existence range of emergencies of the target talent object under the corresponding work type;

[0107] The current information processing module is used to process the environmental information of the target talent object and the characteristic information about the environment, and obtain the potential emergency event conversion range of the target talent object in the corresponding work type;

[0108] The feedback module is used to propose a current rectification plan based on the potential emergency event conversion scope of the target talent object when an emergency event occurs in the corresponding work type.

[0109] Furthermore, the establishment process of the potential determination model is as follows:

[0110] Collect historical work variable data of target talents in the historical stages of corresponding work types;

[0111] Collect the current job variable data of the target talent in the current stage under the corresponding job type;

[0112] Collect the planned work variable data of the target talent in the planning stage under the corresponding work type;

[0113] According to the work variable data of the target talent in different stages of the corresponding work type, establish a historical conversion evaluation function for the work variable data in the historical work scenario, establish a current conversion evaluation function for the work variable data in the current work scenario, and establish a planned conversion evaluation function for the work variable data in the planned work scenario;

[0114] Based on the historical conversion evaluation function, the current conversion evaluation function and the planned conversion evaluation function, a potential determination model is obtained to evaluate the work variable data of the target talent object converted over time under the corresponding work type;

[0115] Based on the work variable data of the corresponding work type obtained by evaluation, and according to the expression of the probability of emergency occurrence evaluated, the potential existence range of emergency events occurring to the target talent object in the corresponding work type is obtained.

[0116] Furthermore, the establishment process of the potential conversion probability model is as follows:

[0117] Determine the environment of the target talent object, and based on the environmental information of the target talent object, collect historical work information, current work information, and planned work information related to the environmental information of the target talent object;

[0118] Based on the historical work information, current work information and planned work information, the historical conversion evaluation function, the current conversion evaluation function and the planned conversion evaluation function are substituted to update the preset algorithms in different conversion evaluation functions;

[0119] Based on the updated historical conversion evaluation function, current conversion evaluation function and planned conversion evaluation function, a potential conversion probability model is obtained, and the evaluation is modified to obtain the work variable data of the target talent object converted over time under the corresponding work type;

[0120] Based on the work variable data of the corresponding work type obtained by the revised evaluation, the potential existence range is revised according to the expression of the probability of the emergency occurring in the evaluation, so as to obtain the potential emergency conversion range of the target talent object when an emergency occurs in the corresponding work type.

[0121] Furthermore, the probability expression of evaluating the occurrence of an emergency is:

[0122]

[0123] Among them, H 1 is the probability range of emergencies in historical work scenarios, h1 is the work variable data evaluated in historical work scenarios, t1 is the current time in historical work scenarios, g 1 [(h1) t1 is the preset function in the historical working scenario; H 2 is the probability range of an emergency in the current work scenario, h2 is the work variable data evaluated in the current work scenario, and t2 is the current time g in the current work scenario. 2 [(h2) t2 ] is the preset function in the current working scenario; H 3 is the probability range of an emergency under the current work scenario, h3 is the work variable data evaluated under the current work scenario, and t3 is the current time g under the planned work scenario. 3 [(h3) t3 It is the preset function for the planned working scenario.

[0124] Furthermore, the potential emergency event conversion scope of the target talent object based on the evaluation of the emergency event occurs, determines the potential emergency event conversion scope of the target talent object under the corresponding job type, and proposes a current rectification plan, which specifically includes:

[0125] Collect the historical potential emergency event conversion range of the target talent object's emergency events at different current times under historical work scenarios, the current potential emergency event conversion range of the emergency events at different current times under current work scenarios, and the planned potential emergency event conversion range of the emergency events at different current times under planned work scenarios;

[0126] Set the historical probability threshold range of emergencies occurring in historical working scenarios, the current probability threshold range of emergencies occurring in current working scenarios, and the planned probability threshold range of emergencies occurring in planned working scenarios;

[0127] If the historical potential emergency event conversion range falls within the historical probability threshold range, the current time is set as the current threshold in the historical working scenario; if the current potential emergency event conversion range falls within the current probability threshold range, the current time is set as the current threshold in the current working scenario; if the planned potential emergency event conversion range falls within the planned probability threshold range, the current time is set as the current threshold in the planned working scenario;

[0128] Based on the obtained current threshold value of the corresponding job type, provide the target talent with the best current time under the corresponding job type;

[0129] The historical work scenario refers to the target talent objects that have resigned historically, the current work scenario refers to the target talent objects that are currently employed, and the planned work scenario refers to the target talent objects that may resign.

[0130] Those skilled in the art will appreciate that the contents disclosed in this disclosure may be subject to various modifications and improvements. For example, the various devices or components described above may be implemented by hardware, or by software, firmware, or a combination of some or all of the three.

[0131] Flowcharts are used in this disclosure to illustrate the steps of the method according to the embodiments of the present disclosure. It should be understood that the preceding or following steps are not necessarily performed precisely in order. On the contrary, various steps may be processed in reverse order or simultaneously. At the same time, other operations may also be added to these processes.

[0132] Those skilled in the art will appreciate that all or part of the steps in the above method can be completed by instructing related hardware through a computer program, and the program can be stored in a computer-readable storage medium, such as a read-only memory, a disk, or an optical disk. Optionally, all or part of the steps in the above embodiment can also be implemented using one or more integrated circuits. Accordingly, each module / unit in the above embodiment can be implemented in the form of hardware or in the form of a software functional module. The present disclosure is not limited to any particular form of combination of hardware and software.

[0133] Unless otherwise defined, all terms used herein have the same meaning as commonly understood by those of ordinary skill in the art to which the present disclosure belongs. It should also be understood that terms such as those defined in common dictionaries should be interpreted as having a meaning consistent with their meaning in the context of the relevant technology, and should not be interpreted in an idealized or highly formal sense, unless explicitly defined as such herein.

[0134] The above is an explanation of the present disclosure and should not be considered as a limitation thereof. Although several exemplary embodiments of the present disclosure are described, it will be readily understood by those skilled in the art that many modifications may be made to the exemplary embodiments without departing from the novel teachings and advantages of the present disclosure. Therefore, all such modifications are intended to be included within the scope of the present disclosure as defined in the claims. It should be understood that the above is an explanation of the present disclosure and should not be considered to be limited to the specific embodiments disclosed, and modifications to the disclosed embodiments and other embodiments are intended to be included within the scope of the appended claims. The present disclosure is defined by the claims and their equivalents.

[0135] In the description of this specification, the description with reference to the terms "one embodiment", "some embodiments", "illustrative embodiments", "examples", "specific examples", or "some examples" means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner.

[0136] Although embodiments of the present invention have been shown and described, those skilled in the art will appreciate that various transformations, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the claims and their equivalents.

Claims

1. A talent data processing method based on a big data model, characterized in that: include: Collect work variable data of target talent objects in historical work scenarios, current work scenarios, and planned work scenarios, wherein the historical work scenarios are target talent objects that have resigned in the past, the current work scenarios are target talent objects that are currently employed, and the planned work scenarios are target talent objects that are potentially leaving; Based on the work variable data of the target talent object's corresponding work type, according to the potential judgment model, evaluate the potential existence range of emergencies that may occur to the target talent object in the corresponding work type; Collecting the environmental information and characteristic information about the environment of the target talent object, and determining the potential emergency event conversion range based on the potential existence range evaluated according to the potential conversion probability model; Based on the potential emergency conversion scope of emergencies occurring to the evaluated target talent objects, determine the potential emergency conversion scope of emergencies occurring to the target talent objects in the corresponding job types, and propose a current rectification plan.

2. A talent data processing method based on a big data model as claimed in claim 1, characterized in that: The establishment process of the potential judgment model is as follows: Collect historical work variable data of target talents in the historical stages of corresponding work types; Collect the current job variable data of the target talent in the current stage under the corresponding job type; Collect the planned work variable data of the target talent in the planning stage under the corresponding work type; According to the work variable data of the target talent in different stages of the corresponding work type, establish a historical conversion evaluation function for the work variable data in the historical work scenario, establish a current conversion evaluation function for the work variable data in the current work scenario, and establish a planned conversion evaluation function for the work variable data in the planned work scenario; Based on the historical conversion evaluation function, the current conversion evaluation function and the planned conversion evaluation function, a potential determination model is obtained to evaluate the work variable data of the target talent object converted over time under the corresponding work type; Based on the work variable data of the corresponding work type obtained by evaluation, and according to the expression of the probability of emergency occurrence evaluated, the potential existence range of emergency events occurring to the target talent object in the corresponding work type is obtained.

3. A talent data processing method based on a big data model as claimed in claim 2, characterized in that: The establishment process of the potential conversion probability model is as follows: Determine the environment of the target talent object, and based on the environmental information of the target talent object, collect historical work information, current work information, and planned work information related to the environmental information of the target talent object; Based on the historical work information, current work information and planned work information, the historical conversion evaluation function, the current conversion evaluation function and the planned conversion evaluation function are substituted to update the preset algorithms in different conversion evaluation functions; Based on the updated historical conversion evaluation function, current conversion evaluation function and planned conversion evaluation function, a potential conversion probability model is obtained, and the evaluation is modified to obtain the work variable data of the target talent object converted over time under the corresponding work type; Based on the work variable data of the corresponding work type obtained by the revised evaluation, the potential existence range is revised according to the expression of the probability of the emergency occurring in the evaluation, so as to obtain the potential emergency conversion range of the target talent object when an emergency occurs in the corresponding work type.

4. A talent data processing method based on a big data model as claimed in claim 3, characterized in that: The probability expression of the emergency event is: Among them, H1 is the probability range of emergencies in historical work scenarios, h1 is the work variable data evaluated in historical work scenarios, t1 is the current time in historical work scenarios, g1[(h1) t1 is the preset function under the historical work scenario; H2 is the probability range of an emergency under the current work scenario, h2 is the work variable data evaluated under the current work scenario, t2 is the current time under the current work scenario, g2[(h2) t2 ] is the preset function in the current working scenario; H3 is the probability range of the emergency in the current working scenario, h3 is the working variable data evaluated in the current working scenario, t3 is the current time in the planned working scenario, g3[(h3) t3 It is the preset function for the planned working scenario.

5. The talent data processing method based on the big data model according to claim 4 is characterized in that: The potential emergency event conversion scope of the target talent object based on the evaluation of the emergency event occurs, determines the potential emergency event conversion scope of the target talent object under the corresponding work type, and proposes a current rectification plan, which specifically includes: Collect the historical potential emergency event conversion range of the target talent object's emergency events at different current times under historical work scenarios, the current potential emergency event conversion range of the emergency events at different current times under current work scenarios, and the planned potential emergency event conversion range of the emergency events at different current times under planned work scenarios; Set the historical probability threshold range of emergencies occurring in historical working scenarios, the current probability threshold range of emergencies occurring in current working scenarios, and the planned probability threshold range of emergencies occurring in planned working scenarios; If the historical potential emergency event conversion range falls within the historical probability threshold range, the current time is set as the current threshold in the historical working scenario; if the current potential emergency event conversion range falls within the current probability threshold range, the current time is set as the current threshold in the current working scenario; if the planned potential emergency event conversion range falls within the planned probability threshold range, the current time is set as the current threshold in the planned working scenario; Based on the obtained current threshold value of the corresponding job type, provide the target talent with the best current time under the corresponding job type; The historical work scenario refers to the target talent objects that have resigned historically, the current work scenario refers to the target talent objects that are currently employed, and the planned work scenario refers to the target talent objects that may resign.

6. A talent data processing device based on a big data model, characterized in that: include: The information collection module is used to collect the work variable data of the target talent in the historical work scenarios, current work scenarios and planned work scenarios; A historical information processing module, used to process the work variable data of the corresponding work type, and obtain the potential existence range of emergencies of the target talent object under the corresponding work type; The current information processing module is used to process the environmental information of the target talent object and the characteristic information about the environment, and obtain the potential emergency event conversion range of the target talent object in the corresponding work type; The feedback module is used to propose a current rectification plan based on the potential emergency event conversion scope of the target talent object when an emergency event occurs in the corresponding work type.

7. A talent data processing device based on a big data model as claimed in claim 6, characterized in that: The establishment process of the potential judgment model is as follows: Collect historical work variable data of target talents in the historical stages of corresponding work types; Collect the current job variable data of the target talent in the current stage under the corresponding job type; Collect the planned work variable data of the target talent in the planning stage under the corresponding work type; According to the work variable data of the target talent in different stages of the corresponding work type, establish a historical conversion evaluation function for the work variable data in the historical work scenario, establish a current conversion evaluation function for the work variable data in the current work scenario, and establish a planned conversion evaluation function for the work variable data in the planned work scenario; Based on the historical conversion evaluation function, the current conversion evaluation function and the planned conversion evaluation function, a potential determination model is obtained to evaluate the work variable data of the target talent object converted over time under the corresponding work type; Based on the work variable data of the corresponding work type obtained by evaluation, and according to the expression of the probability of emergency occurrence evaluated, the potential existence range of emergency events occurring to the target talent object in the corresponding work type is obtained.

8. A talent data processing device based on a big data model as claimed in claim 7, characterized in that: The establishment process of the potential conversion probability model is as follows: Determine the environment of the target talent object, and based on the environmental information of the target talent object, collect historical work information, current work information, and planned work information related to the environmental information of the target talent object; Based on the historical work information, current work information and planned work information, the historical conversion evaluation function, the current conversion evaluation function and the planned conversion evaluation function are substituted to update the preset algorithms in different conversion evaluation functions; Based on the updated historical conversion evaluation function, current conversion evaluation function and planned conversion evaluation function, a potential conversion probability model is obtained, and the evaluation is modified to obtain the work variable data of the target talent object converted over time under the corresponding work type; Based on the work variable data of the corresponding work type obtained by the revised evaluation, the potential existence range is revised according to the expression of the probability of the emergency occurring in the evaluation, so as to obtain the potential emergency conversion range of the target talent object when an emergency occurs in the corresponding work type.

9. A talent data processing device based on a big data model as claimed in claim 8, characterized in that: The probability expression of the emergency event is: Among them, H1 is the probability range of emergencies in historical work scenarios, h1 is the work variable data evaluated in historical work scenarios, t1 is the current time in historical work scenarios, g1[(h1) t1 is the preset function under the historical work scenario; H2 is the probability range of an emergency under the current work scenario, h2 is the work variable data evaluated under the current work scenario, t2 is the current time under the current work scenario, g2[(h2) t2 ] is the preset function in the current working scenario; H3 is the probability range of the emergency in the current working scenario, h3 is the working variable data evaluated in the current working scenario, t3 is the current time in the planned working scenario, g3[(h3) t3 It is the preset function for the planned working scenario.

10. A talent data processing device based on a big data model as claimed in claim 9, characterized in that: The potential emergency event conversion scope of the target talent object based on the evaluation of the emergency event occurs, determines the potential emergency event conversion scope of the target talent object under the corresponding work type, and proposes a current rectification plan, which specifically includes: Collect the historical potential emergency event conversion range of the target talent object's emergency events at different current times under historical work scenarios, the current potential emergency event conversion range of the emergency events at different current times under current work scenarios, and the planned potential emergency event conversion range of the emergency events at different current times under planned work scenarios; Set the historical probability threshold range of emergencies occurring in historical working scenarios, the current probability threshold range of emergencies occurring in current working scenarios, and the planned probability threshold range of emergencies occurring in planned working scenarios; If the historical potential emergency event conversion range falls within the historical probability threshold range, the current time is set as the current threshold in the historical working scenario; if the current potential emergency event conversion range falls within the current probability threshold range, the current time is set as the current threshold in the current working scenario; if the planned potential emergency event conversion range falls within the planned probability threshold range, the current time is set as the current threshold in the planned working scenario; Based on the obtained current threshold value of the corresponding job type, provide the target talent with the best current time under the corresponding job type; The historical work scenario refers to the target talent objects that have resigned historically, the current work scenario refers to the target talent objects that are currently employed, and the planned work scenario refers to the target talent objects that may resign.

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