Rural human resource intelligent management method and system

Abstract

The invention provides a rural human resource intelligent management method and system, and the method comprises the steps: monitoring a to-be-managed target event based on a human resource library of a target rural area; deciding a first event management strategy of the target event based on a knowledge base of rural human resource management; and performing corresponding management on the target event based on the first event management strategy. According to the rural human resource intelligent management method and system, the to-be-managed target event is automatically monitored based on the human resource library of the target rural area, the first event management strategy of the target event is automatically decided based on the knowledge library of rural human resource management, and finally, the to-be-managed target event is automatically managed based on the first event management strategy. Therefore, the target event is correspondingly managed without manual rural human resource management by managers, so that the human cost is reduced, and the management efficiency is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of human resource management, and in particular to a rural human resource intelligent management method and system thereof. Background Art

[0002] Rural human resource management is crucial to improving agricultural productivity and promoting social and economic development. Specifically, by rationally allocating and optimizing rural labor, agricultural efficiency can be improved, the diversification of the rural economy can be promoted, and farmers' living standards and employment opportunities can be improved. In addition, as the flow of urban and rural populations intensifies, scientific human resource management can effectively solve labor shortages, improve work skills, and help rural areas adapt to the process of modernization.

[0003] However, in traditional rural human resource management, the monitoring of events that need to be managed and the decision-making of management strategies are mostly done manually by multiple managers, which results in high labor costs and insufficient management efficiency.

[0004] Therefore, a solution is urgently needed. Summary of the invention

[0005] One of the purposes of the present invention is to provide a method for intelligent management of rural human resources, which automatically monitors target events to be managed based on the human resources database of the target rural area, automatically decides the first event management strategy for the target event based on the knowledge base of rural human resources management, and finally manages the target event accordingly based on the first event management strategy. There is no need for management personnel to manually manage rural human resources, which reduces labor costs and improves management efficiency.

[0006] An embodiment of the present invention provides a rural human resources intelligent management method, comprising:

[0007] Based on the human resource pool of target villages, monitor the target events to be managed;

[0008] Based on the knowledge base of rural human resource management, the first event management strategy for decision-making target events;

[0009] Based on the first event management strategy, the target event is managed accordingly.

[0010] Optionally, after managing the target event accordingly based on the first event management strategy, the method further includes:

[0011] Evaluate the management effect of the target event and obtain the evaluation value;

[0012] When the evaluation value does not exceed the evaluation value threshold, a second event management strategy for online assisting the user in deciding the target event;

[0013] Based on the second event management strategy, the target event is managed accordingly.

[0014] Optionally, the second event management strategy for online assisting users in making decisions about target events includes:

[0015] Display the target event to the user;

[0016] Continuously track the user's viewing history of the displayed target event;

[0017] Generate decision-making rhythm control timeline in real time based on viewing history;

[0018] Based on the decision-making rhythm, the timeline is controlled to control the rhythm of the user's management decision-making for the target event accordingly;

[0019] receiving a second event management strategy input by the user after completing the management decision;

[0020] The step of generating a decision-making rhythm control timeline in real time based on the viewing history includes:

[0021] obtaining multiple initial decision rhythm items of the event type of the target event;

[0022] Based on the viewing history, multiple target decision rhythm items are selected from each initial decision rhythm item, and the rhythm sequence of each target decision rhythm item and the rhythm holding time of each target decision rhythm item are determined;

[0023] Based on the constraints set by the rhythm items, each target decision rhythm item is sequentially set on the initial time axis;

[0024] The initial time axis after each target decision rhythm item is set in sequence is used as the decision rhythm control time axis;

[0025] The rhythm item setting constraints include:

[0026] Constraint 1: Set each target decision rhythm item in sequence from the starting point of the initial time axis based on the rhythm sequence;

[0027] as well as,

[0028] Constraint 2: The on-axis distance between adjacent target decision rhythm items on the initial time axis is the rhythm maintenance duration of the former of the corresponding adjacent target decision rhythm items.

[0029] Optionally, based on the viewing history, a plurality of target decision rhythm items are screened out from each initial decision rhythm item, and a rhythm sequence of each target decision rhythm item and a rhythm holding time of each target decision rhythm item are determined, including:

[0030] Determine the degree of association between each initial decision rhythm item and the viewing history; wherein the degree of association is the sum of the mapping values ​​of at least one mapping node mapped by the viewing history in the association mapping tree of the initial decision rhythm item;

[0031] taking the initial decision rhythm items whose relevance exceeds the first threshold of the relevance as the first candidate items, and taking the remaining initial decision rhythm items as the second candidate items;

[0032] The first candidate item and the second candidate item having a rhythm association relationship with the first candidate item are used as a plurality of target decision rhythm items;

[0033] When there is a target decision rhythm item whose correlation exceeds the second threshold of the correlation and the user's decision history is empty, based on the target decision rhythm item whose correlation exceeds the second threshold of the correlation, query the rhythm layout rule library to obtain the first rhythm layout rule, and based on the first rhythm layout rule, determine the rhythm sequence of each target decision rhythm item and the rhythm retention time of each target decision rhythm item; otherwise, based on the target decision rhythm item whose correlation exceeds the third threshold of the correlation and the user's decision history, query the rhythm layout rule library to obtain the second rhythm layout rule, and based on the second rhythm layout rule, determine the rhythm sequence of each target decision rhythm item and the rhythm retention time of each target decision rhythm item;

[0034] The second threshold of the degree of association is greater than the third threshold of the degree of association, which is greater than the first threshold of the degree of association.

[0035] Optionally, after taking over the corresponding management of the target event based on the second event management strategy, the method further includes:

[0036] Perform knowledge representation on target events and second event management strategies to obtain knowledge;

[0037] Set the knowledge into the knowledge base.

[0038] An embodiment of the present invention provides a rural human resources intelligent management system, including:

[0039] A monitoring module is used to monitor target events to be managed based on the human resource database of the target villages;

[0040] A decision-making module, used to decide the first event management strategy of the target event based on the knowledge base of rural human resource management;

[0041] The first management module is used to manage the target event accordingly based on the first event management strategy.

[0042] Optionally, after the first management module manages the target event accordingly based on the first event management strategy, the first management module further includes a second management module for:

[0043] Evaluate the management effect of the target event and obtain the evaluation value;

[0044] When the evaluation value does not exceed the evaluation value threshold, a second event management strategy for online assisting the user in deciding the target event;

[0045] Based on the second event management strategy, the target event is managed accordingly.

[0046] Optionally, the second management module online assists the user in deciding the second event management strategy for the target event, including:

[0047] Display the target event to the user;

[0048] Continuously track the user's viewing history of the displayed target event;

[0049] Generate decision-making rhythm control timeline in real time based on viewing history;

[0050] Based on the decision-making rhythm, the timeline is controlled to control the rhythm of the user's management decision-making for the target event accordingly;

[0051] receiving a second event management strategy input by the user after completing the management decision;

[0052] The step of generating a decision-making rhythm control timeline in real time based on the viewing history includes:

[0053] obtaining multiple initial decision rhythm items of the event type of the target event;

[0054] Based on the viewing history, multiple target decision rhythm items are selected from each initial decision rhythm item, and the rhythm sequence of each target decision rhythm item and the rhythm holding time of each target decision rhythm item are determined;

[0055] Based on the constraints set by the rhythm items, each target decision rhythm item is sequentially set on the initial time axis;

[0056] The initial time axis after each target decision rhythm item is set in sequence is used as the decision rhythm control time axis;

[0057] The rhythm item setting constraints include:

[0058] Constraint 1: Set each target decision rhythm item in sequence from the starting point of the initial time axis based on the rhythm sequence;

[0059] as well as,

[0060] Constraint 2: The on-axis distance between adjacent target decision rhythm items on the initial time axis is the rhythm maintenance duration of the former of the corresponding adjacent target decision rhythm items.

[0061] Optionally, the second management module selects a plurality of target decision rhythm items from each initial decision rhythm item based on the viewing history, and determines the rhythm sequence of each target decision rhythm item and the rhythm holding time of each target decision rhythm item, including:

[0062] Determine the degree of association between each initial decision rhythm item and the viewing history; wherein the degree of association is the sum of the mapping values ​​of at least one mapping node mapped by the viewing history in the association mapping tree of the initial decision rhythm item;

[0063] taking the initial decision rhythm items whose relevance exceeds the first threshold of the relevance as the first candidate items, and taking the remaining initial decision rhythm items as the second candidate items;

[0064] The first candidate item and the second candidate item having a rhythm association relationship with the first candidate item are used as a plurality of target decision rhythm items;

[0065] When there is a target decision rhythm item whose correlation exceeds the second threshold of the correlation and the user's decision history is empty, based on the target decision rhythm item whose correlation exceeds the second threshold of the correlation, query the rhythm layout rule library to obtain the first rhythm layout rule, and based on the first rhythm layout rule, determine the rhythm sequence of each target decision rhythm item and the rhythm retention time of each target decision rhythm item; otherwise, based on the target decision rhythm item whose correlation exceeds the third threshold of the correlation and the user's decision history, query the rhythm layout rule library to obtain the second rhythm layout rule, and based on the second rhythm layout rule, determine the rhythm sequence of each target decision rhythm item and the rhythm retention time of each target decision rhythm item;

[0066] The second threshold of the degree of association is greater than the third threshold of the degree of association, which is greater than the first threshold of the degree of association.

[0067] Optionally, after the second management module takes over the corresponding management of the target event based on the second event management strategy, it further includes a setting module for:

[0068] Perform knowledge representation on target events and second event management strategies to obtain knowledge;

[0069] Set the knowledge into the knowledge base.

[0070] Other features and advantages of the present invention will be described in the following description, and partly become apparent from the description, or understood by practicing the present invention. The purpose and other advantages of the present invention can be realized and obtained by the structures particularly pointed out in the written description and the accompanying drawings.

[0071] The technical solution of the present invention is further described in detail below through the accompanying drawings and embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0072] The accompanying drawings are used to provide a further understanding of the present invention and constitute a part of the specification. Together with the embodiments of the present invention, they are used to explain the present invention and do not constitute a limitation of the present invention. In the accompanying drawings:

[0073] Figure 1 A flowchart of a rural human resources intelligent management method in an embodiment of the present invention;

[0074] Figure 2 It is a schematic diagram of a rural human resources intelligent management system in an embodiment of the present invention. DETAILED DESCRIPTION

[0075] The preferred embodiments of the present invention are described below in conjunction with the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention.

[0076] The embodiment of the present invention provides a rural human resources intelligent management method, such as Figure 1 As shown, including:

[0077] S1. Monitor the target events to be managed based on the human resource database of the target villages;

[0078] In S1, the target villages are villages that need human resource management; the human resource database stores a large amount of human resource information of the target villages, such as: the name, gender, age, home address, contact information, labor skills, work experience, health status, work status, educational background, mobility, etc. of different laborers; the target events to be managed refer to events that require human resource management in the target villages, such as: the job positions of the laborers do not match their educational background, labor loss, insufficient labor skill training, etc. The human resource database reflects the real-time human resource situation of the target villages, so the target events can be monitored based on it;

[0079] S2, based on the knowledge base of rural human resource management, the first event management strategy for decision-making target events;

[0080] In S2, the knowledge base stores a large number of first event management strategies corresponding to different target events. The knowledge base can be constructed in advance based on the human resource management experience generated by experts in history. Therefore, the first event management strategy of the target event can be decided based on the knowledge base. The first event management strategy indicates how to perform human resource management on the target event, such as searching for vacant positions for the labor force with the goal of matching their educational background, and making job transfer arrangements when the search is completed;

[0081] S3. Based on the first event management strategy, manage the target event accordingly.

[0082] In S3, after deciding the first event management strategy, the target event is managed accordingly directly based on the first event management strategy.

[0083] This application is based on the human resources database of the target rural area, automatically monitors the target events to be managed, automatically decides the first event management strategy for the target events based on the knowledge base of rural human resources management, and finally manages the target events accordingly based on the first event management strategy. There is no need for management personnel to manually manage rural human resources, which reduces labor costs and improves management efficiency.

[0084] In one embodiment, after the step S3, managing the target event accordingly based on the first event management strategy, further includes:

[0085] S4. Evaluate the management effect of the target event and obtain an evaluation value;

[0086] In S4, after managing the target event, the system can track the management effect of the target event, such as whether vacant positions that match the educational background of the labor force are searched, and whether the labor force and the leaders of the current job positions of the labor force accept the job transfer, etc. The management effect reflects the implementation effect of the first event management strategy, which can be evaluated. The obtained evaluation value represents the degree of effectiveness of the implementation effect of the first event management strategy. When evaluating, the evaluation system constructed in advance can be called up. There are scores corresponding to different management effects in the evaluation system. The sum of the scores corresponding to the management effect of the target event in the evaluation system is used as the evaluation value.

[0087] S5. When the evaluation value does not exceed the evaluation value threshold, assist the user in deciding the second event management strategy of the target event online;

[0088] In S5, the threshold of the evaluation value is an evaluation value representing a low degree of effectiveness of the implementation effect of the first event management strategy, such as 8. When the evaluation value does not exceed the threshold of the evaluation value, it means that the implementation effect of the first event management strategy is poor. At this time, it is a special case where the system performs human resource management autonomously but the management effect is poor. The user, i.e., the manager, needs to intervene. In order to ensure the intervention efficiency of the manager, the second event management strategy for the target event is assisted online in making decisions.

[0089] S6. Based on the second event management strategy, take over the corresponding management of the target event.

[0090] In S6, after deciding on the second event management strategy, the target event is managed accordingly based on its succession. Succession means stopping the use of the first event management strategy and replacing it with the second event management strategy.

[0091] When the system autonomously performs human resource management but the management effect is not good, the embodiment of the present invention assists the user online in deciding the second event management strategy for the target event, and based on the second event management strategy, takes over the corresponding management of the target event, thereby ensuring the management effect of the target event and greatly improving the applicability of the system.

[0092] In one embodiment, in S5, the second event management strategy for online assisting the user in deciding the target event includes:

[0093] S51, displaying the target event to the user;

[0094] In S51, when displaying the target event to the user, detailed information of the target event may be displayed to the user, and the management effect of the target event and problems encountered when managing the target event based on the first event management strategy may also be displayed to the user;

[0095] S52, continuously tracking the viewing history of the user viewing the displayed target event;

[0096] In S52, when the user views, the viewing history generated by the user is tracked, such as: the content viewed and the viewing duration, the management operations performed during the viewing, etc.;

[0097] S53, based on the viewing history, generating a decision rhythm control timeline in real time;

[0098] In S53, the decision rhythm control timeline indicates how to control the rhythm of the user's management decision for the target event within a certain period of time in the future; the viewing history reflects how the user wants to make decisions, what aspects of the decision to make, etc., so the decision rhythm control timeline can be generated in real time based on the viewing history;

[0099] S54, based on the decision-making rhythm control time axis, the rhythm of the user's management decision of the target event is controlled accordingly;

[0100] In S54, after the decision rhythm control time axis is generated, the rhythm of the user's management decision of the target event is controlled accordingly based on the time axis to achieve assistance;

[0101] S55, receiving a second event management strategy input by the user after the user makes a management decision;

[0102] In S55, when the user completes the management decision, the user will input the decided second event management strategy;

[0103] Wherein, the step S53, based on the viewing history, generating a decision rhythm control timeline in real time, includes:

[0104] S531, obtaining multiple initial decision rhythm items of the event type of the target event;

[0105] In S531, the event type of the target event is preset to correspond to multiple initial decision rhythm items, and the initial decision rhythm items are decision rhythms that need to be entered when human resource management is performed on the target event of the event type. For example, if the event type of the target event is labor loss, the corresponding multiple initial decision rhythm items are respectively analyzing the common characteristics of the lost labor force, analyzing whether the treatment of the original job position of the lost labor force is qualified, and analyzing whether there is a historical loss record of the lost labor force, etc.;

[0106] S532, based on the viewing history, selecting a plurality of target decision rhythm items from each initial decision rhythm item, and determining the rhythm sequence of each target decision rhythm item and the rhythm holding time of each target decision rhythm item;

[0107] In S532, the review history fully reflects how the current user wants to make decisions, what aspects of the decision to make, etc. Therefore, based on it, multiple target decision rhythm items can be screened out from each initial decision rhythm item, and the corresponding rhythm sequence and rhythm retention time can be determined; the target decision rhythm item is the decision rhythm that the user needs to enter in sequence when currently performing human resource management on the target event, the rhythm sequence is the order in which the user currently needs to enter each target decision rhythm item in sequence, and the rhythm retention time is the time that the user needs to maintain when entering the target decision rhythm item;

[0108] S533, setting constraints on the rhythm items, and sequentially setting each target decision rhythm item on the initial time axis;

[0109] In S533, the initial time axis is a time axis without any content set; based on the rhythm item setting constraints, each target decision rhythm item is quickly set on the initial time axis in sequence;

[0110] S534, using the initial time axis after each target decision rhythm item is set in sequence as the decision rhythm control time axis;

[0111] In S534, after the setting is completed, the current initial time axis is used as the decision rhythm control time axis; in this way, when the decision rhythm control time axis is used, the progress pointer moves from the starting point of the initial time axis at the actual time lapse speed, and whenever the progress pointer touches the set target decision rhythm, the user is prompted to enter the corresponding target decision rhythm, thereby realizing the control of the user's management rhythm;

[0112] The rhythm item setting constraints include:

[0113] Constraint 1: Set each target decision rhythm item in sequence from the starting point of the initial time axis based on the rhythm sequence;

[0114] as well as,

[0115] Constraint 2: The on-axis distance between adjacent target decision rhythm items on the initial time axis is the rhythm maintenance duration of the former of the corresponding adjacent target decision rhythm items.

[0116] In constraint one and constraint two, when setting them in sequence, start from the starting point of the initial time axis; the on-axis spacing is the interval distance between the two target decision rhythm items on the initial time axis, and the unit is time unit; the on-axis spacing between adjacent target decision rhythm items is the rhythm holding time of the former of the adjacent target decision rhythm items, so that when the progress pointer touches the target decision rhythm, it can not give new prompts to the user within the corresponding rhythm holding time, thereby further realizing the control of the user's management rhythm.

[0117] It should be noted that the target events that require the intervention of managers for human resource management are usually highly complex. When managers manage them, if they cannot accurately control the rhythm of management decisions, it may lead to inaccurate and untimely management decisions, or even wrong decisions and serious delays in the optimal processing time of the target events. The embodiment of the present invention can solve this problem: generate a decision rhythm control timeline, and based on the decision rhythm control timeline, control the rhythm of the user's management decision for the target event accordingly, assist managers to accurately control the rhythm of management decisions, and greatly improve the accuracy and timeliness of management decisions.

[0118] In addition, traditional management decision assistance mostly directly gives users a decision-making idea and allows users to follow the decision-making idea. However, this has poor flexibility. When managers manage target events, their ideas change with the decision progress, the content of the decision, and the actual situation of the event. A fixed decision-making idea cannot provide continuous assistance to them, and can only be roughly borrowed or referenced, which seriously reduces the assistance effect and efficiency. The embodiment of the present invention can also solve this problem: the decision rhythm control timeline is generated in real time based on the viewing history of the target event that is continuously tracked by the user viewing the display. The decision rhythm control timeline is set with multiple target decision rhythm items selected from multiple initial decision rhythm items of the event type of the target event, so that the assistance content is staged and updated in real time. Secondly, the rhythm sequence of each target decision rhythm item and the rhythm retention time of each target decision rhythm item are determined to be compatible with the viewing history, so that the assistance method is also staged and updated in real time, and can provide continuous assistance to managers. Managers can continue to make management decisions according to the assistance of the decision rhythm control timeline, which greatly improves the assistance effect and efficiency.

[0119] In one embodiment, the S532, based on the viewing history, screens out a plurality of target decision rhythm items from each initial decision rhythm item, and determines the rhythm sequence of each target decision rhythm item and the rhythm holding time of each target decision rhythm item, including:

[0120] S5321, determining the degree of association between each initial decision rhythm item and the viewing history; wherein the degree of association is the sum of the mapping values ​​of at least one mapping node mapped by the viewing history in the association mapping tree of the initial decision rhythm item;

[0121] In S5321, the initial decision rhythm item presets the corresponding associated mapping tree, in which the management mapping tree includes a root node, a branch path connected to the root node, a branch node on the branch path, and a leaf node at the end of the branch path. The root node sets a specific viewing history, the branch node sets a specific initial decision rhythm item, and the leaf node sets the mapping value of the branch node on the same branch path. The mapping value represents the viewing history on the root node, which can reflect the degree to which the user wants to enter the initial decision rhythm item on the branch node. For example, if the viewing history is to view the historical salary of the lost labor force, and the initial decision rhythm item is to analyze the original job benefits of the lost labor force, it means that the viewing history obviously reflects that the user wants to enter the initial decision rhythm item, and the corresponding mapping value is a larger value such as 5. When determining the degree of association, the root node is searched based on the viewing history to find the tree where the corresponding root node is located, and then the branch node on the tree is searched based on the initial decision rhythm item to find the corresponding branch node, which is the mapping node. Then, the mapping value on the leaf node corresponding to the branch node is found. Finally, the mapping values ​​found are accumulated to obtain the degree of association. The specific accumulation calculation formula can be: Where D is the correlation, Y i is the i-th mapping value, and n is the total number of mapping values; thus, the relevance represents the degree to which the user who views the overall historical reflection wants to enter the initial decision rhythm item;

[0122] S5322, taking the initial decision rhythm item whose relevance exceeds the first threshold of the relevance as the first candidate item, and taking the remaining initial decision rhythm items as the second candidate items;

[0123] In S5322, the first threshold of the correlation degree is a threshold representing a relatively large correlation degree, such as 15; according to the magnitude relationship between the correlation degree and the first threshold of the correlation degree, the initial decision rhythm item is divided into a first candidate item and a second candidate item;

[0124] S5323, taking the first candidate item and the second candidate item having a rhythm association relationship with the first candidate item as a plurality of target decision rhythm items;

[0125] In S5323, if the relevance of the first candidate item exceeds the first threshold of the relevance, it means that the user wants to enter the corresponding initial decision rhythm item to a greater extent, and it is directly used as the target decision rhythm item; if the relevance of the second candidate item does not exceed the first threshold of the relevance, it means that the user wants to enter the corresponding initial decision rhythm item to a lesser extent, but if it has a rhythm association relationship with the first candidate item, it also needs the user to enter, and it is also used as the target decision rhythm item; the rhythm association relationship refers to the relationship between the initial decision rhythm items that the user needs to enter at the same stage, such as: the decision result of entering one initial decision rhythm item is the decision basis after entering another initial decision rhythm item, and the decision objects of the two initial decision rhythm items are the same, etc.;

[0126] S5324. When there is a target decision rhythm item whose correlation exceeds the second threshold of the correlation and the user's decision history is empty, based on the target decision rhythm item whose correlation exceeds the second threshold of the correlation, query the rhythm layout rule library to obtain a first rhythm layout rule, and based on the first rhythm layout rule, determine the rhythm sequence of each target decision rhythm item and the rhythm retention time of each target decision rhythm item; otherwise, based on the target decision rhythm item whose correlation exceeds the third threshold of the correlation and the user's decision history, query the rhythm layout rule library to obtain a second rhythm layout rule, and based on the second rhythm layout rule, determine the rhythm sequence of each target decision rhythm item and the rhythm retention time of each target decision rhythm item;

[0127] In S5324, the second threshold of the correlation is a threshold representing a particularly large correlation, such as: 40; the user's decision history is the management strategy to be implemented for the target event that has been decided when the user enters other target decision rhythm items in the history; when there is a target decision rhythm item with a correlation exceeding the second threshold of the correlation or the user's decision history is empty, it means that in order to make the rhythm layout reasonable, at this time, only the target decision rhythm item with a correlation exceeding the third threshold of the correlation can be used as the focus for rhythm layout, and the first rhythm layout rule is determined based on its library search; otherwise, in order to make the rhythm layout reasonable, a more comprehensive rhythm layout is performed with the target decision rhythm item with a correlation exceeding the third threshold of the correlation and the user's decision history as the focus, and the second rhythm layout rule is determined based on its library search; the third threshold of the correlation is a threshold representing a huge correlation, such as: 30; rhythm layout rules corresponding to the content based on different queries are pre-set in the rhythm layout rule library, and the rhythm layout rules indicate how to plan the rhythm sequence of each target decision rhythm item and The rhythm holding time of each target decision rhythm item is, for example, when there is a target decision rhythm item with a correlation exceeding the second threshold of the correlation and the user's decision history is empty, and the target decision rhythm item with a correlation exceeding the second threshold of the correlation is to analyze the original job benefits of the lost labor force, and the remaining target decision rhythm items are to analyze the current job benefits of the lost labor force, and the user needs to focus on analyzing the original job benefits of the lost labor force, then it is arranged in front, and the target decision rhythm item of analyzing the current job benefits of the lost labor force is arranged in the back, and the rhythm sequence is formed one after the other. Secondly, the user needs to focus on analyzing the original job benefits of the lost labor force, then a longer rhythm holding time is set, such as 5 minutes, and a shorter rhythm holding time is set for the target decision rhythm item of analyzing the current job benefits of the lost labor force, such as 3 minutes, to complete the setting of the corresponding first rhythm layout rule; the specific rhythm holding time can be statistically reasonably determined based on the time required for the user's actual analysis, the average analysis usage time, etc.Specifically, for example, the target decision rhythm item whose correlation exceeds the third threshold of correlation is to analyze the original job benefits of lost labor and analyze the common characteristics of lost labor. The user's decision history is to summarize the complaints made by lost labor against their original jobs due to dissatisfaction with the benefits. After summarizing the complaints made by lost labor against their original jobs due to dissatisfaction with the benefits, it is necessary to analyze whether the complaints are true. Then, the target decision rhythm item of analyzing the original job benefits of lost labor needs to be performed first and arranged in the front. Then, the common characteristics of lost labor can be analyzed and arranged in the back. The rhythm sequence is formed one after the other. Secondly, the user needs to focus on analyzing the original job benefits of lost labor. Then, a longer rhythm retention time is set, such as 3 minutes. The target decision rhythm item of analyzing the common characteristics of lost labor is set to a shorter rhythm retention time, such as 1 minute. Then, the setting of the corresponding second rhythm layout rule is completed.

[0128] The second threshold of the degree of association is greater than the third threshold of the degree of association, which is greater than the first threshold of the degree of association.

[0129] The second threshold of the correlation is set to the maximum, which can accurately determine the situation where the rhythm layout can only be carried out with the target decision rhythm item whose correlation exceeds the second threshold of the correlation as the focus, so as to carry out a reasonable rhythm layout in this situation; the third threshold of the correlation is set to the second largest, so that when the rhythm layout is carried out with the target decision rhythm item whose correlation exceeds the third threshold of the correlation and the user's decision history as the focus, it can be more comprehensive; the first threshold of the correlation is set to the minimum, which improves the rationality of the division of the first candidate item and the second candidate item, so that there can be a focus to rely on when the rhythm layout is carried out later.

[0130] The embodiment of the present invention introduces an association mapping tree of the initial decision rhythm items when screening out multiple target decision rhythm items based on the viewing history and determining the rhythm sequence and the rhythm retention time. The association mapping tree of the initial decision rhythm items is used to quickly determine the correlation between each initial decision rhythm item and the viewing history, thereby improving the efficiency and accuracy of determining the degree to which the viewing history reflects the user's overall desire to enter the initial decision rhythm items; secondly, the initial decision rhythm items are first divided according to a first threshold of the correlation, and then based on a second threshold of the correlation, it is determined whether to perform rhythm layout with the target decision rhythm item whose correlation exceeds the second threshold of the correlation as the center. If so, the first rhythm layout rule is determined and executed. Otherwise, the rhythm layout is performed with the target decision rhythm item whose correlation exceeds the third threshold of the correlation and the user's decision history as the center, and the second rhythm layout rule is determined and executed. The optimal rhythm layout method is accurately determined by setting the threshold, etc., which greatly improves the accuracy of the target decision rhythm item screening and the determination of the rhythm sequence and the rhythm retention time, and further improves the applicability of the system.

[0131] In one embodiment, after taking over the corresponding management of the target event based on the second event management strategy, S6 further includes:

[0132] S7, performing knowledge representation on the target event and the second event management strategy to obtain knowledge;

[0133] S8. Set the knowledge into the knowledge base.

[0134] The second event management strategy can be used as the basis for the system to make management decisions autonomously in the future. In this case, knowledge representation of the target event and the second event management strategy is performed, and the acquired knowledge is set into the knowledge base. When representing knowledge, it can be represented according to a pre-set knowledge format.

[0135] The embodiment of the present invention performs knowledge representation of the target event and the second event management strategy, and sets the acquired knowledge into the knowledge base, thereby enriching the knowledge base and improving the ability of the system to autonomously make management decisions in the future.

[0136] The embodiment of the present invention provides a rural human resources intelligent management system, such as Figure 2 As shown, including:

[0137] Monitoring module 1, used to monitor the target events to be managed based on the human resource database of the target villages;

[0138] Decision-making module 2, used for deciding the first event management strategy of the target event based on the knowledge base of rural human resource management;

[0139] The first management module 3 is used to manage the target event accordingly based on the first event management strategy.

[0140] After the first management module 3 manages the target event accordingly based on the first event management strategy, it also includes a second management module for:

[0141] Evaluate the management effect of the target event and obtain the evaluation value;

[0142] When the evaluation value does not exceed the evaluation value threshold, a second event management strategy for online assisting the user in deciding the target event;

[0143] Based on the second event management strategy, the target event is managed accordingly.

[0144] The second management module online assists the user in deciding the second event management strategy for the target event, including:

[0145] Display the target event to the user;

[0146] Continuously track the user's viewing history of the displayed target event;

[0147] Generate decision-making rhythm control timeline in real time based on viewing history;

[0148] Based on the decision-making rhythm, the timeline is controlled to control the rhythm of the user's management decision-making for the target event accordingly;

[0149] receiving a second event management strategy input by the user after completing the management decision;

[0150] The step of generating a decision-making rhythm control timeline in real time based on the viewing history includes:

[0151] obtaining multiple initial decision rhythm items of the event type of the target event;

[0152] Based on the viewing history, multiple target decision rhythm items are selected from each initial decision rhythm item, and the rhythm sequence of each target decision rhythm item and the rhythm holding time of each target decision rhythm item are determined;

[0153] Based on the constraints set by the rhythm items, each target decision rhythm item is sequentially set on the initial time axis;

[0154] The initial time axis after each target decision rhythm item is set in sequence is used as the decision rhythm control time axis;

[0155] The rhythm item setting constraints include:

[0156] Constraint 1: Set each target decision rhythm item in sequence from the starting point of the initial time axis based on the rhythm sequence;

[0157] as well as,

[0158] Constraint 2: The on-axis distance between adjacent target decision rhythm items on the initial time axis is the rhythm maintenance duration of the former of the corresponding adjacent target decision rhythm items.

[0159] The second management module selects a plurality of target decision rhythm items from each initial decision rhythm item based on the viewing history, and determines the rhythm sequence of each target decision rhythm item and the rhythm holding time of each target decision rhythm item, including:

[0160] Determine the degree of association between each initial decision rhythm item and the viewing history; wherein the degree of association is the sum of the mapping values ​​of at least one mapping node mapped by the viewing history in the association mapping tree of the initial decision rhythm item;

[0161] taking the initial decision rhythm items whose relevance exceeds the first threshold of the relevance as the first candidate items, and taking the remaining initial decision rhythm items as the second candidate items;

[0162] The first candidate item and the second candidate item having a rhythm association relationship with the first candidate item are used as a plurality of target decision rhythm items;

[0163] When there is a target decision rhythm item whose correlation exceeds the second threshold of the correlation and the user's decision history is empty, based on the target decision rhythm item whose correlation exceeds the second threshold of the correlation, query the rhythm layout rule library to obtain the first rhythm layout rule, and based on the first rhythm layout rule, determine the rhythm sequence of each target decision rhythm item and the rhythm retention time of each target decision rhythm item; otherwise, based on the target decision rhythm item whose correlation exceeds the third threshold of the correlation and the user's decision history, query the rhythm layout rule library to obtain the second rhythm layout rule, and based on the second rhythm layout rule, determine the rhythm sequence of each target decision rhythm item and the rhythm retention time of each target decision rhythm item;

[0164] The second threshold of the degree of association is greater than the third threshold of the degree of association, which is greater than the first threshold of the degree of association.

[0165] After the second management module takes over the corresponding management of the target event based on the second event management strategy, it also includes a setting module for:

[0166] Perform knowledge representation on target events and second event management strategies to obtain knowledge;

[0167] Set the knowledge into the knowledge base.

[0168] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A rural human resources intelligent management method, characterized in that: include: Based on the human resource pool of target villages, monitor the target events to be managed; Based on the knowledge base of rural human resource management, the first event management strategy for decision-making target events; Based on the first event management strategy, the target event is managed accordingly.

2. The rural human resources intelligent management method according to claim 1, characterized in that: After the target event is managed accordingly based on the first event management strategy, the method further includes: Evaluate the management effect of the target event and obtain the evaluation value; When the evaluation value does not exceed the evaluation value threshold, a second event management strategy for online assisting the user in deciding the target event; Based on the second event management strategy, the target event is managed accordingly.

3. The rural human resources intelligent management method according to claim 2, characterized in that: The second event management strategy for online assisting users in making decisions about target events includes: Display the target event to the user; Continuously track the user's viewing history of the displayed target event; Generate decision-making rhythm control timeline in real time based on viewing history; Based on the decision-making rhythm, the timeline is controlled to control the rhythm of the user's management decision-making for the target event accordingly; receiving a second event management strategy input by the user after completing the management decision; The step of generating a decision-making rhythm control timeline in real time based on the viewing history includes: obtaining multiple initial decision rhythm items of the event type of the target event; Based on the viewing history, multiple target decision rhythm items are selected from each initial decision rhythm item, and the rhythm sequence of each target decision rhythm item and the rhythm holding time of each target decision rhythm item are determined; Based on the constraints set by the rhythm items, each target decision rhythm item is sequentially set on the initial time axis; The initial time axis after each target decision rhythm item is set in sequence is used as the decision rhythm control time axis; The rhythm item setting constraints include: Constraint 1: Set each target decision rhythm item in sequence from the starting point of the initial time axis based on the rhythm sequence; as well as, Constraint 2: The on-axis distance between adjacent target decision rhythm items on the initial time axis is the rhythm maintenance duration of the former of the corresponding adjacent target decision rhythm items.

4. The rural human resources intelligent management method according to claim 3, characterized in that: The method of selecting a plurality of target decision rhythm items from each initial decision rhythm item based on the viewing history, and determining the rhythm sequence of each target decision rhythm item and the rhythm holding time of each target decision rhythm item includes: Determine the degree of association between each initial decision rhythm item and the viewing history; wherein the degree of association is the sum of the mapping values ​​of at least one mapping node mapped by the viewing history in the association mapping tree of the initial decision rhythm item; taking the initial decision rhythm items whose relevance exceeds the first threshold of the relevance as the first candidate items, and taking the remaining initial decision rhythm items as the second candidate items; The first candidate item and the second candidate item having a rhythm association relationship with the first candidate item are used as a plurality of target decision rhythm items; When there is a target decision rhythm item whose correlation exceeds the second threshold of the correlation and the user's decision history is empty, based on the target decision rhythm item whose correlation exceeds the second threshold of the correlation, query the rhythm layout rule library to obtain the first rhythm layout rule, and based on the first rhythm layout rule, determine the rhythm sequence of each target decision rhythm item and the rhythm retention time of each target decision rhythm item; otherwise, based on the target decision rhythm item whose correlation exceeds the third threshold of the correlation and the user's decision history, query the rhythm layout rule library to obtain the second rhythm layout rule, and based on the second rhythm layout rule, determine the rhythm sequence of each target decision rhythm item and the rhythm retention time of each target decision rhythm item; The second threshold of the degree of association is greater than the third threshold of the degree of association, which is greater than the first threshold of the degree of association.

5. The rural human resources intelligent management method according to claim 2, characterized in that: After taking over the corresponding management of the target event based on the second event management strategy, the method further includes: Perform knowledge representation on target events and second event management strategies to obtain knowledge; Set the knowledge into the knowledge base.

6. A rural human resources intelligent management system, characterized in that: include: A monitoring module is used to monitor target events to be managed based on the human resource database of the target villages; A decision-making module, used to decide the first event management strategy of the target event based on the knowledge base of rural human resource management; The first management module is used to manage the target event accordingly based on the first event management strategy.

7. The rural human resources intelligent management system according to claim 6, characterized in that: After the first management module manages the target event accordingly based on the first event management strategy, the second management module is further included, which is used to: Evaluate the management effect of the target event and obtain the evaluation value; When the evaluation value does not exceed the evaluation value threshold, a second event management strategy for online assisting the user in deciding the target event; Based on the second event management strategy, the target event is managed accordingly.

8. The rural human resources intelligent management system according to claim 7, characterized in that: The second management module online assists the user in deciding the second event management strategy for the target event, including: Display the target event to the user; Continuously track the user's viewing history of the displayed target event; Generate decision-making rhythm control timeline in real time based on viewing history; Based on the decision-making rhythm, the timeline is controlled to control the rhythm of the user's management decision-making for the target event accordingly; receiving a second event management strategy input by the user after completing the management decision; The step of generating a decision-making rhythm control timeline in real time based on the viewing history includes: obtaining multiple initial decision rhythm items of the event type of the target event; Based on the viewing history, multiple target decision rhythm items are selected from each initial decision rhythm item, and the rhythm sequence of each target decision rhythm item and the rhythm holding time of each target decision rhythm item are determined; Based on the constraints set by the rhythm items, each target decision rhythm item is sequentially set on the initial time axis; The initial time axis after each target decision rhythm item is set in sequence is used as the decision rhythm control time axis; The rhythm item setting constraints include: Constraint 1: Set each target decision rhythm item in sequence from the starting point of the initial time axis based on the rhythm sequence; as well as, Constraint 2: The on-axis distance between adjacent target decision rhythm items on the initial time axis is the rhythm maintenance duration of the former of the corresponding adjacent target decision rhythm items.

9. The rural human resources intelligent management system according to claim 8, characterized in that: The second management module selects a plurality of target decision rhythm items from each initial decision rhythm item based on the viewing history, and determines the rhythm sequence of each target decision rhythm item and the rhythm holding time of each target decision rhythm item, including: Determine the degree of association between each initial decision rhythm item and the viewing history; wherein the degree of association is the sum of the mapping values ​​of at least one mapping node mapped by the viewing history in the association mapping tree of the initial decision rhythm item; taking the initial decision rhythm items whose relevance exceeds the first threshold of the relevance as the first candidate items, and taking the remaining initial decision rhythm items as the second candidate items; The first candidate item and the second candidate item having a rhythm association relationship with the first candidate item are used as a plurality of target decision rhythm items; When there is a target decision rhythm item whose correlation exceeds the second threshold of the correlation and the user's decision history is empty, based on the target decision rhythm item whose correlation exceeds the second threshold of the correlation, query the rhythm layout rule library to obtain the first rhythm layout rule, and based on the first rhythm layout rule, determine the rhythm sequence of each target decision rhythm item and the rhythm retention time of each target decision rhythm item; otherwise, based on the target decision rhythm item whose correlation exceeds the third threshold of the correlation and the user's decision history, query the rhythm layout rule library to obtain the second rhythm layout rule, and based on the second rhythm layout rule, determine the rhythm sequence of each target decision rhythm item and the rhythm retention time of each target decision rhythm item; The second threshold of the degree of association is greater than the third threshold of the degree of association, which is greater than the first threshold of the degree of association.

10. The rural human resources intelligent management system according to claim 7, characterized in that: After the second management module takes over the corresponding management of the target event based on the second event management strategy, it also includes a setting module for: Perform knowledge representation on target events and second event management strategies to obtain knowledge; Set the knowledge into the knowledge base.

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