Human resource management digital intelligent management system based on big data and application

Abstract

The invention relates to the technical field of human resource management, in particular to a human resource management digital intelligent management system and application based on big data, and the system comprises an information collection module, a classification module, a data analysis module, a data storage module, a job application data comparison module and a position information push module. The classification module is used for classifying human resource information of the same school calendar and the same job seeking intention post, and the data analysis module is used for performing unified batch analysis on classified personal information and intention post information of job seekers. The problem that the information analysis module needs to analyze different job seekers one by one due to the fact that the obtained job seeking data is directly issued to the information analysis module and is not classified in advance, so that the analysis time is increased, and the job recommendation efficiency is influenced is solved.

Description

Technical Field

[0001] The present invention relates to the technical field of human resource management, and in particular to a digital intelligent management system and application of human resource management based on big data. Background Art

[0002] Human resource management is a management model that effectively utilizes relevant human resources inside and outside the organization through recruitment, selection, training, compensation and other management forms under the guidance of economics and humanistic thinking. Due to factors such as personal basic information and intended job information, job seekers may not get the desired positions, so it is necessary to uniformly manage human resource information based on big data.

[0003] The prior art has a human resource management system based on big data, including an information collection module, which is used to collect the job seeker's basic personal information, school education information, and intended job information; the information analysis module is used to analyze the job seeker's basic personal information and intended job information; the information comparison module is used to compare the basic personal information, intended job information and the information of existing employees; the position matching module is used to match the job according to the intended job and the basic personal information of the job seeker; it is convenient to display the searched positions to the job seeker, and can quickly match the corresponding positions according to the job seeker's personal information and intended job, so that the recruitment companies recommended to the job seeker are more accurate.

[0004] However, in the above method, since the obtained job search data is directly sent to the information analysis module without being classified in advance, the information analysis module needs to analyze different job seekers one by one, which increases the analysis time and affects the efficiency of job recommendation. Summary of the invention

[0005] The purpose of the present invention is to provide a digital intelligent management system and application for human resource management based on big data, aiming to solve the problem that the existing digital intelligent management system for human resource management based on big data, because the acquired job search data is directly sent to the information analysis module without prior classification, the information analysis module needs to analyze different job seekers one by one, resulting in increased analysis time and affecting the efficiency of job recommendation.

[0006] To achieve the above-mentioned purpose, in a first aspect, the present invention provides a digital intelligent management system for human resource management based on big data, including an information collection module, a classification module, a data analysis module, a data storage module, a job search data comparison module and a job information push module;

[0007] The classification module is connected to the information collection module; the data analysis module is connected to the classification module; the data storage module is connected to the data analysis module; the job search data comparison module is connected to the data storage module; the job information push module is connected to the job search data comparison module;

[0008] The information collection module is used to collect the job seeker's basic personal information, school education information, intended position information and job position information based on multiple platforms to obtain corresponding human resources data;

[0009] The classification module is used to classify the corresponding human resource data obtained, and classify the human resource information of the same school degree and the same job-seeking intended position, so as to facilitate subsequent job recommendation;

[0010] The data analysis module is used to perform unified batch analysis on the classified personal information and intended job information of job seekers;

[0011] The data storage module is used to store the personal information and intended job information analyzed by the data analysis module, so as to facilitate quick call when encountering the same job search information data in the future, thus reducing the analysis time;

[0012] The job search data comparison module is used to call the analyzed personal information and intended position information in the data storage module for comparison with the existing staff information;

[0013] The job information push module is used to match the matched job search information data and then send suitable job information to the job seeker.

[0014] The classification module includes a data acquisition submodule, a job search information identification submodule and a job search data classification submodule. The data acquisition submodule is connected to the information collection module; the job search information identification submodule is connected to the data acquisition submodule; the job search data classification submodule is connected to the job search information identification submodule;

[0015] The data acquisition submodule is used to acquire the job seeker's personal information, school education information and intended position information collected by the information collection module;

[0016] The job search information identification submodule is used to identify various information data of job seekers to determine whether there is any false or erroneous information;

[0017] The job search data classification submodule is used to classify and store the various information data of the real and correct job seekers according to the same school education information and the same intended position information.

[0018] Wherein, the data storage module includes a data receiving submodule and a tree storage submodule, the data receiving submodule is connected to the data analysis module; the tree storage submodule is connected to the data receiving submodule;

[0019] The data receiving submodule is used to obtain various information data of job seekers analyzed by the data analyzing module;

[0020] The tree-type storage submodule is used to store various information data of job seekers in a tree-type data format, so as to facilitate the subsequent rapid call of the background.

[0021] Wherein, the job search data comparison module includes a data association submodule, an information difference calculation submodule and a data comparison submodule, wherein the data association submodule is connected to the data storage module; the information difference calculation submodule is connected to the data association submodule; the data comparison submodule is connected to the information difference calculation submodule;

[0022] The data association submodule is used to realize the merging and sharing of job seeker information and existing employee information, and to realize the connection, exchange and sharing between different databases;

[0023] The information difference calculation submodule is used to calculate the difference between different job seekers' information and existing employees' information;

[0024] The data comparison submodule is used to compare the calculated job seeker information with the existing employee information to determine whether the job seeker is suitable for the current position.

[0025] Wherein, the digital intelligent management system for human resource management based on big data further includes a data security access module, and the data security access module is connected to the position information push module;

[0026] The data security access module is used by the client to view the content of the job information push module in a ciphertext security access technology to increase data security.

[0027] Wherein, the data security access module includes a login submodule, an encryption submodule and a data transmission submodule, wherein the login submodule is connected to the job information push module; the encryption submodule is connected to the login submodule; the data transmission submodule is connected to the encryption submodule;

[0028] The login submodule is used to log in to the human resources data query client;

[0029] The encryption submodule is used to receive the encrypted information to form an encryption key;

[0030] The data transmission submodule is used to transmit signals to the data processor.

[0031] Wherein, the digital intelligent management system for human resource management based on big data further includes a job seeker information sending module; the job seeker information sending module is connected to the position information pushing module;

[0032] The job seeker information sending module is used to send the job seeker information suitable for the job information to the corresponding enterprise while pushing the suitable job information in the job information pushing module, so that the enterprise can check and achieve the effect of two-way selection.

[0033] In a second aspect, the present invention also provides an application of a digital intelligent management system for human resource management based on big data, and the digital intelligent management system for human resource management based on big data is applied to digital intelligent management of human resource management.

[0034] The present invention is a digital intelligent management system for human resource management based on big data. The information collection module selects data seeds and then analyzes them. Through the hyperlink information in the webpage, the information collection module continuously obtains the personal basic information, school education information, intended job information and job position information of job seekers from other webpages on the network to collect from multiple platforms. The classification module obtains the job search data and job position data of multiple platforms collected by the information collection module, and classifies the human resource information of the same school education and the same intended job position, so as to facilitate the subsequent job recommendation. Then, the data analysis module performs a unified batch analysis on the classified job seeker personal information and intended job position information, and then analyzes the data analysis module through the data storage module. The personal information and intended job information obtained are stored to facilitate quick call-up when the same job search information data is encountered later, reducing analysis time, and then the job search data comparison module calls the analyzed personal information and intended job information in the data storage module for comparison with the existing staff information, and finally the job search information data that has been compared is matched through the job information push module, and then the appropriate job information is sent to the job seeker, so as to solve the problem that the existing digital intelligent management system for human resource management based on big data, because the obtained job search data is directly sent to the information analysis module without being classified in advance, will cause the information analysis module to analyze different job seekers one by one, resulting in increased analysis time and affecting the efficiency of job recommendation. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art are briefly introduced below.

[0036] Figure 1 It is a schematic diagram of the overall structure of the first embodiment of a digital intelligent management system for human resource management based on big data of the present invention.

[0037] Figure 2 It is a structural diagram of the classification module of the first embodiment of a digital intelligent management system for human resource management based on big data of the present invention.

[0038] Figure 3 It is a structural diagram of a position information push module of a first embodiment of a digital intelligent management system for human resource management based on big data of the present invention.

[0039] Figure 4 It is a schematic diagram of the overall structure of the second embodiment of a digital intelligent management system for human resource management based on big data of the present invention.

[0040] Figure 5 It is a structural diagram of a data security access module of a second embodiment of a digital intelligent management system for human resource management based on big data of the present invention.

[0041] Figure 6 It is a schematic diagram of the overall structure of the third embodiment of a digital intelligent management system for human resource management based on big data of the present invention.

[0042] 101-information collection module, 102-position recommendation submodule, 103-classification module, 104-data analysis module, 105-data storage module, 106-job search data comparison module, 107-position information push module, 108-data acquisition submodule, 109-job search information identification submodule, 110-job search data classification submodule, 111-data receiving submodule, 112-tree storage submodule, 113-data association submodule, 114-information difference calculation submodule, 115-data comparison submodule, 116-comparison information collection submodule, 117-position information matching submodule, 201-data security access module, 202-login submodule, 203-encryption submodule, 204-data transmission submodule, 301-job seeker information sending module. DETAILED DESCRIPTION

[0043] In the first aspect, the present invention provides a digital intelligent management system for human resource management based on big data. The first embodiment of a digital intelligent management system for human resource management based on big data of the present application is:

[0044] See also Figure 1-Figure 3 ,in, Figure 1 It is a schematic diagram of the overall structure of the first embodiment of a digital intelligent management system for human resource management based on big data of the present invention. Figure 2 It is a structural diagram of a classification module of a first embodiment of a digital intelligent management system for human resource management based on big data of the present invention. Figure 3 It is a structural diagram of a position information push module of a first embodiment of a digital intelligent management system for human resource management based on big data of the present invention.

[0045] The present invention provides a digital intelligent management system for human resource management based on big data; it comprises an information collection module 101, a classification module 103, a data analysis module 104, a data storage module 105, a job search data comparison module 106 and a job information push module 107, wherein the classification module 103 comprises a data acquisition submodule 108, a job search information identification submodule 109 and a job search data classification submodule 110, the data storage module 105 comprises a data receiving submodule 111 and a tree storage submodule 112, the job search data comparison module 106 comprises a data association submodule 113, an information difference calculation submodule 114 and a data comparison submodule 115, the job information push module 107 comprises a comparison information collection submodule 116, a job information matching submodule 117 and a job recommendation submodule 102, and the above-mentioned scheme solves the problem that the existing digital intelligent management system for human resource management based on big data, because the acquired job search data is directly sent to the information analysis module without being classified in advance, the information analysis module needs to analyze different job seekers one by one, resulting in an increase in analysis time and affecting the efficiency of job recommendation.

[0046] According to this specific implementation, the classification module 103 is connected to the information collection module 101; the data analysis module 104 is connected to the classification module 103; the data storage module 105 is connected to the data analysis module 104; the job search data comparison module 106 is connected to the data storage module 105;The job information push module 107 is connected to the job search data comparison module 106. The information collection module 101 is used to collect the job seeker's basic personal information, school education information, intended job information and job position information based on multiple platforms to obtain corresponding human resource data. The classification module 103 is used to classify the corresponding human resource data obtained, and classify the human resource information of the same school education and the same intended job position to facilitate subsequent job recommendation. The data analysis module 104 is used to perform unified batch analysis on the classified job seekers' personal information and intended job position information. The data storage module 105 is used to The personal information and intended job information analyzed by the data analysis module are stored, so that they can be quickly called up when the same job search information data is encountered later, reducing the analysis time. The job search data comparison module 106 is used to call up the analyzed personal information and intended job information in the data storage module for comparison with the existing staff information. The job information push module 107 is used to match the compared job search information data and then send the appropriate job information to the job seeker. The information collection module 101 selects the data seed and then analyzes it. Through the hyperlink information in the web page, it continuously obtains the data of other web pages on the network and collects it to multiple platforms The classification module 103 obtains the job search data and job position data of multiple platforms collected by the information collection module 101, and classifies the human resource information of the same school education and the same job search intention position, so as to facilitate the subsequent job recommendation. Then, the data analysis module 104 performs a unified batch analysis on the classified job seekers' personal information and intended job position information, and then stores the personal information and intended job position information analyzed by the data analysis module 104 through the data storage module 105, so as to facilitate the subsequent rapid analysis when encountering the same job search information data. The job search data comparison module 106 calls the analyzed personal information and intended job information in the data storage module 105 to compare with the existing staff information, and finally matches the compared job search information data through the job information push module 107, and then sends the appropriate job information to the job seeker, solving the problem that the existing digital intelligent management system for human resource management based on big data, because the acquired job search data is directly sent to the information analysis module without being classified in advance, will cause the information analysis module to analyze different job seekers one by one, resulting in increased analysis time and affecting the efficiency of job recommendation. ;

[0047] The data acquisition submodule 108 is connected to the information collection module 101; the job search information identification submodule 109 is connected to the data acquisition submodule 108; the job search data classification submodule 110 is connected to the job search information identification submodule 109. The data acquisition submodule 108 is used to obtain the personal information, school education information and intended job information of the job seeker collected by the information collection module 101. The job search information identification submodule 109 is used to identify the various information data of the job seeker to determine whether there is false or erroneous information. The job search data classification submodule 110 is used to classify the identified true and correct job seekers into The various information data of the job seekers are classified and stored according to the same school education information and the same intended job information. The data acquisition submodule 108 is used to obtain the personal information, school education information and intended job information of the job seekers collected by the information collection module 101, and then the job search information identification submodule 109 is used to identify the various information data of the job seekers obtained to determine whether there is false or erroneous information. If the data information is correct, the job search data classification submodule 110 will classify and store the various information data of the job seekers that are identified to be true and correct according to the same school education information and the same intended job information for subsequent calls.

[0048] Secondly, the data receiving submodule 111 is connected to the data analysis module 104; the tree-type storage submodule 112 is connected to the data receiving submodule 111, the data receiving submodule 111 is used to obtain the various information data of the job seekers analyzed by the data analysis module, and the tree-type storage submodule 112 is used to store the various information data of the job seekers in a tree-type data structure, which is convenient for subsequent quick backend calls. The data receiving submodule 111 obtains the various information data of the job seekers analyzed by the data analysis module 104, and then uses the tree-type storage submodule 112 to store the various information data of the job seekers in a tree-type data structure, which is convenient for subsequent quick backend calls.

[0049] Again, the data association submodule 113 is connected to the data storage module 105; the information difference calculation submodule 114 is connected to the data association submodule 113; the data comparison submodule is connected to the information difference calculation submodule 114, the data association submodule 113 is used to realize the merging and sharing of job seeker information and existing employee information, and realize the connection, exchange and sharing between different databases, the information difference calculation submodule 114 is used to calculate the difference between different job seeker information and existing employee information, the data comparison submodule 115 is used to compare the calculated job seeker information with the existing employee information to determine whether it is suitable for the current position, the data association submodule 113 is used to realize the merging and sharing of job seeker information and existing employee information, and realize the connection, exchange and sharing between different databases, and then calculate the difference between different job seeker information and existing employee information through the information difference calculation submodule 114, after the calculation, the data comparison submodule 115 compares the calculated job seeker information with the existing employee information to determine whether the job seeker's personal information is suitable for the current position.

[0050] In addition, the job information push module 107 includes a comparison information collection submodule 116 and a job information matching submodule 117. The comparison information collection submodule 116 is connected to the job search data comparison module 106; the job information matching submodule 117 is connected to the comparison information collection submodule 116. The comparison information collection submodule 116 is used to collect the personal information of the matched job seekers, and the job information matching submodule 117 is used to match the matched job seekers' personal information and intended positions to screen out suitable job information. The comparison information collection submodule 116 is used to obtain the job seekers' personal information that has been matched in advance, and then the job information matching submodule 117 is used to match the job seekers' personal information and some intended positions to screen out some suitable positions.

[0051] Furthermore, the position recommendation submodule 102 is connected to the position information matching submodule 117. The position recommendation submodule 102 is used to display the searched positions to job seekers, and push suitable position information such as advancement opportunities, position salary and other information according to the job-seeking intentions of job seekers for reference by job seekers. The position recommendation submodule 102 is used to push some of the screened suitable positions and detailed data such as advancement opportunities, position salary and other data directly to the communication device of job seekers for selection based on supply and demand responsibilities.

[0052] When using the digital intelligent management system for human resource management based on big data described in the present invention, the information collection module 101 selects data seeds and then parses them. Through the hyperlink information in the web page, the data of other web pages on the network are continuously obtained to collect the basic personal information, school education information, intended job information and job position information of job seekers from multiple platforms. The classification module 103 obtains the job search data and job position data of multiple platforms collected by the information collection module 101, and classifies the human resource information of the same school education and the same intended job position, so as to facilitate the subsequent job recommendation. Then, the data analysis module 104 performs a unified batch analysis on the classified job seeker personal information and intended job position information, and then stores the data through the data storage module 105. The personal information and intended job information analyzed by the analysis module 104 are stored, so as to facilitate quick call when the same job search information data is encountered later, thereby reducing the analysis time. Then, the job search data comparison module 106 calls the analyzed personal information and intended job information in the data storage module 105 for comparison with the existing staff information. Finally, the compared job search information data is matched through the job information push module, and then the appropriate job information is sent to the job seeker, so as to solve the problem that the existing digital intelligent management system for human resource management based on big data, because the acquired job search data is directly sent to the information analysis module without being classified in advance, the information analysis module needs to analyze different job seekers one by one, which increases the analysis time and affects the efficiency of job recommendation.

[0053] A second embodiment of a digital intelligent management system for human resource management based on big data of the present application is:

[0054] See also Figure 4-Figure 5 ,in, Figure 4 It is a schematic diagram of the overall structure of the second embodiment of a digital intelligent management system for human resource management based on big data of the present invention. Figure 5 It is a structural diagram of a data security access module of a second embodiment of a digital intelligent management system for human resource management based on big data of the present invention.

[0055] Based on the first embodiment, the present invention provides a digital intelligent management system for human resource management based on big data, and the digital intelligent management system for human resource management based on big data also includes a data security access module 201, and the data security access module 201 includes a login sub-module 202, an encryption sub-module 203 and a data transmission sub-module 204.

[0056] Among them, the data security access module 201 is connected to the position information push module 107, and the data security access module 201 is used for the client to view the content of the position information push module 107 by means of ciphertext security access technology, thereby increasing data security. The data security access module 201 is used for the client to view the content of the position information push module 107 by means of ciphertext security access technology, thereby increasing data security.

[0057] Secondly, the login submodule 202 is connected to the position information push module 107; the encryption submodule 203 is connected to the login submodule 202; the data transfer submodule 204 is connected to the encryption submodule 203, the login submodule 202 is used to log in to the human resources data query client, the encryption submodule 203 is used to receive the encrypted information to form an encryption key, the data transfer submodule 204 is used to transmit signals to the data processor, the login submodule 202 is used to log in to the human resources data query client, the encrypted information is received through the encryption submodule 203 to form an encryption key, and then the signal is transmitted to the data processor through the data transfer submodule 204, thereby increasing the security of the human resources data.

[0058] In the digital intelligent management system for human resource management based on big data described in this embodiment, the login submodule 202 is used to log in to the human resource data query client, the encrypted information is received by the encryption submodule 203 to form an encryption key, and then the signal is transmitted to the data processor through the data transmission submodule 204, thereby increasing the security of the human resource data.

[0059] A third embodiment of a digital intelligent management system for human resource management based on big data of the present application is:

[0060] See also Figure 6 ,in, Figure 6 It is a schematic diagram of the overall structure of the third embodiment of a digital intelligent management system for human resource management based on big data of the present invention.

[0061] On the basis of the first embodiment, the present invention provides a digital intelligent management system for human resource management based on big data, and the digital intelligent management system for human resource management based on big data also includes a job seeker information sending module 301.

[0062] Among them, the job seeker information sending module 301 is connected to the position information pushing module 107. The job seeker information sending module 301 is used to send the job seeker information suitable for the position information to the corresponding enterprise while pushing the suitable position information to the position information pushing module 107, so as to facilitate the enterprise to view and achieve a two-way selection effect. The job seeker information sending module 301 is used to send the job seeker information suitable for the position information to the corresponding enterprise based on the Internet while pushing the suitable position information to the position information pushing module 107, so as to facilitate the enterprise to view and achieve a two-way selection effect.

[0063] In the digital intelligent management system for human resource management based on big data described in this embodiment, the job seeker information sending module 301 is used to push suitable job information in the job information pushing module 107, and at the same time, send the job seeker information suitable for the job information to the corresponding enterprise based on the Internet, so as to facilitate the enterprise to view and achieve a two-way selection effect.

[0064] In a second aspect, the present invention also provides an application of a digital intelligent management system for human resource management based on big data, and the digital intelligent management system for human resource management based on big data is applied to digital intelligent management of human resource management.

[0065] What is disclosed above is only one or more preferred embodiments of the present application, and cannot be used to limit the scope of rights of the present application. Ordinary technicians in this field can understand that all or part of the processes of implementing the above embodiments and equivalent changes made according to the claims of the present application are still within the scope covered by the present application.

Claims

1. A digital intelligent management system for human resource management based on big data, characterized in that: It includes information collection module, classification module, data analysis module, data storage module, job search data comparison module and job information push module; The classification module is connected to the information collection module; the data analysis module is connected to the classification module; the data storage module is connected to the data analysis module; the job search data comparison module is connected to the data storage module; the job information push module is connected to the job search data comparison module; The information collection module is used to collect the job seeker's basic personal information, school education information, intended position information and job position information based on multiple platforms to obtain corresponding human resources data; The classification module is used to classify the corresponding human resource data obtained, and classify the human resource information of the same school degree and the same job-seeking intended position, so as to facilitate subsequent job recommendation; The data analysis module is used to perform unified batch analysis on the classified personal information and intended job information of job seekers; The data storage module is used to store the personal information and intended job information analyzed by the data analysis module, so as to facilitate quick call when encountering the same job search information data in the future, thus reducing the analysis time; The job search data comparison module is used to call the analyzed personal information and intended position information in the data storage module for comparison with the existing staff information; The job information push module is used to match the matched job search information data and then send suitable job information to the job seeker.

2. A digital intelligent management system for human resource management based on big data as claimed in claim 1, characterized in that: The classification module includes a data acquisition submodule, a job search information identification submodule and a job search data classification submodule. The data acquisition submodule is connected to the information collection module; the job search information identification submodule is connected to the data acquisition submodule; the job search data classification submodule is connected to the job search information identification submodule; The data acquisition submodule is used to acquire the job seeker's personal information, school education information and intended position information collected by the information collection module; The job search information identification submodule is used to identify various information data of job seekers to determine whether there is any false or erroneous information; The job search data classification submodule is used to classify and store the various information data of the real and correct job seekers according to the same school education information and the same intended position information.

3. A digital intelligent management system for human resource management based on big data as claimed in claim 2, characterized in that: The data storage module includes a data receiving submodule and a tree storage submodule, wherein the data receiving submodule is connected to the data analysis module; the tree storage submodule is connected to the data receiving submodule; The data receiving submodule is used to obtain various information data of job seekers analyzed by the data analyzing module; The tree-type storage submodule is used to store various information data of job seekers in a tree-type data format, so as to facilitate the subsequent rapid call of the background.

4. A digital intelligent management system for human resource management based on big data as claimed in claim 3, characterized in that: The job search data comparison module includes a data association submodule, an information difference calculation submodule and a data comparison submodule, wherein the data association submodule is connected to the data storage module; the information difference calculation submodule is connected to the data association submodule; the data comparison submodule is connected to the information difference calculation submodule; The data association submodule is used to realize the merging and sharing of job seeker information and existing employee information, and to realize the connection, exchange and sharing between different databases; The information difference calculation submodule is used to calculate the difference between different job seekers' information and existing employees' information; The data comparison submodule is used to compare the calculated job seeker information with the existing employee information to determine whether the job seeker is suitable for the current position.

5. A digital intelligent management system for human resource management based on big data as claimed in claim 1, characterized in that: The digital intelligent management system for human resource management based on big data also includes a data security access module, which is connected to the position information push module; The data security access module is used by the client to view the content of the job information push module in a ciphertext security access technology to increase data security.

6. A digital intelligent management system for human resource management based on big data as claimed in claim 5, characterized in that: The data security access module includes a login submodule, an encryption submodule and a data transfer submodule, wherein the login submodule is connected to the job information push module; the encryption submodule is connected to the login submodule; and the data transfer submodule is connected to the encryption submodule; The login submodule is used to log in to the human resources data query client; The encryption submodule is used to receive the encrypted information to form an encryption key; The data transmission submodule is used to transmit signals to the data processor.

7. A digital intelligent management system for human resource management based on big data as claimed in claim 1, characterized in that: The digital intelligent management system for human resource management based on big data also includes a job seeker information sending module; the job seeker information sending module is connected to the job information pushing module; The job seeker information sending module is used to send the job seeker information suitable for the job information to the corresponding enterprise while pushing the suitable job information in the job information pushing module, so that the enterprise can check and achieve the effect of two-way selection.

8. An application of a digital intelligent management system for human resource management based on big data, using the digital intelligent management system for human resource management based on big data as described in any one of claims 1 to 7, characterized in that: The digital intelligent management system for human resource management based on big data is applied to digital intelligent management for human resource management.

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