Employment service management system based on intelligent big data

Abstract

The invention relates to the technical field of employment service, in particular to an employment service management system based on intelligent big data. According to the system, an enterprise recruitment demand is acquired through a demand acquisition unit, a demand extraction unit extracts a plurality of demand tags based on the recruitment demand, and a retrieval unit acquires a plurality of pieces of job application information meeting the recruitment demand from an employment database based on the demand tags; the screening unit is used for screening a plurality of pieces of job application information according to a preset screening label to obtain a plurality of pieces of screened information, the auditing unit is used for auditing based on the screened information to obtain auditing information and sending interview notifications to corresponding job application personnel, and the statistical unit is used for counting the personnel increase quantity of an enterprise in a preset period; the analysis unit judges whether the recruitment process meets the standard based on comparison of the personnel increase number and the preset value and determines reasons when the recruitment process does not meet the standard, and finally the adjustment module determines and adjusts the operation parameters of the corresponding unit based on the reasons, so that the recruitment process is optimized, and the recruitment efficiency of an enterprise is improved.

Description

Technical Field

[0001] The present invention relates to the field of employment service technology, and in particular to an employment service management system based on intelligent big data. Background Art

[0002] Employment service management is one of the means to allocate human resources and maintain social stability. Through some measures of employment service management, the needs of workers for job hunting and the needs of employers for recruiting personnel can be met.

[0003] The current employment service system includes some recruitment platforms, which input some resume information of job seekers and some recruitment needs of enterprises through the platform, and then display the information of relevant enterprises to job seekers or display the information of relevant job seekers to enterprises through the platform, so as to promote employment in related industries. However, the current existing technology only provides some basic information for both, and cannot effectively monitor and feedback the employment status. In actual situations, it will make it impossible for recruiting companies to accurately recruit the required job seekers or the number of recruits will be insufficient, which will affect the recruitment efficiency of related companies, thus affecting the business conditions of the companies and the employment efficiency of job seekers. Summary of the invention

[0004] To this end, the present invention provides an employment service management system based on intelligent big data, which can determine whether the recruitment process meets the standards by monitoring the number of personnel increases in the enterprise, and determine the corresponding processing when the recruitment does not meet the standards to achieve self-regulation of the system, thereby improving recruitment efficiency.

[0005] To achieve the above purpose, the present invention provides an employment service management system based on intelligent big data, comprising:

[0006] A demand acquisition unit, which is connected to the enterprise to receive the recruitment demand of the enterprise;

[0007] A demand extraction unit, connected to the demand acquisition unit, for extracting a number of demand tags based on the recruitment demand;

[0008] A retrieval unit, which is connected to the demand extraction unit and the employment database respectively, and is used to search the employment database based on a number of the demand tags to obtain a number of job search information;

[0009] A screening unit connected to the retrieval unit, for screening the job-seeking information according to a preset screening tag to obtain screened information;

[0010] An audit unit, connected to the screening unit, for auditing the screened information to obtain audit information, and sending an interview notice to a job seeker corresponding to the audit information;

[0011] A statistical unit, which is connected to the enterprise and is used to count the number of employees added by the enterprise within a preset period;

[0012] an analysis unit, which is connected to the review unit and the statistics unit respectively, and is used to determine whether the recruitment process meets the standards based on the comparison result of the number of personnel increase and the preset number of personnel increase, and to generate corresponding instructions based on the reasons for not meeting the standards;

[0013] The adjustment unit is connected to the retrieval unit, the screening unit and the analysis unit respectively, and is used to increase the amount of the job search information acquired by the retrieval unit, update the screening label of the screening unit or reduce the determination criterion of the analysis unit based on the instruction.

[0014] Further, the analysis unit is used to make a determination based on a comparison result of the personnel increase ratio with a preset personnel increase ratio stored in the analysis unit, or to re-determine whether the recruitment process meets the standards based on the proportion of on-the-job personnel, and to determine the reasons for not meeting the standards based on the interview notification sending rate when it is determined that the recruitment process does not meet the standards;

[0015] Among them, the personnel increase ratio is the ratio between the number of personnel increases and the number of personnel needed for recruitment, the proportion of on-the-job personnel is the ratio between the actual number of people in the position and the expected number of people in the position, and the interview notification sending rate is the ratio between the number of review information and the total number of job search information.

[0016] Furthermore, the analysis unit is also used to determine whether to reduce the preset personnel increase ratio of the analysis unit based on a comparison result of the on-the-job personnel ratio with a preset on-the-job personnel ratio pre-stored in the analysis unit.

[0017] Furthermore, the analysis unit is also used to determine to reduce the preset personnel increase ratio of the analysis unit based on a comparison result of the on-the-job personnel ratio difference with a preset on-the-job personnel ratio difference pre-stored in the analysis unit, and the reduction degree of the preset personnel increase ratio is directly proportional to the on-the-job personnel ratio difference, wherein the on-the-job personnel ratio difference is the difference between the on-the-job personnel ratio and the preset on-the-job personnel ratio.

[0018] Furthermore, the analysis unit is also used to determine the reason why the recruitment process does not meet the standards based on the comparison result of the interview notification sending rate and the preset interview notification sending rate pre-stored in the analysis unit, and determine the corresponding processing based on the reason, including: updating the screening label of the screening unit, or re-determining the reason why the recruitment process does not meet the standards based on the interview completion degree, wherein the interview completion degree is the ratio between the actual number of people participating in the interview and the total number of interview notifications sent.

[0019] Furthermore, the screening unit is also used to update the tags with an appearance frequency higher than a preset appearance frequency into the screening tags based on the job search information excluded by the review unit in the previous review process, wherein, for a single tag, the number of job search information with the tag that is screened out after the review is recorded as the preset appearance frequency.

[0020] Furthermore, the analysis unit is also used to determine to reduce the preset occurrence frequency of the screening tag based on the comparison result of the sending rate difference and the preset sending rate difference pre-stored in the analysis unit, and the reduction degree of the preset occurrence frequency is proportional to the sending rate difference.

[0021] Furthermore, the analysis unit is also used to re-determine the reason for failure of the recruitment process based on the comparison result of the interview completion degree with the preset interview completion degree pre-stored in the analysis unit, and determine the corresponding processing based on the reason, including: increasing the amount of job search information obtained by the retrieval unit, or increasing the update frequency of the employment database.

[0022] Furthermore, the analysis unit is also used to determine to increase the update frequency of the employment database based on a comparison result of the completion difference with a preset completion difference pre-stored in the analysis unit, and the increase in the update frequency is directly proportional to the completion difference, wherein the completion difference is the difference between the preset interview completion and the interview completion.

[0023] Furthermore, the analysis unit is also used to determine to increase the number of job search information acquired by the retrieval unit based on a comparison result of the ratio difference with a preset ratio difference pre-stored in the analysis unit, and the increase in the number of job search information is directly proportional to the ratio difference, wherein the ratio difference is the difference between the preset personnel increase ratio and the personnel increase ratio.

[0024] Compared with the prior art, the beneficial effect of an employment service management system based on intelligent big data of the present invention is that the system obtains the recruitment needs of the enterprise through a demand acquisition unit, extracts a plurality of demand tags based on the recruitment needs through a demand extraction unit, obtains a plurality of job search information that meets the recruitment needs from the employment database based on the demand tags through a retrieval unit, screens the plurality of job search information according to preset screening tags through a screening unit to obtain a plurality of screened information, obtains the review information based on the screened information through a review unit and sends an interview notice to the corresponding job seeker, counts the number of personnel added by the enterprise within a preset period through a statistical unit, determines whether the recruitment process meets the standards based on a comparison between the number of personnel added and the preset number of personnel added through an analysis unit, and determines the reasons when it does not meet the standards, and finally determines to adjust the operating parameters of the corresponding unit based on the reasons through an adjustment module, and then optimizes the recruitment process through self-adjustment, thereby improving the recruitment efficiency of the enterprise.

[0025] Furthermore, the present invention also determines whether the recruitment process meets the standards based on the comparison between the personnel increase ratio and the preset personnel increase ratio, and can determine the reason based on the interview notification sending rate, so as to quickly adjust the operating parameters of the corresponding units of the system to optimize the recruitment process.

[0026] Furthermore, the present invention also re-evaluates the recruitment process based on the comparison result of the proportion of on-the-job personnel and the preset proportion of on-the-job personnel, thereby reducing misjudgment and improving the judgment accuracy of the process.

[0027] Furthermore, when the present invention determines that the current recruitment process meets the standards during the secondary judgment, it can also reduce the preset personnel increase ratio of the analysis unit based on the difference in the proportion of on-the-job personnel, thereby expanding the judgment range of recruitment meeting the standards, thereby helping enterprises to quickly complete recruitment tasks.

[0028] Furthermore, the present invention also determines the specific reasons why the recruitment process does not meet the standards based on the comparison results of the interview notification sending rate and the preset interview notification sending rate, and determines the corresponding processing based on the reasons, and increases the amount of review information by updating the screening label of the screening unit, thereby increasing the number of interviewers and improving recruitment efficiency.

[0029] Furthermore, when updating the screening unit, the present invention further determines based on the sending rate difference whether to reduce the preset occurrence frequency of the screening tag, thereby increasing the amount of audit information.

[0030] Furthermore, when determining the reason why the recruitment process does not meet the standards, the present invention further determines the specific reason based on the comparison result of the interview completion degree with the preset interview completion degree, thereby improving the accuracy of determining the reason.

[0031] Furthermore, after further determining the reasons why the recruitment does not meet the standards, the present invention determines the corresponding processing based on the reasons, optimizes the recruitment process by increasing the update frequency of the employment database or increasing the amount of job search information obtained by the retrieval unit, thereby improving the personnel increase ratio and improving recruitment efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] Figure 1 This is a module diagram of an employment service management system based on intelligent big data in this embodiment;

[0033] Figure 2 This is a flow chart of an employment service management system based on intelligent big data in this embodiment;

[0034] Figure 3 This is a logic flow chart for determining whether the recruitment process meets the standards based on the personnel increase ratio in this embodiment;

[0035] Figure 4 This is a logic flow chart for determining the reason why the recruitment process does not meet the standards and correcting the recruitment process based on the interview notification sending rate in this embodiment;

[0036] Figure 5 This is a logical flow chart for re-determining the reasons why the recruitment process does not meet the standards and correcting the recruitment process based on the interview completion rate in this embodiment. DETAILED DESCRIPTION

[0037] In order to make the objects and advantages of the present invention more clearly understood, the present invention is further described below in conjunction with embodiments; it should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0038] The preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood by those skilled in the art that these embodiments are only used to explain the technical principles of the present invention and are not intended to limit the protection scope of the present invention.

[0039] It should be noted that in the description of the present invention, unless otherwise clearly specified and limited, the term "connection" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium, or it can be the internal communication of two components. For those skilled in the art, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0040] In the present embodiment, an employment service management system based on intelligent big data is provided. The employment service management system in the present embodiment is a system for enterprises to obtain job search information from the employment database and conduct audits. The system can monitor the recruitment situation of the enterprise within a preset period in real time, and determine whether the recruitment process meets the standards based on the number of additional personnel, that is, whether it meets the expected number of recruits of the enterprise. It can also determine the reasons why the recruitment process does not meet the standards based on the number of additional personnel, and then realize self-regulation of the system through corresponding processing, thereby improving the recruitment efficiency of the enterprise.

[0041] See also Figure 1As shown, it is a module diagram of an employment service management system based on intelligent big data in this embodiment. The system includes an enterprise, an employment database, a demand acquisition unit, a demand extraction unit, a retrieval unit, a screening unit, an audit unit, a statistical unit, an analysis unit and an adjustment unit. The demand acquisition unit is connected to the enterprise to receive the recruitment needs of the enterprise; the demand extraction unit is connected to the demand acquisition unit to extract a number of demand tags based on the recruitment needs; the retrieval unit is respectively connected to the demand extraction unit and the employment database to search the employment database based on a number of the demand tags to obtain a number of job search information; the screening unit is connected to the retrieval unit to screen the job search information according to a preset screening tag to obtain the screened information; the audit unit is connected to the screening unit to audit the screened information to obtain the audit information, and to send the audit information to the audit unit. the statistical unit is connected with the enterprise to count the number of personnel increases in the enterprise within a preset period; the analysis unit is connected with the review unit and the statistical unit respectively to determine whether the recruitment process meets the standards based on the comparison result of the number of personnel increases with the preset number of personnel increases, and to generate corresponding instructions based on the reasons for not meeting the standards; the adjustment unit is connected with the retrieval unit, the screening unit and the analysis unit respectively to increase the number of job search information obtained by the retrieval unit, update the screening label of the screening unit or lower the determination criterion of the analysis unit based on the instructions.

[0042] Specifically, in this embodiment, when an enterprise needs to recruit job seekers, it can receive the recruitment needs of the enterprise through a demand acquisition unit connected to the enterprise; then, the recruitment needs are obtained through a demand extraction unit connected to the demand acquisition unit, and a number of demand tags are extracted based on the recruitment needs. The demand tags are key search terms classified and planned from the recruitment needs, and the corresponding information can be obtained based on these demand tags; then, the demand tags are obtained through a retrieval unit connected to the demand extraction unit and the employment database respectively, and the job seeker information in the employment database is retrieved based on the demand tags to preliminarily obtain a number of job search information that meets the recruitment needs of the enterprise, wherein each job search information includes a number of tags. When searching, the number of tags corresponding to the demand tags in a single job search information is obtained, and the ratio between the number of tags and the total number of demand tags is calculated, and the ratio is recorded as the job search information ratio. When the job search information ratio is greater than the preset job search information ratio, the job search information is obtained; then, the obtained job search information is further screened according to the preset screening tags by a screening unit connected to the retrieval unit to obtain a number of screened information. Such a setting can be further screened before the interview so that the recruiter can quickly find the job search information that meets the needs of the enterprise. Job seekers, wherein, when screening, the number of labels corresponding to the screened labels in a single screened information is obtained, and the ratio between the number of labels and the total number of screened labels is calculated, and the ratio is recorded as the screened information ratio. When the screened information ratio is less than or equal to the preset screened information ratio, the screened information is obtained. In this embodiment, when the current enterprise first enables the management system, the preset screened labels have not been constructed. After enabling the management system more than once, the preset screened labels that meet the current enterprise recruitment needs are constructed and updated; then the screened information is obtained through the review unit connected to the screening unit, and based on The screened information is reviewed to obtain the review information, and then an interview notice is sent to the job seeker corresponding to the review information, wherein the screened information obtained before the review is automatically screened and pushed to the enterprise by the management system according to the recruitment needs, and the review information is obtained after the enterprise's recruiters further review the screened information according to the actual situation of the enterprise; then the number of personnel added by the enterprise within the preset period is obtained through the statistical unit connected to the enterprise, and corresponding data is provided for subsequent analysis of the employment service management system, wherein the preset period refers to the time taken from the issuance of the interview notice to the job seeker's formal reporting to the enterprise for work;The number of personnel increases is obtained through the analysis unit connected to the audit unit and the statistical unit respectively, and the comparison result between the number of personnel increases and the preset number of personnel increases is used to determine whether the current recruitment process meets the standard. When the number of personnel increases is greater than the preset number of personnel increases, the recruitment process can be determined to meet the standard. If the recruitment process does not meet the standard, the corresponding reason can be determined based on the number of personnel increases, and the corresponding instruction is generated based on the reason, wherein meeting the standard means that the number of personnel increases in this recruitment can at least meet the expected number of personnel to be recruited by the enterprise at the current time; the instruction is obtained through the adjustment unit connected to the retrieval unit, the screening unit and the analysis unit respectively, and the operating parameters in the corresponding unit are adjusted based on the instruction, so as to realize the self-adjustment of the employment service management system, thereby meeting the recruitment needs of the enterprise, increasing the number of personnel increases of the enterprise, and thus increasing the number of employed personnel, wherein the adjusted operating parameters include: increasing the number of job search information obtained by the retrieval unit, updating the screening label of the screening unit, or lowering the judgment criterion of the analysis unit. ;

[0043] See also Figure 2 As shown, it is a flow chart of an employment service management system based on intelligent big data in this embodiment. The process includes:

[0044] S1: Receive the recruitment needs of the enterprise through a demand acquisition unit connected to the enterprise.

[0045] S2: extracting a number of requirement tags based on the recruitment requirements through a requirement extraction unit connected to the requirement acquisition unit.

[0046] S3: searching the employment database based on a number of the demand tags to obtain a number of job search information via a retrieval unit connected to the demand extraction unit and the employment database respectively.

[0047] S4: filtering the job search information according to preset screening tags through a screening unit connected to the retrieval unit to obtain screened information.

[0048] S5: The screened information is reviewed by a review unit connected to the screening unit to obtain review information, and an interview notice is sent to the job seeker corresponding to the review information.

[0049] S6: Counting the number of employees added in the enterprise within a preset period through a statistical unit connected to the enterprise.

[0050] S7: determining whether the recruitment process meets the standards based on the comparison result between the number of personnel increase and the preset number of personnel increase through the analysis unit respectively connected to the review unit and the statistical unit, and generating corresponding instructions based on the reasons for not meeting the standards.

[0051] S8: increasing the amount of job search information acquired by the retrieval unit, updating the screening label of the screening unit, or lowering the determination criterion of the analysis unit based on the instruction through the adjustment unit respectively connected to the retrieval unit, the screening unit, and the analysis unit.

[0052] See also Figure 3 As shown, it is a logic flow chart of determining whether the recruitment process meets the standards based on the personnel increase ratio in this embodiment. The analysis unit is used to determine based on the comparison result of the personnel increase ratio with the preset personnel increase ratio stored in the analysis unit, or to re-determine whether the recruitment process meets the standards based on the proportion of on-the-job personnel, and to determine the reason for not meeting the standards based on the interview notification sending rate when it is determined that the recruitment process does not meet the standards;

[0053] Among them, the personnel increase ratio is the ratio between the number of personnel increases and the number of personnel needed for recruitment, the proportion of on-the-job personnel is the ratio between the actual number of people in the position and the expected number of people in the position, and the interview notification sending rate is the ratio between the number of review information and the total number of job search information.

[0054] Specifically, in this embodiment, the preset staff increase ratio L0 can be divided into a first preset staff increase ratio L1 and a second preset staff increase ratio L2, and the preset staff increase ratio standard L3=0.6, L1=L3, L2=1.5×L3 is set. It should be noted that in other embodiments, the values ​​of L1, L2 and L3 can also be determined according to relative recruitment needs, and the values ​​of the staff are rounded up; the comparison process based on the staff increase ratio L with L1 and L2 is as follows:

[0055] If L<L1, it means that the number of personnel added in the current preset period is relatively small. Therefore, it can be determined that the current recruitment process does not meet the standards. It is necessary to determine the reason why the recruitment process does not meet the standards based on the interview notification sending rate P, where P is the ratio of the number of audited information after review to the total number of job search information obtained by the company from the employment database; if L1≤L<L2, it is impossible to determine whether the current recruitment process meets the standards. In order to avoid misjudgment, it is necessary to further determine based on the proportion of on-the-job personnel Q to ensure the accuracy of the judgment result; if L2≤L, it means that the number of personnel added in the current preset period is relatively large, which can preliminarily meet the company's expected recruitment goals. Therefore, it can be determined that the current recruitment process meets the standards, and subsequent recruitment work will continue according to the current system settings.

[0056] Furthermore, the analysis unit is also used to determine whether to reduce the preset personnel increase ratio of the analysis unit based on a comparison result of the on-the-job personnel ratio with a preset on-the-job personnel ratio pre-stored in the analysis unit.

[0057] Specifically, in this embodiment, when making a secondary judgment, the proportion of on-the-job personnel Q is the ratio between the actual number of positions and the expected number of positions. The expected number of positions is certain. The proportion of on-the-job personnel Q can determine the actual number of positions of the current enterprise, and then the number of recruitment needs can be calculated. The number of recruitment needs is the difference between the expected number of positions and the actual number of positions. When the Q value is larger, the number of recruitment needs is smaller. When the number of recruitment needs is smaller, the increase in personnel is larger. Therefore, when re-judgment is made, if the Q value is greater than the preset value, it means that the current recruitment process also meets the standards, and the judgment benchmark at this time needs to be lowered to expand the scope of recruitment that meets the standards; the proportion of on-the-job personnel Q0 is preset to be 0.5, and the comparison process based on Q and Q0 is as follows:

[0058] If Q≤Q0, it means that the actual number of people in the position within the current preset period is relatively small, while the corresponding number of recruitment needs is relatively large. If L1≤L<L2 at this time, it is determined that the number of added people has not reached the company's actual recruitment target for the position. Therefore, it can be determined that the current recruitment process does not meet the standards, and the reason for non-compliance with the standards needs to be determined based on the interview notification sending rate P; if Q0<Q, it means that the actual number of people in the position within the current preset period is relatively large, while the corresponding number of recruitment needs is relatively small. If L1≤L<L2 at this time, it is determined that the number of added people can actually initially meet the company's actual recruitment target for the position. At this time, L is qualified. Therefore, the L0 pre-stored in the analysis unit can be reduced to expand the judgment range of recruitment compliance, thereby helping the company to quickly complete the recruitment task.

[0059] Furthermore, the analysis unit is also used to determine to reduce the preset personnel increase ratio of the analysis unit based on a comparison result of the on-the-job personnel ratio difference with a preset on-the-job personnel ratio difference pre-stored in the analysis unit, and the reduction degree of the preset personnel increase ratio is directly proportional to the on-the-job personnel ratio difference, wherein the on-the-job personnel ratio difference is the difference between the on-the-job personnel ratio and the preset on-the-job personnel ratio.

[0060] Specifically, in this embodiment, the preset difference value N0 of the proportion of on-the-job personnel can be divided into a first preset difference value N1 of the proportion of on-the-job personnel and a second preset difference value N2 of the proportion of on-the-job personnel, and the preset difference value standard N3 of the proportion of on-the-job personnel is set to be 0.2, N1=N3, and N2=1.5×N3. It should be noted that N1, N2, and N3 can be adjusted accordingly as needed; the preset personnel increase ratio L of the analysis unit is reduced, specifically, the second preset personnel increase ratio L2 is reduced, and the comparison process based on the on-the-job personnel proportion difference N and N1 and N2 is as follows:

[0061] If N≤N1, the adjustment unit uses the first benchmark adjustment coefficient to reduce the preset personnel increase ratio L0 to 0.8 times the initial value, that is, the second preset personnel increase ratio L2 is reduced to 0.8 times the initial value; if N1<N≤N2, the adjustment unit uses the second benchmark adjustment coefficient to reduce L0 to 0.6 times the initial value, that is, L2 is reduced to 0.6 times the initial value; if N2<N, the adjustment unit uses the third benchmark adjustment coefficient to reduce L0 to 0.4 times the initial value, that is, L2 is reduced to 0.4 times the initial value; specifically, in this embodiment, the reduction ratio of L0 or L2 can also be modified accordingly and the obtained values ​​are rounded up.

[0062] See also Figure 4 As shown, it is a logic flow chart for determining the reason why the recruitment process does not meet the standards and correcting the recruitment process based on the interview notification sending rate in this embodiment. The analysis unit is also used to determine the reason why the recruitment process does not meet the standards based on the comparison result of the interview notification sending rate and the preset interview notification sending rate pre-stored in the analysis unit, and determine the corresponding processing based on the reason, including: updating the screening label of the screening unit, or re-determining the reason why the recruitment process does not meet the standards based on the interview completion degree, wherein the interview completion degree is the ratio between the actual number of interview participants and the total number of interview notifications sent.

[0063] Specifically, in this embodiment, the interview notification sending rate P0 is preset to be 0.7, and the comparison process based on the interview notification sending rate P and P0 is as follows:

[0064] If P≤P0, it means that the number of audited information is relatively small. At this time, the reason why the recruitment process does not meet the standards is that too many job applications are screened out, resulting in insufficient job applications that can pass the review. At this time, the screening unit's screening label can be updated based on the sending rate difference M, and the number of screened information can be increased by lowering the screening standard, thereby increasing the number of audited information to increase the interview notification sending rate P, so that the company can meet the recruitment needs. The sending rate difference M is the difference between P0 and P. If P0<P, it means that the number of audited information is relatively large, so there is no problem with the screening process. At this time, it is necessary to re-determine the reason why the recruitment process does not meet the standards based on the interview completion degree V.

[0065] Furthermore, the screening unit is also used to update the tags with an appearance frequency higher than a preset appearance frequency into the screening tags based on the job search information excluded by the review unit in the previous review process, wherein, for a single tag, the number of job search information with the tag that is screened out after the review is recorded as the preset appearance frequency.

[0066] Specifically, in this embodiment, the preset occurrence frequency K0 of a single tag is set to 5 times. If a tag with an occurrence frequency K greater than 5 times can be recorded as a screened-out tag, for this tag in a single job search information, no matter how many times it appears in the single job search information, it is recorded as 1 occurrence frequency K; the job search information excluded in the statistical review process, and the tags with K greater than K0 are updated into the screened-out tags, so that the screened information in the screening unit during the next screening can better meet the company's recruitment needs. In this embodiment, when the company uses the system for the first time, the screening tag is empty. After using the system for multiple times, the processing based on intelligent big data can gradually improve the company's recruitment needs, thereby improving the company's recruitment efficiency.

[0067] Furthermore, the analysis unit is also used to determine to reduce the preset occurrence frequency of the screening tag based on the comparison result of the sending rate difference and the preset sending rate difference pre-stored in the analysis unit, and the reduction degree of the preset occurrence frequency is proportional to the sending rate difference.

[0068] Specifically, in this embodiment, the preset transmission rate difference M0 can be divided into a first preset transmission rate difference M1 and a second preset transmission rate difference M2, and the preset transmission rate difference standard M3=0.2, M1=1.5×M3, M2=2.5×M3 is set. It should be noted that the values ​​of M1, M2 and M3 can be adjusted accordingly; the comparison process based on the transmission rate difference M with M1 and M2 is as follows:

[0069] If M≤M1, the preset occurrence frequency K0 is reduced to 0.8 times the initial value by using the first frequency adjustment coefficient through the adjustment unit; if M1<M≤M2, the second frequency adjustment coefficient is used by the adjustment unit to reduce K0 to 0.6 times the initial value; if M2<M, the third frequency adjustment coefficient is used by the adjustment unit to reduce K0 to 0.4 times the initial value; specifically, in this embodiment, the reduction ratio of K0 can be adjusted accordingly, and is rounded up.

[0070] See also Figure 5 As shown, it is a logic flow chart for re-determining the reason why the recruitment process does not meet the standards based on the interview completion degree and correcting the recruitment process in this embodiment. The analysis unit is also used to re-determine the reason why the recruitment process is unqualified based on the comparison result of the interview completion degree and the preset interview completion degree pre-stored in the analysis unit, and determine the corresponding processing based on the reason, including: increasing the amount of job search information obtained by the retrieval unit, or increasing the update frequency of the employment database.

[0071] Specifically, in this embodiment, the preset interview completion degree V0 can be set to 0.85, and the comparison process based on the interview completion degree V and V0 is as follows:

[0072] If V≤V0, it means that the interview completion rate within the current preset period is relatively low, which actually means that the number of people who actually participated in the interview is relatively small. Therefore, it can be determined that the job search information in the employment database is not updated in a timely manner, and the job search information of people who have already been employed is sent to the company, which results in the people who received the interview notice being unable to participate in the interview, and further causes the recruitment process to not meet the standards. At this time, the update frequency of the employment database can be increased based on the comparison result of the completion difference H and the preset completion difference H0, where H is the difference between V0 and V. If V0<V, it means that the completion rate of interviews within the current preset period is relatively high, which actually means that the actual number of interview participants meets expectations. Therefore, it can be determined that the number of job search information obtained by the retrieval unit is insufficient, which actually means that the number of resumes obtained from the employment database does not match the number of recruitment needs. Even if the candidates who pass the interview are recruited into the company, there is a big gap between the expected personnel requirements for the position, which leads to the recruitment process not meeting the standards. At this time, the number of job search information obtained by the retrieval unit can be increased based on the comparison result of the ratio difference F and the preset ratio difference F0, where F is the difference between the preset personnel increase ratio L0 and the personnel increase ratio L. More specifically, in this embodiment, F is the difference between L1 and L.

[0073] Furthermore, the analysis unit is also used to determine to increase the update frequency of the employment database based on a comparison result of the completion difference with a preset completion difference pre-stored in the analysis unit, and the increase in the update frequency is directly proportional to the completion difference, wherein the completion difference is the difference between the preset interview completion and the interview completion.

[0074] Specifically, in this embodiment, the preset completion difference H0 can be divided into a first preset completion difference H1 and a second preset completion difference H2, and the preset completion difference standard H3=0.1, H1=2×H3, H2=4×H3 is set. It should be noted that the values ​​of H1, H2 and H3 can be modified accordingly; the comparison process based on the completion difference H and H0 is as follows:

[0075] The adjustment unit is also connected to the employment database. If H≤H1, the adjustment unit uses the first update frequency adjustment coefficient to increase the update frequency to 1.5 times the initial value; if H1<H≤H2, the adjustment unit uses the second update frequency adjustment coefficient to increase the update frequency to 2 times the initial value; if H2<H, the adjustment unit uses the third update frequency adjustment coefficient to increase the update frequency to 2.5 times the initial value; specifically, in this embodiment, the increase ratio of the update frequency can also be other values.

[0076] Furthermore, the analysis unit is also used to determine to increase the number of job search information acquired by the retrieval unit based on a comparison result of the ratio difference with a preset ratio difference pre-stored in the analysis unit, and the increase in the number of job search information is directly proportional to the ratio difference, wherein the ratio difference is the difference between the preset personnel increase ratio and the personnel increase ratio.

[0077] Specifically, in this embodiment, the ratio difference F is specifically the difference between the first preset personnel increase ratio L1 and the personnel increase ratio L, and the preset ratio difference F0 can be divided into a first preset ratio difference F1 and a second preset ratio difference F2; the comparison process based on F with F1 and F2 is as follows:

[0078] If F≤F1, the adjustment unit uses the first adjustment coefficient for the number of job search information obtained to increase the number of job search information obtained to twice the initial value; if F1<F≤F2, the adjustment unit uses the second adjustment coefficient for the number of job search information obtained to increase the number of job search information obtained to four times the initial value; if F2<F, the adjustment unit uses the third adjustment coefficient for the number of job search information obtained to increase the number of job search information obtained to six times the initial value; specifically, in this embodiment, the increase ratio of the number of job search information obtained can also be other values.

[0079] So far, the technical solutions of the present invention have been described in conjunction with the preferred embodiments shown in the accompanying drawings. However, it is easy for those skilled in the art to understand that the protection scope of the present invention is obviously not limited to these specific embodiments. Without departing from the principle of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will fall within the protection scope of the present invention.

[0080] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. For those skilled in the art, the present invention may have various modifications and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. An employment service management system based on intelligent big data, characterized in that: include: A demand acquisition unit, which is connected to the enterprise to receive the recruitment demand of the enterprise; A demand extraction unit, connected to the demand acquisition unit, for extracting a number of demand tags based on the recruitment demand; A retrieval unit, which is connected to the demand extraction unit and the employment database respectively, and is used to search the employment database based on a number of the demand tags to obtain a number of job search information; A screening unit connected to the retrieval unit, for screening the job-seeking information according to a preset screening tag to obtain screened information; An audit unit, connected to the screening unit, for auditing the screened information to obtain audit information, and sending an interview notice to a job seeker corresponding to the audit information; A statistical unit, which is connected to the enterprise and is used to count the number of employees added by the enterprise within a preset period; an analysis unit, which is connected to the review unit and the statistics unit respectively, and is used to determine whether the recruitment process meets the standards based on the comparison result of the number of personnel increase and the preset number of personnel increase, and to generate corresponding instructions based on the reasons for not meeting the standards; The adjustment unit is connected to the retrieval unit, the screening unit and the analysis unit respectively, and is used to increase the amount of the job search information acquired by the retrieval unit, update the screening label of the screening unit or reduce the determination criterion of the analysis unit based on the instruction.

2. The employment service management system based on intelligent big data according to claim 1 is characterized in that: The analysis unit is used to make a determination based on a comparison result of the personnel increase ratio with a preset personnel increase ratio stored in the analysis unit, or to re-determine whether the recruitment process meets the standards based on the proportion of on-the-job personnel, and to determine the reasons for not meeting the standards based on the interview notification sending rate when it is determined that the recruitment process does not meet the standards; Among them, the personnel increase ratio is the ratio between the number of personnel increases and the number of personnel needed for recruitment, the proportion of on-the-job personnel is the ratio between the actual number of people in the position and the expected number of people in the position, and the interview notification sending rate is the ratio between the number of review information and the total number of job search information.

3. The employment service management system based on intelligent big data according to claim 2 is characterized in that: The analysis unit is further used to determine whether to reduce the preset personnel increase ratio of the analysis unit based on a comparison result of the on-the-job personnel ratio with a preset on-the-job personnel ratio pre-stored in the analysis unit.

4. The employment service management system based on intelligent big data according to claim 3 is characterized in that: The analysis unit is also used to determine to reduce the preset personnel increase ratio of the analysis unit based on the comparison result of the on-the-job personnel ratio difference and the preset on-the-job personnel ratio difference stored in the analysis unit, and the reduction degree of the preset personnel increase ratio is directly proportional to the on-the-job personnel ratio difference, wherein the on-the-job personnel ratio difference is the difference between the on-the-job personnel ratio and the preset on-the-job personnel ratio.

5. The employment service management system based on intelligent big data according to claim 2 is characterized in that: The analysis unit is also used to determine the reason why the recruitment process does not meet the standards based on the comparison result of the interview notification sending rate and the preset interview notification sending rate pre-stored in the analysis unit, and determine the corresponding processing based on the reason, including: updating the screening label of the screening unit, or re-determining the reason why the recruitment process does not meet the standards based on the interview completion degree, wherein the interview completion degree is the ratio between the actual number of people participating in the interview and the total number of interview notifications sent.

6. The employment service management system based on intelligent big data according to claim 5 is characterized in that: The screening unit is further configured to update the tags with an appearance frequency higher than a preset appearance frequency into the screening tags based on the job search information excluded by the review unit in the previous review process, wherein, for a single tag, the number of job search information with the tag that is screened out after the review is recorded as the preset appearance frequency.

7. The employment service management system based on intelligent big data according to claim 6 is characterized in that: The analysis unit is also used to determine to reduce the preset occurrence frequency of the screening tag based on the comparison result of the sending rate difference and the preset sending rate difference pre-stored in the analysis unit, and the reduction range of the preset occurrence frequency is proportional to the sending rate difference.

8. The employment service management system based on intelligent big data according to claim 5 is characterized in that: The analysis unit is also used to redetermine the reason for failure in the recruitment process based on a comparison result between the interview completion degree and a preset interview completion degree pre-stored in the analysis unit, and to determine corresponding processing based on the reason, including: increasing the amount of job search information obtained by the retrieval unit, or increasing the update frequency of the employment database.

9. The employment service management system based on intelligent big data according to claim 8 is characterized in that: The analysis unit is also used to determine to increase the update frequency of the employment database based on a comparison result of the completion difference with a preset completion difference pre-stored in the analysis unit, and the increase in the update frequency is proportional to the completion difference, wherein the completion difference is the difference between the preset interview completion and the interview completion.

10. The employment service management system based on intelligent big data according to claim 8 is characterized in that: The analysis unit is also used to determine to increase the number of job search information acquired by the retrieval unit based on a comparison result of the ratio difference with a preset ratio difference pre-stored in the analysis unit, and the increase in the number of job search information is directly proportional to the ratio difference, wherein the ratio difference is the difference between the preset personnel increase ratio and the personnel increase ratio.

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