Block chain-based interview management method and system

Abstract

The invention discloses an interview management method and system based on a block chain, and relates to the technical field of human resource management, and the method comprises the steps: carrying out the data extraction of recruitment information, and obtaining recruitment data; matching the resume information of the applicant with the recruitment data to determine the integrating degree of the applicant; sorting the resume information of each applicant based on the integrating degree to obtain sequence data; obtaining a screening result of a recruiter on the sorted resumes, and performing interview time arrangement on the screening result according to the sequence data; obtaining the number of enrollment personnel, when the number of the enrollment personnel is smaller than the recruitment number, analyzing the screening result, determining a resume filtering rule, and filtering resume information of subsequent applicants based on the resume filtering rule; and analyzing the resume information of the recording personnel and the resume information of the non-recording personnel, determining a screening rule, and screening the resume information of subsequent applicants based on the screening rule. The method has the effect of improving the recruitment efficiency.

Description

Technical Field

[0001] The present application relates to the field of human resource management technology, and in particular to an interview management method and system based on blockchain. Background Art

[0002] Interview is a key link in the recruitment process of enterprises, which directly affects the quality of talent selection and the development of enterprises. For a good position or enterprise, there are a large number of applicants, which leads to a large number of resumes. In traditional recruitment, it is necessary to manually screen the resumes of the applicants in turn, so as to select the applicants whose resumes meet the requirements for the next interview process. This takes up a lot of time and energy in the preliminary screening, so a blockchain-based interview management method and system is needed to improve recruitment efficiency. Summary of the invention

[0003] In order to improve recruitment efficiency, this application provides an interview management method and system based on blockchain.

[0004] In the first aspect, this application provides an interview management method based on blockchain, which adopts the following technical solutions:

[0005] A blockchain-based interview management method, comprising:

[0006] Obtain the number of applicants' resumes and judge the number of resumes. When the number of resumes is greater than the built-in screening threshold, obtain the recruitment information and extract the recruitment data from the recruitment information to obtain the recruitment data.

[0007] Determine the number of vacancies in the recruitment data to determine whether it is greater than 1. If it is 1, obtain the applicant's resume information based on the blockchain, match the resume information with the recruitment data, and determine the compatibility between the applicant and the recruitment information.

[0008] Sort the resume information of each applicant based on the degree of fit to obtain sequence data, and display and output the resume information of the applicant based on the sequence data;

[0009] Obtain the recruiter's screening results of the displayed resumes, arrange interview times for the screening results according to the sequence data, and send the arranged interview time to the corresponding applicants;

[0010] If the number of recruitments is greater than 1, the number of hired personnel is obtained and compared with the number of recruitments. When the number of hired personnel is less than the number of recruitments, the screening results are analyzed, the resume filtering rules are determined, and the resume information of subsequent applicants is filtered based on the resume filtering rules;

[0011] The resumes of the hired personnel are read to obtain the resume information of the hired personnel, and the resume information of the hired personnel is analyzed with the resume information of the unhired personnel to determine the screening rules, and the resume information of subsequent applicants is screened based on the screening rules.

[0012] Preferably, based on the screening results, determining resume information filtered out by the recruiter;

[0013] Based on the sequence data, read the sequence data of the filtered resume information;

[0014] The sequence data of the filtered resume information is judged to determine whether there is a sequence with a forward sequence number in the sequence data of the filtered resume information;

[0015] If there is resume information with a forward sequence number, the filtered resume information is analyzed to determine the difference between the filtered resume information and the resume information corresponding to the screening result, and the resume information in the screening result is matched as a whole based on the difference to determine whether the resume information in the screening result includes the difference;

[0016] If the number of resumes including a distinguishing point in the screening results is greater than a preset threshold, the distinguishing point will be deleted until the number of resumes including a certain distinguishing point in the screening results is less than the preset threshold, then the distinguishing point will be added to the system's filtering rules.

[0017] Preferably, the fit degree of the filtered resume information is obtained, and the resumes in the screening results are matched according to the fit degree to obtain resume information with the same fit degree;

[0018] Performing information item judgment on the filtered resume information to obtain the information item category of the filtered resume information and the information item data of the corresponding information item;

[0019] Performing information item judgment on the resume information with the same degree of fit, obtaining the information item category of the resume information with the same degree of fit and the information item data of the corresponding information item;

[0020] Compare the information item categories and information item data in the filtered resume information with the information item categories and information item data of the resume information with the same degree of fit to determine the information item category differences and information item data differences;

[0021] Based on the blockchain data, the data corresponding to the data difference of the corresponding information item is judged to obtain the quality data;

[0022] The information item category difference, information item data difference and the superiority and inferiority data of the corresponding information item data difference are uniformly marked as distinguishing points.

[0023] Preferably, the number of recruited personnel is judged to determine whether the number of recruited personnel is greater than 1. If the number of recruited personnel is greater than 1, the resume information of the recruited personnel is read to obtain the recruitment resume information;

[0024] Compare the resume information of the applicants to each other to determine the common item categories and common item data;

[0025] Based on the common item categories and common item data, the resume information of the unhired personnel is matched to determine whether there are common item categories and corresponding common item data in the resume information of the unhired personnel, and the common item categories and corresponding common item data that do not exist are marked as screening rules;

[0026] If the number of hired personnel is equal to 1, the resume information of the hired personnel is matched with the resume information of the unhired personnel to obtain the first similarity data;

[0027] Based on the built-in selection quantity and the first similarity data, the resume information of the unhired personnel with the highest similarity is marked to obtain comparative resume information;

[0028] Compare the resume information of the recruited personnel with the comparative resume information to determine the differences between the resume information of the recruited personnel and the comparative resume information;

[0029] Determine the correlation between the information data in the resume of the recruited personnel and the recruitment position;

[0030] If the difference point is related to the information data in the resume information of the recruited personnel and the recruitment position, the difference point is marked as a screening rule;

[0031] If the difference point has no relevance between the information data in the resume information of the recruited person and the recruitment position, the difference point will not be marked.

[0032] Preferably, based on the recruitment conditions and recruitment positions in the recruitment data, the rationality of the recruitment conditions in the recruitment data is judged to obtain rationality data;

[0033] Match the resume information with the recruitment conditions to obtain the first matching data;

[0034] Match the resume information with the recruitment position to obtain the second matching data;

[0035] Based on the rationality data, the first matching data and the second matching data are matched to calculate the matching degree to obtain the matching degree data.

[0036] Preferably, the resume information is matched with the recruitment conditions to obtain the satisfaction degree of each recruitment condition in the resume information and obtain the satisfaction degree data;

[0037] Obtain the importance coefficient of each recruitment condition, perform corresponding weighted processing on the satisfaction data of each recruitment condition based on the importance coefficient, and obtain the first matching data.

[0038] Preferably, the number of interviews and the number of recruits of the applicants are obtained, and the ratio of the number of recruits to the number of interviews is calculated to determine the recruitment rate;

[0039] Calculate the ratio of the number of interviews to the number of resumes to determine the interview rate;

[0040] Based on the acceptance rate, interview rate and number of resumes, the number of candidates who have not been interviewed is evaluated to obtain the expected number of candidates to be accepted.

[0041] Based on the number of recruits and the number of recruits in the recruitment data, the expected number of recruits is judged to determine whether the expected number of recruits meets the recruitment number;

[0042] If the estimated number of employees does not meet the number of employees to be recruited, the second matching data of the applicants are counted to determine the second matching data set;

[0043] Performing normal analysis on the second matching data set to determine the applicant's satisfaction with the recruitment position, and reading the first matching data of the corresponding applicant according to the satisfaction, and judging the read first matching data of the corresponding applicant with the recruitment conditions to determine the recruitment conditions that the read corresponding applicant satisfies;

[0044] The recruitment conditions are regularized based on the recruitment conditions satisfied by the corresponding applicants to obtain new recruitment conditions, and the new recruitment conditions are output for the reference of the recruiter.

[0045] In the second aspect, this application provides an interview management system based on blockchain, which adopts the following technical solutions:

[0046] An interview management system based on blockchain, including: recruitment information analysis module, resume analysis module, and resume regularization module;

[0047] Recruitment information analysis module, which obtains the number of applicants' resumes and determines the number of resumes. When the number of resumes is greater than the built-in screening threshold, the recruitment information is obtained and recruitment data is extracted from the recruitment information to obtain recruitment data;

[0048] The resume analysis module determines the number of recruitments in the recruitment data to determine whether the number of recruitments is greater than 1. If the number of recruitments is 1, the resume information of the applicant is obtained based on the blockchain, and the resume information is matched with the recruitment data to determine the compatibility between the applicant and the recruitment information.

[0049] The resume sorting module sorts the resume information of each applicant based on the degree of fit, obtains sequence data, and displays and outputs the resume information of the applicant based on the sequence data; obtains the screening results of the recruiter on the displayed resumes, arranges the interview time for the screening results according to the sequence data, and sends the arranged interview time to the corresponding applicant; if the number of recruitments is greater than 1, the number of hired personnel is obtained, and the number of hired personnel is compared with the number of recruitments. When the number of hired personnel is less than the number of recruitments, the screening results are analyzed, the resume filtering rules are determined, and the resume information of subsequent applicants is filtered based on the resume filtering rules; the resumes of hired personnel are read to obtain the resume information of hired personnel, and the resume information of hired personnel is analyzed with the resume information of unhired personnel to determine the screening rules, and the resume information of subsequent applicants is filtered based on the screening rules.

[0050] In summary, the present application includes at least one of the following beneficial technical effects:

[0051] 1. By judging the degree of fit between the applicant's resume information and the recruitment information, the applicant's resume information is arranged according to the degree of fit, so that the resume that meets the recruitment requirements is placed at the front, thereby improving the recruitment rate. By analyzing the screening results of the recruiter, the resume information is filtered once, and then by analyzing the resume information of the recruited personnel, the resume information is filtered once, thereby further improving the quality of the recruiter's review of the applicant's resume information, thereby improving the recruitment recruitment rate and improving the recruitment efficiency;

[0052] 2. By judging the serial number of the resume information filtered out by the recruiter, it is determined whether the resume information filtered out by the recruiter is related to the degree of fit. If there is a sequence with a higher serial number, it means that the recruiter does not follow the degree of fit when filtering the resume information. Therefore, by comparing and analyzing the filtered resume information with the resume information in the screening results, and then comparing the difference points obtained by the comparison and analysis with the resume information in the screening results, it is determined whether the corresponding difference points are the filtering reasons for the recruiter to filter the resume information, and the difference points determined as filtering reasons are added to the filtering rules to filter the resumes of subsequent applicants, so as to improve the quality of resumes viewed by recruiters. Among them, the higher the resume quality, the more the resume of the applicant meets the recruitment needs of the recruiter;

[0053] 3. Comprehensively utilize the comparative analysis of the filtered resume information and the resume information of the hired personnel to determine the difference between the filtered resume information and the screened information and the information items unique to the hired personnel, and compare the difference points with the resume information in the screening results to determine whether the corresponding difference points are the filtering reasons for the recruiter to filter the resume information, and add the difference points determined as filtering reasons to the filtering rules to filter the resumes of subsequent applicants, and determine whether the information items unique to the hired personnel and the recruitment positions are related to determine whether the information items are the reasons for the recruiter to screen the applicants, and add the information items determined as screening reasons to the screening rules to screen the resumes of subsequent applicants, thereby improving the quality of resumes viewed by recruiters. BRIEF DESCRIPTION OF THE DRAWINGS

[0054] Figure 1 This is a flowchart of the steps of the blockchain-based interview management method of this embodiment;

[0055] Figure 2 This is a module block diagram of the blockchain-based interview management system in this embodiment.

[0056] Figure numerals: 1. Recruitment information analysis module; 2. Resume analysis module; 3. Resume organization module. DETAILED DESCRIPTION

[0057] The following is combined with Figure 1-Figure 2 This application is described in further detail.

[0058] The embodiments of the present application disclose a blockchain-based interview management method and system.

[0059] Example: Figure 1 As shown, the present invention provides an interview management method based on blockchain, comprising:

[0060] S100, obtaining the number of resumes of applicants and judging the number of resumes. When the number of resumes is greater than the built-in screening threshold, obtaining recruitment information and extracting recruitment data from the recruitment information to obtain recruitment data; this application is applied to the case where there are too many resumes submitted by applicants, thereby helping recruiters to screen and sort out a large number of submitted resumes, so that recruiters can quickly and effectively view and screen the resume information of applicants, thereby improving the recruitment rate and effective recruitment. By extracting data from the recruitment information of recruiters, the system is helped to determine the recruitment needs of recruiters, providing a data basis for assisting recruiters in recruitment.

[0061] S200, judging the number of recruitments in the recruitment data to determine whether the number of recruitments is greater than 1. If the number of recruitments is 1, obtaining the resume information of the applicant based on the blockchain, matching the resume information with the recruitment data, and determining the degree of fit between the applicant and the recruitment information; by judging the number of recruitments, it is determined whether to screen and filter the resume information of the applicant in the future, thereby simplifying the system process, improving efficiency and reducing the possibility of system failure.

[0062] S300, sorting the resume information of each applicant based on the degree of fit to obtain sequence data, and displaying and outputting the resume information of the applicant based on the sequence data; by matching the resume information of the applicant with the recruitment data, the recruiter can more quickly screen out effective resume information when screening the resumes, thereby improving the speed of screening resumes.

[0063] S400, obtaining the screening results of the displayed resumes by the recruiter, arranging interview time for the screening results according to the sequence data, and sending the arranged interview time to the corresponding applicant;

[0064] S500, if the number of recruitments is greater than 1, the number of hired personnel is obtained, and the number of hired personnel is compared with the number of recruitments. When the number of hired personnel is less than the number of recruitments, the screening results are analyzed, the resume filtering rules are determined, and the resume information of subsequent applicants is filtered based on the resume filtering rules; when the number of recruitments is greater than 1 and the recruitment task is not completed, it means that the recruiter still needs to recruit talents. Therefore, by analyzing and judging the screening results of the recruiter, the system can understand the needs of the recruiter more accurately, and then when judging the resume information of the next applicant, the resume information of the next applicant is simply screened, thereby further improving the recruiter's resume screening rate.

[0065] S600, read the resume of the hired personnel, obtain the resume information of the hired personnel, analyze the resume information of the hired personnel and the resume information of the unhired personnel, determine the screening rules, and screen the resume information of subsequent applicants based on the screening rules. When analyzing the resume information, the resume information of the applicants is processed according to a unified rule, so that the resume information of different applicants can be uniformly compared.

[0066] In this embodiment, when there are too many resumes of applicants who have submitted applications, the degree of compatibility between the resume information of the applicants and the recruitment information is judged, and the resumes of the applicants are sorted according to the degree of compatibility, thereby ensuring the quality of the resume information viewed by the recruiter, and then assisting the recruiter to quickly screen the resumes of the applicants, thereby improving recruitment efficiency. By analyzing the screening results of the recruiter, the system can more accurately understand the recruiter's demand for talents, so as to filter the resume information for the next time, thereby further improving the quality of the resume information viewed by the recruiter. By analyzing the resume information of the hired personnel, the system can further understand the needs of the recruiter, and then screen the resume information, thereby improving the quality of the resume information viewed by the recruiter.

[0067] By judging the compatibility between the applicant's resume information and the recruitment information, and arranging the applicant's resume information according to the compatibility, the resumes that meet the recruitment requirements are placed at the front, thereby improving the acceptance rate. By analyzing the screening results of the recruiter, the resume information is filtered once, and then by analyzing the resume information of the recruited personnel, the resume information is screened once, thereby further improving the quality of the recruiter's review of the applicant's resume information, thereby improving the recruitment acceptance rate and improving recruitment efficiency.

[0068] For example, there are applicants A, B, C, D, and E, who submit resumes a, b, c, d, and e respectively. The resume submission order is a, b, c, d, and e. If the final recruits are D and E, if interviews are conducted in sequence according to the resume submission order, the desired talent can only be recruited after three unsatisfactory interviews. In the present invention, the recruitment information fit is judged for resumes a, b, c, d, and e, and the fit results are 90%, 60%, 30%, 90%, and 100% respectively. The interview order after the fit is sorted is e, a, d, b, c, so only three interviews are needed at most to recruit the desired talents, thereby saving interview time and improving recruitment efficiency. When the recruiter's filtering conditions are analyzed to determine that the recruiter filters condition m, and among the submitted resumes a, b, c, d, e, resume a includes condition m, then by filtering condition m, the interview order is e, d, b, c, a. Similarly, the recruiter's screening conditions are analyzed. For example, the screening condition is n, and resume d includes screening condition n, then the interview order is d, e, b, c, a.

[0069] In step S500, when the number of hired candidates is less than the number of recruits, the screening results are analyzed, resume filtering rules are determined, and resume information of subsequent applicants is filtered based on the resume filtering rules, including the following steps:

[0070] S510, based on the screening result, determining the resume information filtered out by the recruiter;

[0071] S520, reading sequence data of the filtered resume information based on the sequence data;

[0072] S530, judging the sequence data of the filtered resume information to determine whether there is a sequence with a leading sequence number in the sequence data of the filtered resume information; wherein the sequence with a leading sequence number can be a percentage of the whole or the top number, or can be a sequence with a degree of fit greater than a certain value. For example, the top ten sequences are sequences with a leading sequence number; the sequences with a sequence number in the top 10% are sequences with a leading sequence number; the sequences with a sequence number with a degree of fit greater than 85% are sequences with a leading sequence number.

[0073] S540, if there is resume information with a forward sequence number, the filtered resume information is analyzed to determine the difference between the filtered resume information and the resume information corresponding to the screening result, and the resume information in the screening result is matched as a whole according to the difference to determine whether the resume information in the screening result includes the difference;

[0074] S550, if the number of resumes including the distinguishing point in the screening results is greater than the preset threshold, the distinguishing point is deleted, until the number of resumes including a certain distinguishing point in the screening results is less than the preset threshold, then the distinguishing point is added to the system's filtering rules.

[0075] In this embodiment, the resume information filtered out by the recruiter is judged by the sequence number, so as to determine whether the resume information filtered out by the recruiter is related to the degree of fit. If there is a sequence with a higher sequence number, it indicates that the filtering of the resume information by the recruiter does not follow the degree of fit. Therefore, the filtered resume information is compared and analyzed with the resume information of the screening result, and then the difference points obtained by the comparison analysis are compared with the resume information in the screening result to determine whether the corresponding difference points are the filtering reasons for the recruiter to filter the resume information, and the difference points determined as the filtering reasons are added to the filtering rules to filter the resumes of subsequent applicants, so as to improve the quality of resumes viewed by the recruiter. Among them, the higher the resume quality, the more the resume of the applicant meets the recruitment needs of the recruiter.

[0076] In step S540, if there is resume information with a forward sequence number, the filtered resume information is analyzed to determine the difference between the filtered resume information and the resume information corresponding to the screening result, including the following steps:

[0077] S541, obtaining the fit of the filtered resume information, and matching the resumes in the screening results according to the fit to obtain resume information with the same fit;

[0078] S542, judging the information items of the filtered resume information, obtaining the information item categories of the filtered resume information and the information item data of the corresponding information items; wherein the information items may be name, address, age, school, education experience, work experience, etc.

[0079] S543, performing information item judgment on the resume information with the same degree of fit, and obtaining information item categories and information item data of the corresponding information items of the resume information with the same degree of fit;

[0080] S544, comparing the information item categories and information item data in the filtered resume information with the information item categories and information item data of resume information with the same degree of fit, and determining the information item category differences and information item data differences;

[0081] S545, based on the blockchain data, the data corresponding to the data difference of the corresponding information item is judged to obtain the quality data; wherein, the quality judgment is the quality between the data on the same information item, for example, the information item: work experience, the work experience of applicant A is a, and the work experience of applicant B is b, and for the recruitment position, the advantage of work experience b is greater than work experience a, then it is determined that the advantage of work experience b is greater than work experience a.

[0082] S546, uniformly mark the information item category difference, the information item data difference and the superiority and inferiority data of the corresponding information item data difference as distinguishing points.

[0083] In this embodiment, the filtered resume information is matched with resume information of the same fit to obtain comparative resume information corresponding to the filtered resume information, and then the information item categories and corresponding information item data of the filtered resume information and the comparative resume information are read and compared to determine the information difference between the filtered resume information and the comparative resume information at the same fit, and then the advantages and disadvantages of the existing information difference are judged to further clarify the differences between the difference points, thereby improving the accuracy of the difference points, so that when filtering the resume information according to the difference points, the filtering results meet the filtering standards of the recruiter, thereby improving the quality of the resumes viewed by the recruiter, increasing the probability of employment, and thereby improving the recruitment efficiency.

[0084] In step S600, the resume of the hired personnel is read to obtain the resume information of the hired personnel, and the resume information of the hired personnel is analyzed with the resume information of the unhired personnel to determine the screening rules, and the resume information of the subsequent applicants is screened based on the screening rules, including the following steps:

[0085] S610, judge the number of recruited personnel to determine whether the number of recruited personnel is greater than 1. If the number of recruited personnel is greater than 1, read the resume information of the recruited personnel to obtain the recruitment resume information; when the number of recruited personnel is greater than 1, it indicates that multiple talents have been admitted, and then compare the resume information of the admitted personnel with each other to determine the common points of the admissions, so that the judgment result is more accurate.

[0086] S620, compare the recruitment resume information to determine the common item category and common item data; the common item category is the information item category existing in multiple recruitment resume information, and similarly, the common item data is the data of the corresponding information item.

[0087] S630, matching the resume information of the unhired personnel based on the common item categories and the common item data to determine whether there are common item categories and corresponding common item data in the resume information of the unhired personnel, and marking the common item categories and corresponding common item data that do not exist as screening rules;

[0088] S640, if the number of hired personnel is equal to 1, the resume information of the hired personnel is matched with the resume information of the unhired personnel to obtain the first similarity data; when the number of hired personnel is 1, it means that only one person is hired, and it is impossible to clarify the recruiter's demand for hired personnel by mutual comparison, so by comparing the resume information of the hired personnel with that of the unhired personnel, the information items unique to the hired personnel are analyzed. When the number of hired personnel is 0, it means that no applicant has successfully applied for the job, so there is no reference data, and it is impossible to determine the screening rules.

[0089] S650, based on the built-in selection quantity and the first similarity data, marking the resume information of the unhired personnel with the highest similarity to obtain comparative resume information;

[0090] S660, comparing the resume information of the recruited personnel with the comparative resume information to determine the differences between the resume information of the recruited personnel and the comparative resume information;

[0091] S670, determining the correlation between the information data in the resume information of the recruited personnel and the recruitment position;

[0092] S680, if the difference point is related to the information data in the resume information of the recruited person and the recruitment position, the difference point is marked as a screening rule;

[0093] S690: If the difference point has no relevance between the information data in the resume information of the recruited person and the recruitment position, the difference point is not marked.

[0094] In this embodiment, by judging the number of recruited personnel once, it is determined whether it is necessary to perform screening rule judgment, as well as the judgment method of screening rules in different situations, so that the judgment process is simpler and more effective. When the number of recruited personnel is greater than 1, the resume information of the recruited personnel is compared with each other to evaluate the recruitment items, and then the evaluated recruitment items are matched with the resume information of the unrecruited personnel to determine the information items unique to the recruited personnel; when the number of recruited personnel is 1, the resume information of the recruited personnel is compared with the resume information of the unrecruited personnel with high similarity, and according to the correlation between the comparison result and the recruitment position, it is determined whether the information item unique to the recruited personnel is the recruiter's screening item for the recruited personnel, thereby improving the accuracy of the screening rules, so that the system can accurately screen the resume information of the applicant according to the screening rules, thereby improving the quality of the recruiter's review of the resume.

[0095] In step S200, the resume information of the applicant is obtained, the resume information is matched with the recruitment data, and the compatibility between the applicant and the recruitment information is determined, including the following steps:

[0096] S210, based on the recruitment conditions and recruitment positions in the recruitment data, the rationality of the recruitment conditions in the recruitment data is judged to obtain rationality data; for example, the recruitment position is industrial technical guidance, and the recruitment condition is the ability to speak talk show. By judging the influence relationship between talk show and industrial technical guidance, it is determined that there is no mutual influence relationship between talk show and industrial technical guidance, so it is determined that there is no rationality between the recruitment condition and the recruitment position, that is, the rationality data is 0.

[0097] S220, matching the resume information with the recruitment conditions to obtain the first matching data; for example, if the applicant A mentions in the resume that he can do talk shows, the first matching data is 1, otherwise it is 0. When the recruitment condition is that he can use Word documents and Excel spreadsheets, and the applicant only mentions in the resume that he can use Word documents, the first matching data is 0.5.

[0098] S230, matching the resume information with the recruitment position to obtain second matching data; if the resume information mentions work experience for the recruitment position, the second matching data is determined to be 1; otherwise, if the resume information does not show any industry related to the recruitment position and does not have the skills required for the recruitment position, the second matching data is determined to be 0.

[0099] S240, based on the rationality data, calculate the degree of fit of the first matching data and the second matching data to obtain the degree of fit data. Taking the rationality data as the ratio data, if the recruitment conditions are the same as the recruitment positions, the rationality data is 1, and the degree of fit is z=1*x+0*y; if the rationality is 0.5, the degree of fit is z=0.5*x+0.5*y, where z is the degree of fit, x is the first matching data, and y is the second matching data.

[0100] In this embodiment, when judging the compatibility of the applicant's resume information, the rationality between the recruitment conditions and the recruitment position is determined by judging the compatibility of the recruitment information itself, thereby determining the impact of the applicant's satisfaction with the recruitment position, and then matching the resume information with the recruitment conditions to determine whether the applicant's satisfaction with the recruitment conditions is met. Then, matching the resume information with the recruitment position to determine whether the applicant's own conditions are sufficient for the recruitment position, thereby comprehensively evaluating the applicant's resume information from three aspects, thereby making the final judgment of the compatibility data more accurate and effective, and making the subsequent resume integration, filtering, and screening more accurate.

[0101] In step S220, the resume information is matched with the recruitment conditions to obtain first matching data, including the following steps:

[0102] S221, matching the resume information with the recruitment conditions, determining the extent to which the resume information contains each recruitment condition, and obtaining matching degree data;

[0103] S222, obtaining the importance coefficient of each recruitment condition, and performing corresponding weighting processing on the matching degree data of each recruitment condition based on the importance coefficient to obtain first matching data. The level data of the recruitment condition can be a value set by the recruiter.

[0104] In this embodiment, since the recruiters have different requirements for different recruitment conditions, the importance of each recruitment condition is different during the recruitment. For example, the recruitment conditions include two conditions, P and Q. Now there is a candidate A who meets the recruitment condition P, and the candidate B who meets the recruitment condition Q. Since the importance of the two conditions P and Q is different, if the importance of the condition P is 0.3 and the importance of the condition Q is 0.7, the first matching data of the candidate A is less than the first matching degree of the candidate B, that is, the first matching data of the candidate A is 0.3*1+0.7*0=0.3, and the first matching data of the candidate B is 0.3*0+0.7*1=0.7. Therefore, by matching the resume information with the recruitment conditions, the satisfaction of the resume information for each recruitment condition is determined, and then the satisfaction of the resume information is judged according to the importance of different recruitment conditions, so that the judgment result of the first matching data is more accurate.

[0105] A blockchain-based interview management method further includes the following steps:

[0106] S1, obtain the number of interviews and the number of hired candidates, and calculate the ratio of the number of hired candidates to the number of interviews to determine the hiring rate;

[0107] S2, calculate the ratio of the number of interviews to the number of resumes to determine the interview rate;

[0108] S3, based on the acceptance rate, interview rate and number of resumes, evaluate the number of applicants who have not been interviewed and obtain the expected number of applicants;

[0109] S4, based on the number of recruited personnel and the number of recruitments in the recruitment data, judge the expected number of recruits to determine whether the expected number of recruits meets the number of recruitments;

[0110] S5, if the estimated number of employees to be hired does not meet the number of employees to be recruited, the second matching data of the applicants are counted to determine a second matching data set;

[0111] S6, performing normal analysis on the second matching data set to determine whether the applicant is satisfied with the recruitment position, and reading the first matching data of the corresponding applicant according to the satisfaction status, and judging the first matching data of the corresponding applicant with the recruitment conditions to determine whether the corresponding applicant is satisfied with the recruitment conditions;

[0112] S7, regularizing the recruitment conditions based on the recruitment conditions satisfied by the corresponding applicants to obtain new recruitment conditions, and outputting the new recruitment conditions for the recruiter's reference.

[0113] In this embodiment, the recruitment rate and interview rate of personnel are determined by calculating the ratio of the number of interviews that have been conducted, the number of recruited personnel, and the number of resumes, so as to determine whether the remaining applicants who have not been interviewed can meet the required number of recruited personnel, and thus determine whether it is necessary to relax the recruitment conditions to increase the interview base, thereby ensuring the personnel demand for the recruitment position. When it is determined that it is not met, the second matching data is subjected to normal analysis to determine the recruitment conditions that can be met by most applicants who can meet the job requirements of the recruitment position among the submitted resumes, and then use the recruitment conditions as the recruitment conditions for the next round of recruitment for the reference of recruiters, thereby increasing the number of resume submissions and improving the success rate of admission.

[0114] Based on the description of the above blockchain-based interview management method embodiment, the embodiment of the present invention also discloses a blockchain-based interview management system:

[0115] like Figure 2As shown, a blockchain-based interview management system, by applying the above-mentioned blockchain-based interview management method, includes: a recruitment information analysis module 1, a resume analysis module 2, and a resume regularization module 3;

[0116] Recruitment information analysis module 1, obtains the number of applicants' resumes and determines the number of resumes. When the number of resumes is greater than the built-in screening threshold, the recruitment information is obtained and recruitment data is extracted from the recruitment information to obtain recruitment data;

[0117] Resume analysis module 2 determines the number of recruitments in the recruitment data to determine whether the number of recruitments is greater than 1. If the number of recruitments is 1, the resume information of the applicant is obtained based on the blockchain, and the resume information is matched with the recruitment data to determine the compatibility between the applicant and the recruitment information;

[0118] Resume sorting module 3 sorts the resume information of each applicant based on the degree of fit to obtain sequence data, and displays and outputs the resume information of the applicant based on the sequence data; obtains the screening results of the recruiter on the displayed resumes, arranges the interview time for the screening results according to the sequence data, and sends the arranged interview time to the corresponding applicant; if the number of recruitments is greater than 1, obtains the number of hired personnel, and compares the number of hired personnel with the number of recruitments. When the number of hired personnel is less than the number of recruitments, analyzes the screening results, determines the resume filtering rules, and filters the resume information of subsequent applicants based on the resume filtering rules; reads the resumes of hired personnel to obtain the resume information of hired personnel, analyzes the resume information of hired personnel with the resume information of unhired personnel, determines the screening rules, and filters the resume information of subsequent applicants based on the screening rules.

[0119] Compared with the existing blockchain-based interview management method and system, the present invention improves recruitment efficiency.

[0120] The above are all preferred embodiments of the present application, and the protection scope of the present application is not limited thereto. Therefore, any equivalent changes made according to the structure, shape, and principle of the present application should be included in the protection scope of the present application.

Claims

1. A blockchain-based interview management method, characterized in that: include: Obtain the number of applicants' resumes and judge the number of resumes. When the number of resumes is greater than the built-in screening threshold, obtain the recruitment information and extract the recruitment data from the recruitment information to obtain the recruitment data. Determine the number of vacancies in the recruitment data to determine whether it is greater than 1. If it is 1, obtain the applicant's resume information based on the blockchain, match the resume information with the recruitment data, and determine the compatibility between the applicant and the recruitment information. Sort the resume information of each applicant based on the degree of fit to obtain sequence data, and display and output the resume information of the applicant based on the sequence data; Obtain the recruiter's screening results of the displayed resumes, arrange interview times for the screening results according to the sequence data, and send the arranged interview time to the corresponding applicants; If the number of recruitments is greater than 1, the number of hired personnel is obtained and compared with the number of recruitments. When the number of hired personnel is less than the number of recruitments, the screening results are analyzed, the resume filtering rules are determined, and the resume information of subsequent applicants is filtered based on the resume filtering rules; The resumes of the hired personnel are read to obtain the resume information of the hired personnel, and the resume information of the hired personnel is analyzed with the resume information of the unhired personnel to determine the screening rules, and the resume information of subsequent applicants is screened based on the screening rules.

2. According to the blockchain-based interview management method of claim 1, it is characterized by: When the number of recruited candidates is less than the number of recruits, the screening results are analyzed to determine the resume filtering rules, and the resume information of subsequent applicants is filtered based on the resume filtering rules, specifically: Based on the screening results, determine the resume information filtered out by the recruiter; Based on the sequence data, read the sequence data of the filtered resume information; The sequence data of the filtered resume information is judged to determine whether there is a sequence with a forward sequence number in the sequence data of the filtered resume information; If there is resume information with a forward sequence number, the filtered resume information is analyzed to determine the difference between the filtered resume information and the resume information corresponding to the screening result, and the resume information in the screening result is matched as a whole based on the difference to determine whether the resume information in the screening result includes the difference; If the number of resumes including a distinguishing point in the screening results is greater than a preset threshold, the distinguishing point will be deleted until the number of resumes including a certain distinguishing point in the screening results is less than the preset threshold, then the distinguishing point will be added to the system's filtering rules.

3. According to the blockchain-based interview management method of claim 2, it is characterized by: If there is resume information with a forward sequence number, the filtered resume information is analyzed to determine the difference between the filtered resume information and the resume information corresponding to the screening result, specifically: Obtain the fit of the filtered resume information, and match the resumes in the screening results according to the fit to obtain resume information with the same fit; Performing information item judgment on the filtered resume information to obtain the information item category of the filtered resume information and the information item data of the corresponding information item; Performing information item judgment on the resume information with the same degree of fit, obtaining the information item category of the resume information with the same degree of fit and the information item data of the corresponding information item; Compare the information item categories and information item data in the filtered resume information with the information item categories and information item data of the resume information with the same degree of fit to determine the information item category differences and information item data differences; Based on the blockchain data, the data corresponding to the data difference of the corresponding information item is judged to obtain the quality data; The information item category difference, information item data difference and the superiority and inferiority data of the corresponding information item data difference are uniformly marked as distinguishing points.

4. According to claim 3, a blockchain-based interview management method is characterized in that: The resume of the hired personnel is read to obtain the resume information of the hired personnel, and the resume information of the hired personnel is analyzed with the resume information of the unhired personnel to determine the screening rules, and the resume information of subsequent applicants is screened based on the screening rules, specifically: The number of recruited personnel is judged to determine whether the number of recruited personnel is greater than 1. If the number of recruited personnel is greater than 1, the resume information of the recruited personnel is read to obtain the recruitment resume information; Compare the resume information of the applicants to each other to determine the common item categories and common item data; Based on the common item categories and common item data, the resume information of the unhired personnel is matched to determine whether there are common item categories and corresponding common item data in the resume information of the unhired personnel, and the common item categories and corresponding common item data that do not exist are marked as screening rules; If the number of hired personnel is equal to 1, the resume information of the hired personnel is matched with the resume information of the unhired personnel to obtain the first similarity data; Based on the built-in selection quantity and the first similarity data, the resume information of the unhired personnel with the highest similarity is marked to obtain comparative resume information; Compare the resume information of the recruited personnel with the comparative resume information to determine the differences between the resume information of the recruited personnel and the comparative resume information; Determine the correlation between the information data in the resume of the recruited personnel and the recruitment position; If the difference point is related to the information data in the resume information of the recruited personnel and the recruitment position, the difference point is marked as a screening rule; If the difference point has no relevance between the information data in the resume information of the recruited person and the recruitment position, the difference point will not be marked.

5. According to the blockchain-based interview management method of claim 1, it is characterized by: The obtaining of the applicant's resume information, matching the resume information with the recruitment data, and determining the degree of compatibility between the applicant and the recruitment information, specifically includes: Based on the recruitment conditions and recruitment positions in the recruitment data, the rationality of the recruitment conditions in the recruitment data is judged to obtain rationality data; Match the resume information with the recruitment conditions to obtain the first matching data; Match the resume information with the recruitment position to obtain the second matching data; Based on the rationality data, the first matching data and the second matching data are matched to calculate the matching degree to obtain the matching degree data.

6. According to claim 5, a blockchain-based interview management method is characterized in that: The resume information is matched with the recruitment conditions to obtain the first matching data, which is specifically: Match the resume information with the recruitment conditions to obtain the satisfaction degree of each recruitment condition in the resume information and obtain the satisfaction degree data; Obtain the importance coefficient of each recruitment condition, perform corresponding weighted processing on the satisfaction data of each recruitment condition based on the importance coefficient, and obtain the first matching data.

7. The blockchain-based interview management method according to claim 6 is characterized in that: Also includes: Obtain the number of interviews and the number of hired candidates, and calculate the ratio of the number of hired candidates to the number of interviews to determine the hiring rate; Calculate the ratio of the number of interviews to the number of resumes to determine the interview rate; Based on the acceptance rate, interview rate and number of resumes, the number of candidates who have not been interviewed is evaluated to obtain the expected number of candidates to be accepted. Based on the number of recruits and the number of recruits in the recruitment data, the expected number of recruits is judged to determine whether the expected number of recruits meets the recruitment number; If the estimated number of employees does not meet the number of employees to be recruited, the second matching data of the applicants are counted to determine the second matching data set; Performing normal analysis on the second matching data set to determine the applicant's satisfaction with the recruitment position, and reading the first matching data of the corresponding applicant according to the satisfaction, and judging the read first matching data of the corresponding applicant with the recruitment conditions to determine the recruitment conditions that the read corresponding applicant satisfies; The recruitment conditions are regularized based on the recruitment conditions satisfied by the corresponding applicants to obtain new recruitment conditions, and the new recruitment conditions are output for the reference of the recruiter.

8. An interview management system based on blockchain, characterized in that: The system is used to implement a blockchain-based interview management method as described in any one of claims 1 to 7: comprising: a recruitment information analysis module, a resume analysis module, and a resume regularization module; Recruitment information analysis module, which obtains the number of applicants' resumes and determines the number of resumes. When the number of resumes is greater than the built-in screening threshold, the recruitment information is obtained and recruitment data is extracted from the recruitment information to obtain recruitment data; The resume analysis module determines the number of recruitments in the recruitment data to determine whether the number of recruitments is greater than 1. If the number of recruitments is 1, the resume information of the applicant is obtained based on the blockchain, and the resume information is matched with the recruitment data to determine the compatibility between the applicant and the recruitment information. The resume sorting module sorts the resume information of each applicant based on the degree of fit, obtains sequence data, and displays and outputs the resume information of the applicant based on the sequence data; obtains the screening results of the recruiter on the displayed resumes, arranges the interview time for the screening results according to the sequence data, and sends the arranged interview time to the corresponding applicant; if the number of recruitments is greater than 1, the number of hired personnel is obtained, and the number of hired personnel is compared with the number of recruitments. When the number of hired personnel is less than the number of recruitments, the screening results are analyzed, the resume filtering rules are determined, and the resume information of subsequent applicants is filtered based on the resume filtering rules; the resumes of hired personnel are read to obtain the resume information of hired personnel, and the resume information of hired personnel is analyzed with the resume information of unhired personnel to determine the screening rules, and the resume information of subsequent applicants is filtered based on the screening rules.

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