Business processing method and device, equipment and storage medium

Abstract

The invention provides a business processing method and device, equipment and a storage medium. Relates to the technical field of supplier management. The method comprises the following steps: receiving a service processing request sent by user equipment, wherein the service processing request is used for requesting to determine a target supplier to provide a target level of an application object which accords with an application post; according to the business processing request, performing matching processing on resume information of each application object corresponding to the target supplier and post information of an application post to obtain a first matching degree of the target supplier; determining feature values of a plurality of target features of the target supplier according to the application information of each application object; analyzing and processing the first matching degree and the feature values of the plurality of target features through a preset model to obtain a target weight of the target supplier; and determining a target level of the target supplier corresponding to the target weight. According to the method provided by the invention, the business processing efficiency is improved.

Description

Technical Field

[0001] The present application relates to the technical field of supplier management, and in particular to a business processing method, device, equipment and storage medium. Background Art

[0002] Suppliers can improve the number of interviewers for various positions for the company. The degree of match between interviewers and positions may vary. The supply situation of each supplier can be analyzed to determine the supplier's target level, so as to screen out suppliers who can improve the degree of match with the position.

[0003] In the prior art, the management personnel of an enterprise can obtain the application information of multiple candidates provided by the target supplier, analyze the application information of multiple candidates, and determine the target level of the supplier. However, each supplier may provide a large number of candidates for each position, and the management personnel analyze each supplier, which makes the business processing efficiency low. Summary of the invention

[0004] The present application provides a business processing method, device, equipment and storage medium to solve the technical problem of low efficiency of business processing in the prior art.

[0005] In a first aspect, the present application provides a business processing method, including:

[0006] receiving a service processing request sent by a user device, wherein the service processing request is used to request a target supplier to provide a job candidate that meets a target grade for the job;

[0007] According to the business processing request, matching the resume information of each applicant corresponding to the target supplier with the job information of the job applied for, to obtain a first matching degree of the target supplier;

[0008] Determining characteristic values ​​of a plurality of target characteristics of the target supplier according to the application information of each applicant;

[0009] By using a preset model, the first matching degree and the characteristic values ​​of the plurality of target characteristics are analyzed and processed to obtain a target weight of the target supplier;

[0010] A target level of the target supplier corresponding to the target weight is determined.

[0011] In a possible design, according to the business processing request, the resume information of each applicant corresponding to the target supplier is matched with the job information of the job applied for to obtain a first matching degree of the target supplier, including:

[0012] According to the business processing request, obtain the resume information and applied position of each applicant corresponding to the target supplier;

[0013] Matching the resume information of each applicant with the job information of the job applied for to obtain the job matching degree of each applicant;

[0014] According to the job matching degree of each applicant, a first matching degree of the target supplier is determined.

[0015] In a possible design, for any job applicant, the resume information of the job applicant is matched with the job application position to obtain the job matching degree of the job applicant, including:

[0016] Using a keyword extraction model, keyword extraction processing is performed on the job application to obtain multiple keywords;

[0017] Matching the multiple keywords in the resume information to obtain a matching number;

[0018] The ratio of the matching quantity to the keyword quantity of the multiple keywords is determined as the job matching degree.

[0019] In a possible design, the multiple keywords are matched in the resume information to obtain the number of matches, including:

[0020] Perform similarity matching processing on each keyword in the resume information to obtain a first quantity of each keyword;

[0021] Determine the keywords whose first number is greater than or equal to a preset number as target keywords;

[0022] The number of the target keywords is determined as the matching number.

[0023] In a possible design, for any target feature, determining a feature value of the target feature according to the application information of each applicant includes:

[0024] Acquire at least one characteristic parameter corresponding to the target characteristic according to the application information of each applicant;

[0025] Data processing is performed on the at least one characteristic parameter to obtain a characteristic value of the target characteristic, where the target characteristic includes a first response rate, a response time, a written test pass rate, an entry absence rate, and an interview pass rate.

[0026] In a possible design, the first matching degree and the characteristic values ​​of the plurality of target characteristics are analyzed and processed by a preset model to obtain the target weight of the target supplier, including:

[0027] Performing encoding processing on the first matching degree and the feature values ​​of the plurality of target features to obtain feature codes;

[0028] The characteristic coding is analyzed and processed through the preset model to obtain the target weight.

[0029] In a possible design, determining the target level of the target supplier corresponding to the target weight includes:

[0030] Obtaining an evaluation grade table, wherein the evaluation grade table includes a plurality of weight intervals and an evaluation grade corresponding to each weight interval;

[0031] Determine a target weight interval corresponding to the target weight among the multiple weight intervals;

[0032] The evaluation level corresponding to the target weight interval is determined as the target level.

[0033] In a second aspect, an embodiment of the present application provides a business processing device, including a receiving module, a matching processing module, a first determining module, an analysis processing module, and a second determining module:

[0034] The receiving module is used to receive a business processing request sent by a user device, wherein the business processing request is used to request a target supplier to provide a candidate that meets a target grade for the job;

[0035] The matching processing module is used to match the resume information of each applicant corresponding to the target supplier with the job information of the job applied for according to the business processing request, so as to obtain a first matching degree of the target supplier;

[0036] The first determination module is used to determine the characteristic values ​​of multiple target characteristics of the target supplier according to the application information of each applicant;

[0037] The analysis and processing module is used to analyze and process the first matching degree and the characteristic values ​​of the multiple target characteristics through a preset model to obtain the target weight of the target supplier;

[0038] The second determination module is used to determine the target level of the target supplier corresponding to the target weight.

[0039] In a possible design, the matching processing module is specifically used to:

[0040] According to the business processing request, obtain the resume information and applied position of each applicant corresponding to the target supplier;

[0041] Matching the resume information of each applicant with the job information of the job applied for to obtain the job matching degree of each applicant;

[0042] According to the job matching degree of each applicant, a first matching degree of the target supplier is determined.

[0043] In a possible design, for any job applicant, the matching processing module is specifically used to:

[0044] Using a keyword extraction model, keyword extraction processing is performed on the job application to obtain multiple keywords;

[0045] Matching the multiple keywords in the resume information to obtain a matching number;

[0046] The ratio of the matching quantity to the keyword quantity of the multiple keywords is determined as the job matching degree.

[0047] In a possible design, the matching processing module is specifically used to:

[0048] Perform similarity matching processing on each keyword in the resume information to obtain a first quantity of each keyword;

[0049] Determine the keywords whose first number is greater than or equal to a preset number as target keywords;

[0050] The number of the target keywords is determined as the matching number.

[0051] In a possible design, for any target feature, the first determination module is specifically configured to:

[0052] Acquire at least one characteristic parameter corresponding to the target characteristic according to the application information of each applicant;

[0053] Data processing is performed on the at least one characteristic parameter to obtain a characteristic value of the target characteristic, where the target characteristic includes a first response rate, a response time, a written test pass rate, an entry absence rate, and an interview pass rate.

[0054] In a possible design, the analysis and processing module is specifically used for:

[0055] Performing encoding processing on the first matching degree and the feature values ​​of the plurality of target features to obtain feature codes;

[0056] The characteristic coding is analyzed and processed through the preset model to obtain the target weight.

[0057] In a possible design, the second determining module is specifically configured to:

[0058] Obtaining an evaluation grade table, wherein the evaluation grade table includes a plurality of weight intervals and an evaluation grade corresponding to each weight interval;

[0059] Determine a target weight interval corresponding to the target weight among the multiple weight intervals;

[0060] The evaluation level corresponding to the target weight interval is determined as the target level.

[0061] In a third aspect, an embodiment of the present application provides an electronic device, comprising: at least one processor and a memory; the memory stores computer execution instructions; the at least one processor executes the computer execution instructions stored in the memory, so that the at least one processor executes the business processing method described in the first aspect and various possible designs of the first aspect.

[0062] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, in which computer execution instructions are stored. When a processor executes the computer execution instructions, the business processing method described in the first aspect and various possible designs of the first aspect is implemented.

[0063] In a fifth aspect, an embodiment of the present application provides a computer program product, including a computer program. When the computer program is executed by a processor, it implements the business processing method described in the first aspect and various possible designs of the first aspect.

[0064] The business processing method, device, equipment and storage medium provided in the present application can match the resume information of each applicant corresponding to the target supplier with the job application through a business processing request to obtain a first matching degree, and determine the characteristic values ​​of multiple target characteristics of the target supplier based on the application information of each applicant. The first matching degree and the characteristic values ​​of multiple target characteristics can be analyzed and processed through a preset model to obtain the target weight of the target supplier, and then determine the target level corresponding to the target weight, which can realize automated processing and improve the efficiency of business processing. BRIEF DESCRIPTION OF THE DRAWINGS

[0065] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0066] Figure 1 A schematic diagram of an application scenario provided in an embodiment of the present application;

[0067] Figure 2 A flowchart of a business processing method provided in an embodiment of the present application;

[0068] Figure 3 A flowchart of another business processing method provided in an embodiment of the present application;

[0069] Figure 4 A schematic diagram of a business processing method provided in an embodiment of the present application;

[0070] Figure 5 A schematic diagram of the structure of a service processing device provided in an embodiment of the present application;

[0071] Figure 6 A schematic diagram of the structure of an electronic device provided in an embodiment of the present application.

[0072] The above drawings have shown clear embodiments of the present application, which will be described in more detail later. These drawings and text descriptions are not intended to limit the scope of the present application in any way, but to illustrate the concept of the present application to those skilled in the art by referring to specific embodiments. DETAILED DESCRIPTION

[0073] Exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The implementations described in the following exemplary embodiments do not represent all implementations consistent with the present application. Instead, they are merely examples of devices and methods consistent with some aspects of the present application as detailed in the appended claims.

[0074] Figure 1 A schematic diagram of an application scenario provided by an embodiment of the present application. Figure 1 , may include a user device 101 and a server 102.

[0075] The user device 101 may be a mobile phone, a laptop computer, a desktop computer, a tablet computer, a smart wearable device, etc. The user device 101 may access the business system through application software, a browser, or a small program. The user may select a target supplier in the business system through the user device 101, generate a business processing request corresponding to the target supplier, and the user device 101 may send the business processing request.

[0076] The server 102 may receive the business processing request, and match the resume information of each applicant corresponding to the target supplier with the job position according to the business processing request to obtain a first matching degree of the target supplier. The characteristic values ​​of multiple target features of the target supplier may be determined according to the application information of each applicant, and the first matching degree and the characteristic values ​​of multiple target features may be analyzed and processed through a preset model to obtain a target weight of the target supplier, and a target level of the target supplier corresponding to the target weight may be determined. The server 102 may send the target level of the target supplier to the user device 101.

[0077] In the prior art, the management personnel of an enterprise can obtain the application information of multiple candidates provided by the target supplier, analyze the application information of multiple candidates, and determine the target level of the supplier. However, each supplier may provide a large number of candidates for each position, and the management personnel analyze each supplier, which makes the business processing efficiency low.

[0078] The business processing method provided in the embodiment of the present application can match the resume information of each applicant corresponding to the target supplier with the applied position through a business processing request to obtain a first matching degree, and determine the characteristic values ​​of multiple target characteristics of the target supplier based on the application information of each applicant. The first matching degree and the characteristic values ​​of multiple target characteristics can be analyzed and processed through a preset model to obtain the target weight of the target supplier, and then determine the target level corresponding to the target weight. Automated processing can be achieved, thereby improving the efficiency of business processing.

[0079] The technical solution of the present application and how the technical solution of the present application solves the above-mentioned technical problems are described in detail below with specific embodiments. The following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments. The embodiments of the present application will be described below in conjunction with the accompanying drawings.

[0080] Figure 2 A flowchart of a business processing method provided in an embodiment of the present application. Figure 2 , the method may include:

[0081] S201: Receive a service processing request sent by a user equipment.

[0082] The execution subject of the embodiment of the present application may be a server, or a service processing device arranged in the server. The service processing device may be implemented by software, or by a combination of software and hardware.

[0083] Multiple suppliers may provide candidates for multiple positions in an enterprise, and the execution process of determining the target level for each supplier is the same. The embodiments of the present application are described with respect to any one supplier.

[0084] The target supplier can provide multiple candidates for each job position. For any candidate, the resume information of the candidate can be verified and the candidate can be arranged to take a written test. After passing the written test, the candidate will be interviewed. After passing the interview, an employment notice will be issued, and finally the candidate can start working for the applied position.

[0085] The recruitment system can record the application information of each applicant, which may include the screening of the applicant's resume until failure or employment.

[0086] The business processing request may include an identifier of a target supplier, and the business processing request may be used to request that the target supplier provide applicants that meet the target level of the job position.

[0087] S202: According to the business processing request, the resume information of each applicant corresponding to the target supplier is matched with the job information of the job applied for to obtain a first matching degree of the target supplier.

[0088] The resume information can include the applicant's basic information, major, study subjects, employment experience, etc.

[0089] The job positions that can be applied for include development, operation and maintenance, administration and testing, etc. The job information includes the educational requirements, professional requirements, skill requirements, etc. of the job.

[0090] The first matching degree may be used to indicate the matching degree between the resume information of the applicant provided by the target supplier and the applied position.

[0091] S203: Determine the characteristic values ​​of multiple target characteristics of the target supplier according to the application information of each applicant.

[0092] Target characteristics may include response rate, response time, written test pass rate, absence rate, and interview pass rate.

[0093] For any target feature, at least one feature parameter corresponding to the target feature can be obtained according to the application information of each applicant, and data processing is performed on the at least one feature parameter to obtain a feature value of the target feature.

[0094] If the target feature is response rate, the feature parameters may include application data and the number of vacancies; the number of applications and the number of vacancies corresponding to each job position can be obtained based on the application information of each applicant; for any job position, the ratio of the number of applications to the number of vacancies is determined as the job response rate; the average of the job response rates of each job position is determined as the first response rate of the target supplier.

[0095] Among them, the number of applications can be the number of valid resumes provided by the target suppliers after screening, and the number of recruitments is the minimum supply indicator for the applied positions.

[0096] If the target feature is response time, the feature parameters may include recruitment time and response time; the launch time of each recruitment position may be obtained, and for any recruitment position, the response time of the recruitment position may be determined from the application information of each applicant, and the average time from the launch time to the response time of each recruitment position may be determined as the response time of the target supplier.

[0097] If the target feature is the pass rate of the written test, the feature parameters may include the first number of written tests and the second number of written tests. The first number of applicants who took the written test and the second number of applicants who passed the written test can be determined based on the application information of each applicant, and the ratio of the second number of written tests to the first number of written tests can be determined as the pass rate of the written test.

[0098] If the target feature is the entry absenteeism rate, the feature parameters may include the number of hires and the number of hires; based on the application information of each applicant, the number of hires of applicants to whom the offer notices were issued and the number of applicants who have joined the job can be obtained, the first difference between the number of hires and the number of hires can be determined, and the ratio of the first difference to the number of hires can be determined as the entry absenteeism rate.

[0099] If the target feature is the interview pass rate, the feature parameters may include the number of first interviews and the number of second interviews. The number of first interviews of candidates who participated in the interview and the number of second interviews who passed the interview can be determined based on the application information of each candidate, and the ratio of the second interview number to the first interview number can be determined as the interview pass rate.

[0100] Target features may also include written test absence rate, interview absence rate, etc.

[0101] By quantifying the characteristic information of target suppliers through target characteristics, standardized management of suppliers can be achieved and the accuracy of supplier analysis can be improved.

[0102] S204: Analyze and process the first matching degree and the characteristic values ​​of multiple target characteristics through a preset model to obtain a target weight of the target supplier.

[0103] The initial model can be trained with multiple sample information to obtain a preset model. The initial model can be a neural network model, a Bayesian network, or an association rule model.

[0104] By determining the target weight based on the first matching degree and the feature values ​​of multiple target features, the accuracy of determining the target weight can be improved.

[0105] S205. Determine the target level of the target supplier corresponding to the target weight.

[0106] An evaluation grade table may be obtained, and a target weight interval corresponding to a target weight may be determined among multiple weight intervals; and an evaluation grade corresponding to the target weight interval may be determined as a target grade.

[0107] Target levels for multiple target suppliers may be determined, and target suppliers with lower target levels may be eliminated, or target suppliers with lower target levels may be warned.

[0108] The business processing method provided in the embodiment of the present application can match the resume information of each applicant corresponding to the target supplier with the applied position through a business processing request to obtain a first matching degree, and determine the characteristic values ​​of multiple target characteristics of the target supplier based on the application information of each applicant. The first matching degree and the characteristic values ​​of multiple target characteristics can be analyzed and processed through a preset model to obtain the target weight of the target supplier, and then determine the target level corresponding to the target weight. This can realize automated processing of the information of multiple applicants, obtain the target level of the target supplier, and improve the efficiency of business processing.

[0109] Based on the above embodiments, Figure 3 , further illustrating another business processing method provided by this application.

[0110] Figure 3 A flowchart of another business processing method provided in an embodiment of the present application. Figure 3 , the method may include:

[0111] S301: Receive a service processing request sent by a user equipment.

[0112] The execution process of S301 can refer to the execution process of S201, which will not be repeated here.

[0113] S302 obtains resume information and applied positions of each applicant corresponding to the target supplier according to the business processing request.

[0114] The resume information and job position of each applicant corresponding to the target supplier can be obtained in the database.

[0115] S303: For any applicant, a keyword extraction model is used to extract keywords from the job to obtain multiple keywords.

[0116] The keyword extraction model can be a bidirectional encoder representation from Transformer (BERT) model, a related (Word2vec) model for generating word vectors, etc.

[0117] In some embodiments, keywords may also be determined by using the statistical method TF-IDF (Term Frequency-Inverse Document Frequency).

[0118] S304: Match multiple keywords in the resume information to obtain the number of matches.

[0119] Each keyword can be processed for similarity matching in the resume information to obtain a first quantity of each keyword, and keywords whose first quantity is greater than or equal to a preset quantity are determined as target keywords; and the quantity of target keywords is determined as the matching quantity.

[0120] Since keywords have many synonyms and semantically similar words, similar matching processing can be used when matching resume information. For example, latent semantic analysis (LSA) can be used.

[0121] For example, assuming there are 5 keywords in total, namely keywords 1-5, assuming the first quantity of keyword 1 is 2, the first quantity of keyword 2 is 1, the first quantity of keyword 3 is 1, the first quantity of keyword 4 is 0, and the first quantity of keyword 5 is 3. Assuming the preset quantity is 2, the target keywords can be keyword 1 and keyword 5, then the matching quantity can be determined to be 2.

[0122] S305: Determine the ratio of the matching quantity to the keyword quantity of the multiple keywords as the job matching degree.

[0123] For example, assuming the number of matches is 2 and the number of keywords is 5, it can be determined that the job matching degree of the target supplier is 0.4.

[0124] S306. Determine the first matching degree of the target supplier according to the job matching degree of each applicant.

[0125] In some embodiments, the average of the job matching degrees of each applicant may be determined as the first matching degree of the target supplier.

[0126] In some embodiments, the median of the job matching degree of each applicant may be determined as the first matching degree of the target supplier.

[0127] S307: Determine the characteristic values ​​of multiple target characteristics of the target supplier according to the application information of each applicant.

[0128] The execution process of S307 can refer to the execution process of S203, which will not be repeated here.

[0129] S308 , encoding the first matching degree and the feature values ​​of the multiple target features to obtain feature codes.

[0130] Encoding methods may include binary encoding, ASCII encoding, and Unicode encoding.

[0131] A preset encoding method may be obtained, and the first matching degree and the feature values ​​of the plurality of target features may be encoded to obtain a feature code.

[0132] S309: Analyze and process the feature coding through a preset model to obtain a target weight.

[0133] The feature encoding is used as a preset model input to obtain a preset model output, and the preset model output is determined as a target weight.

[0134] S310, obtaining an evaluation rating table.

[0135] The evaluation grade table may include multiple weight intervals and an evaluation grade corresponding to each weight interval.

[0136] For example, the evaluation grade table has three weight intervals, namely weight interval 1, weight interval 2 and weight interval 3. The evaluation grade corresponding to each weight interval can be shown in Table 1.

[0137] Table 1

[0138] Weight range Rating Weight interval 1 Rating 1 Weight interval 2 Rating 2 Weight interval 3 Rating 3

[0139] S311. Determine a target weight interval corresponding to a target weight among multiple weight intervals.

[0140] For example, assuming that the evaluation grade table can be as shown in Table 1, there are 3 weight intervals, namely weight interval 1, weight interval 2 and weight interval 3. Assuming that the target weight is within weight interval 2, the target weight interval can be determined to be weight interval 2.

[0141] S312. Determine the evaluation level corresponding to the target weight interval as the target level.

[0142] For example, assuming that the evaluation grade table can be as shown in Table 1, and assuming that the target weight interval is weight interval 2, the target grade can be determined to be rating grade 2.

[0143] The business processing method provided in the embodiment of the present application can match the resume information of each applicant corresponding to the target supplier with the applied position through a business processing request to obtain a first matching degree, and determine the characteristic values ​​of multiple target characteristics of the target supplier based on the application information of each applicant. The first matching degree and the characteristic values ​​of multiple target characteristics can be analyzed and processed through a preset model to obtain the target weight of the target supplier, and then determine the target level corresponding to the target weight. This can realize automated processing of the information of multiple applicants, obtain the target level of the target supplier, and improve the efficiency of business processing.

[0144] Figure 4 This is a schematic diagram of a business processing method provided in an embodiment of the present application. Figure 4 After receiving the business processing request, the resume information and job position of each applicant corresponding to the target supplier can be obtained. For any applicant, the keyword extraction model can be used to extract keywords for the job position to obtain multiple keywords, and the multiple keywords can be matched in the resume information to obtain the matching number; the ratio of the matching number to the keyword number of the multiple keywords is determined as the job matching degree. The first matching degree of the target supplier can be determined based on the job matching degree of each applicant.

[0145] For any target feature, at least one feature parameter corresponding to the target feature can be obtained based on the application information of each applicant, and data processing is performed on at least one feature parameter to obtain a feature value of the target feature. The target features include first response rate, response time, written test pass rate, employment absence rate and interview pass rate.

[0146] The first matching degree and the characteristic values ​​of the plurality of target characteristics may be encoded to obtain a characteristic code, and the characteristic code may be analyzed and processed through a preset model to obtain a target weight. Among the plurality of weight intervals in the evaluation grade table, a target weight interval corresponding to the target weight is determined; and the evaluation grade corresponding to the target weight interval is determined as the target grade.

[0147] Figure 5 This is a schematic diagram of the structure of a service processing device provided in an embodiment of the present application. Figure 5 The service processing device may include a receiving module 11, a matching processing module 12, a first determining module 13, an analyzing processing module 14 and a second determining module 15:

[0148] The receiving module 11 is used to receive a business processing request sent by a user device, where the business processing request is used to request a target supplier to provide a candidate that meets the target level of the job;

[0149] The matching processing module 12 is used to match the resume information of each applicant corresponding to the target supplier with the job information of the job applied for according to the business processing request, and obtain a first matching degree of the target supplier;

[0150] The first determination module 13 is used to determine the characteristic values ​​of multiple target characteristics of the target supplier according to the application information of each applicant;

[0151] The analysis and processing module 14 is used to analyze and process the first matching degree and the characteristic values ​​of multiple target characteristics through a preset model to obtain the target weight of the target supplier;

[0152] The second determination module 15 is used to determine the target level of the target supplier corresponding to the target weight.

[0153] The business processing device provided in the embodiment of the present application can execute the technical solution shown in the above method embodiment, and its implementation principle and beneficial effects are similar, which will not be repeated here.

[0154] In a possible design, the matching processing module 12 is specifically used for:

[0155] According to the business processing request, obtain the resume information and job position of each applicant corresponding to the target supplier;

[0156] Matching the resume information of each applicant with the job information of the job to obtain the job matching degree of each applicant;

[0157] Determine the first matching degree of the target supplier based on the job matching degree of each applicant.

[0158] In a possible design, for any job applicant, the matching processing module 12 is specifically used to:

[0159] Through the keyword extraction model, the keywords of the job positions are extracted and processed to obtain multiple keywords;

[0160] Match multiple keywords in the resume information to obtain the number of matches;

[0161] The ratio of the number of matches to the number of keywords of multiple keywords is determined as the job matching degree.

[0162] In a possible design, the matching processing module 12 is specifically used for:

[0163] Perform similarity matching processing on each keyword in the resume information to obtain the first quantity of each keyword;

[0164] Determine keywords with a first quantity greater than or equal to a preset quantity as target keywords;

[0165] The number of target keywords is determined as the matching number.

[0166] In a possible design, for any target feature, the first determination module 13 is specifically used to:

[0167] According to the application information of each applicant, at least one feature parameter corresponding to the target feature is obtained;

[0168] Data processing is performed on at least one characteristic parameter to obtain a characteristic value of a target characteristic, where the target characteristics include a first response rate, a response time, a written test pass rate, an entry absence rate, and an interview pass rate.

[0169] In a possible design, the analysis and processing module 14 is specifically used for:

[0170] Encoding the first matching degree and feature values ​​of multiple target features to obtain feature codes;

[0171] Through the preset model, the feature coding is analyzed and processed to obtain the target weight.

[0172] In a possible design, the second determining module 15 is specifically configured to:

[0173] Obtaining an evaluation grade table, the evaluation grade table including a plurality of weight intervals and an evaluation grade corresponding to each weight interval;

[0174] Determine a target weight interval corresponding to the target weight among multiple weight intervals;

[0175] The evaluation level corresponding to the target weight interval is determined as the target level.

[0176] The business processing device provided in the embodiment of the present application can execute the technical solution shown in the above method embodiment, and its implementation principle and beneficial effects are similar, which will not be repeated here.

[0177] Figure 6 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present application. Figure 6 The electronic device 20 may include a processor 21 and a memory 22. Exemplarily, the processor 21 and the memory 22 are interconnected via a bus 23.

[0178] The memory 22 stores computer executable instructions;

[0179] The processor 21 executes the computer execution instructions stored in the memory 22, so that the processor 21 executes the service processing method shown in the above method embodiment.

[0180] Accordingly, an embodiment of the present application provides a computer-readable storage medium, in which computer-executable instructions are stored. When the computer-executable instructions are executed by a processor, they are used to implement the business processing method of the above method embodiment.

[0181] Accordingly, an embodiment of the present application may also provide a computer program product, including a computer program, which, when executed by a processor, can implement the business processing method shown in the above method embodiment.

[0182] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0183] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0184] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0185] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0186] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0187] The memory may include non-permanent storage in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. The memory is an example of a computer-readable medium.

[0188] Computer readable media include permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. Information can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic tape disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include temporary computer readable media (transitory media), such as modulated data signals and carrier waves.

[0189] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0190] The above are only embodiments of the present application and are not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included within the scope of the claims of the present application.

Claims

1. A business processing method, characterized in that: include: receiving a service processing request sent by a user device, wherein the service processing request is used to request a target supplier to provide a job candidate that meets a target grade for the job; According to the business processing request, matching the resume information of each applicant corresponding to the target supplier with the job information of the job applied for, to obtain a first matching degree of the target supplier; Determining characteristic values ​​of a plurality of target characteristics of the target supplier according to the application information of each applicant; By using a preset model, the first matching degree and the characteristic values ​​of the plurality of target characteristics are analyzed and processed to obtain a target weight of the target supplier; A target level of the target supplier corresponding to the target weight is determined.

2. The method according to claim 1, characterized in that: According to the business processing request, the resume information of each applicant corresponding to the target supplier is matched with the job information of the job applied for to obtain a first matching degree of the target supplier, including: According to the business processing request, obtain the resume information and applied position of each applicant corresponding to the target supplier; Matching the resume information of each applicant with the job information of the job applied for to obtain the job matching degree of each applicant; According to the job matching degree of each applicant, a first matching degree of the target supplier is determined.

3. The method according to claim 2, characterized in that For any candidate, the resume information of the candidate is matched with the job position to obtain the job matching degree of the candidate, including: Using a keyword extraction model, keyword extraction processing is performed on the job application to obtain multiple keywords; Matching the multiple keywords in the resume information to obtain a matching number; The ratio of the matching quantity to the keyword quantity of the multiple keywords is determined as the job matching degree.

4. The method according to claim 3, characterized in that The multiple keywords are matched in the resume information to obtain the number of matches, including: Perform similarity matching processing on each keyword in the resume information to obtain a first quantity of each keyword; Determine the keywords whose first number is greater than or equal to a preset number as target keywords; The number of the target keywords is determined as the matching number.

5. The method according to claims 1-4, characterized in that: For any target feature; Determining the characteristic value of the target characteristic according to the application information of each applicant includes: Acquire at least one characteristic parameter corresponding to the target characteristic according to the application information of each applicant; Data processing is performed on the at least one characteristic parameter to obtain a characteristic value of the target characteristic, where the target characteristic includes a first response rate, a response time, a written test pass rate, an entry absence rate, and an interview pass rate.

6. The method according to any one of claims 1 to 5, characterized in that: By using a preset model, the first matching degree and the characteristic values ​​of the plurality of target characteristics are analyzed and processed to obtain the target weight of the target supplier, including: Performing encoding processing on the first matching degree and the feature values ​​of the plurality of target features to obtain feature codes; The characteristic coding is analyzed and processed through the preset model to obtain the target weight.

7. The method according to any one of claims 1 to 6, characterized in that: Determining a target level of the target supplier corresponding to the target weight includes: Obtaining an evaluation grade table, wherein the evaluation grade table includes a plurality of weight intervals and an evaluation grade corresponding to each weight interval; Determine a target weight interval corresponding to the target weight among the multiple weight intervals; The evaluation level corresponding to the target weight interval is determined as the target level.

8. A service processing device, characterized in that: It includes a receiving module, a matching processing module, a first determining module, an analyzing processing module and a second determining module: The receiving module is used to receive a business processing request sent by a user device, wherein the business processing request is used to request a target supplier to provide a candidate that meets a target grade for the job; The matching processing module is used to match the resume information of each applicant corresponding to the target supplier with the job information of the job applied for according to the business processing request, so as to obtain a first matching degree of the target supplier; The first determination module is used to determine the characteristic values ​​of multiple target characteristics of the target supplier according to the application information of each applicant; The analysis and processing module is used to analyze and process the first matching degree and the characteristic values ​​of the multiple target characteristics through a preset model to obtain the target weight of the target supplier; The second determination module is used to determine the target level of the target supplier corresponding to the target weight.

9. An electronic device, characterized in that: include: Memory and processor, The memory stores computer-executable instructions; The processor executes the computer-executable instructions stored in the memory, so that the processor executes the business processing method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer-executable instructions, which are used to implement the business processing method according to any one of claims 1 to 7 when executed by a processor.

11. A computer program product, comprising a computer program, wherein when the computer program is executed by a processor, the service processing method according to any one of claims 1 to 7 is implemented.

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