Method and device for recommending job seeker resumes based on function categories and electronic equipment

Abstract

The invention discloses a method and device for recommending job seeker resumes based on function categories and electronic equipment. The method comprises the steps of obtaining resume data of job seekers; according to the job-hunting intention, determining a function category to which the job-hunting position belongs, and according to the function category, constructing a label calculation strategy; acquiring position description information published by a recruiter to obtain a query condition; screening the resume data of the job seeker according to the query condition to obtain a candidate resume data list matched with the query condition; assigning a score to each piece of dimension information in each piece of candidate resume data according to a constructed label calculation strategy so as to obtain a weight score of each piece of dimension information; calculating the weight score of each piece of dimension information to obtain a total weight score; screening the candidate resume data list according to the total weight score to obtain a recommended resume data list; triggering a display card according to the recommended resume data list; the total weight score of the same job seeker resume data is different under different function categories.

Description

Technical Field

[0001] The present application relates to the technical field of computers and the Internet, and more particularly to a method, device and electronic device for recommending job seekers' resumes based on job categories. Background Art

[0002] With the increasing demand for recruitment and job hunting, more and more companies and job seekers are recruiting through Internet recruitment platforms. Since the recruitment needs of recruitment companies are different, job seekers' job expectations are also different. As a result, recruitment companies find it difficult to find suitable candidates among many job seekers, and similarly, job seekers also find it difficult to find their ideal positions among many recruitment companies. This phenomenon often occurs when the recruitment platform simply matches the job seeker's resume with the recruitment needs and then recommends the job seeker's resume, which will result in low accuracy in the recommendation of job seeker's resume. Summary of the invention

[0003] The purpose of this application is to provide a method, device and electronic device for recommending job seekers' resumes based on job categories.

[0004] The present application embodiment provides a method for recommending job seekers' resumes based on job categories, including:

[0005] Obtaining resume data of job seekers; wherein the resume data of job seekers includes one or more of the following dimensional information: basic information, education experience, work experience, work skills and job-seeking intention of job seekers;

[0006] Determine the functional category of the job to which the job is applied based on the job application intention, and construct a label calculation strategy based on the functional category; wherein the label calculation strategy includes setting different weight scores for the same dimension information in the job applicant's resume data under different functional categories;

[0007] Obtain job description information posted by recruiters to obtain query conditions;

[0008] Screening the resume data of job seekers according to the query conditions to obtain a list of candidate resume data matching the query conditions;

[0009] According to the established label calculation strategy, each dimension of information in each candidate's resume data is scored to obtain the weighted score of each dimension of information;

[0010] Calculate the weighted scores of each dimension information to obtain the total weighted score;

[0011] Filter the candidate resume data list according to the weighted total score to obtain a recommended resume data list;

[0012] A display card is triggered according to the recommended resume data list; wherein, the display card is used to display the basic information of the job seeker and the weighted total score of the job seeker. The weighted total score of the resume data of the same job seeker is different under different functional categories, so that the weighted total score of the resume data of the same job seeker changes dynamically according to different positions.

[0013] Furthermore, the method further comprises:

[0014] Generate a number of label information corresponding to the education experience, work experience, and work skills in the resume data of the job seeker according to a preset generation strategy to obtain target resume data; wherein the target resume data is the recommended resume data that has been marked with label information;

[0015] The display card is triggered according to the target resume data, and the display card is also used to display tag information and a link to the resume data of the job seeker.

[0016] Furthermore, determining the job category of the job to be applied for according to the job-seeking intention and constructing a label calculation strategy according to the job category includes:

[0017] There are multiple first-level functional categories for functional categories, including blue-collar positions and white-collar positions;

[0018] For blue-collar positions, education experience is not included in the scoring, and age, work experience and work skills are given different weights according to their respective attribute values;

[0019] There are several second-level functional categories under the white-collar category, including technical positions and management positions;

[0020] For technical positions, the weight of age setting is set to be smaller than the weight of education experience, work experience and work skills setting;

[0021] For management positions, the weight score set for education experience is set lower than the weight scores set for age, work experience, and work skills.

[0022] Furthermore, the query conditions include one or more of the following: skill information, job function category and industry.

[0023] Furthermore, the method further comprises:

[0024] In the recommended resume data list, the recommended resume data is re-sorted according to a preset sorting and scattering strategy to generate different sorting positions.

[0025] Furthermore, the label information includes any one of the following: a prestigious university, a senior industry professional, rich experience, a highly educated talent, or an excellent resume.

[0026] Further, triggering the display card according to the target resume data includes:

[0027] Determine whether to mark the target resume data with label information in the display card according to the functional category; wherein, for the dimension information not involved in the scoring, the corresponding label information is not displayed in the display card; and / or,

[0028] Sort multiple tab information in a display card by functional category.

[0029] The embodiment of the present application provides a device for recommending job seekers' resumes based on job categories, including:

[0030] The first acquisition module is used to acquire the resume data of the job seeker; wherein the resume data of the job seeker includes one or more of the following dimensional information: basic information, education experience, work experience, work skills and job-seeking intention of the job seeker;

[0031] A construction module is used to determine the functional category of the job to be applied for according to the job-seeking intention, and to construct a label calculation strategy according to the functional category; wherein the label calculation strategy includes setting different weight scores for the same dimension information in the resume data of the job seeker under different functional categories;

[0032] The second acquisition module is used to acquire the job description information posted by the recruiter to obtain the query conditions;

[0033] A screening module is used to screen the resume data of job seekers according to the query conditions to obtain a list of candidate resume data that matches the query conditions;

[0034] The scoring module is used to score each dimension of information in each candidate resume data according to the established label calculation strategy to obtain the weighted score of each dimension of information;

[0035] A calculation module is used to calculate the weight score of each dimension information to obtain the total weight score;

[0036] The recommendation module is used to filter the candidate resume data list according to the weighted total score to obtain a recommended resume data list;

[0037] A display module is used to trigger a display card based on a recommended resume data list; wherein, the display card is used to display the basic information of the job seeker and the weighted total score of the job seeker, and the weighted total score of the resume data of the same job seeker is different under different functional categories, so that the weighted total score of the resume data of the same job seeker changes dynamically according to different positions.

[0038] An embodiment of the present application provides an electronic device, which includes a processor and a memory storing computer program instructions; when the processor executes the computer program instructions, the steps of the method described above are implemented.

[0039] An embodiment of the present application provides a computer-readable storage medium, on which computer program instructions are stored. When the computer program instructions are executed by a processor, the steps of the method described above are implemented.

[0040] An embodiment of the present application provides a computer program product, wherein the computer program product includes computer program instructions, and when the computer program instructions are executed by a processor, the steps of the method described above are implemented.

[0041] The above technical solution of the present application has the following beneficial technical effects:

[0042] In the embodiment of the present application, by constructing a label calculation strategy, the weight scores assigned to the same dimension information in the job seeker's resume data under different functional categories can be set to be different, so as to achieve different total weight scores for the same job seeker's resume data under different functional categories, so that the total weight score of the same job seeker's resume data can change dynamically according to different positions; when the same job seeker submits resumes to different positions, due to the different functional categories to which different positions belong, the weight scores assigned to each dimension information in the job seeker's resume data are different, and the total weight scores calculated for each weight score are also different. For different positions distributed by each corporate recruiter, the total weight score of the displayed resume data of the same job seeker changes dynamically, and is correspondingly displayed to each corporate recruiter who posts different positions through a display card, and the recommended resume data can be screened out through the total weight score. In this way, quantitative calculation of the job seeker's resume data can improve the accuracy of job seeker resume recommendations, thereby improving recruitment efficiency; it can avoid reducing the exposure opportunities of job seekers' resumes due to a certain preset condition not meeting recruitment requirements. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] In order to more clearly illustrate the technical solution of the embodiments of the present application, the following briefly introduces the drawings in the embodiments of the present application.

[0044] Figure 1 It is a schematic diagram of the system architecture of an embodiment of the present application.

[0045] Figure 2 It is a flowchart of a method for recommending job seekers' resumes based on job category in an embodiment of the present application.

[0046] Figure 3 It is a schematic diagram of a processing process for constructing a labeling system according to an embodiment of the present application.

[0047] Figure 4 It is a structural schematic diagram of a display card triggered by resume data in an embodiment of the present application.

[0048] Figure 5 It is a structural block diagram of a device for recommending job seekers' resumes based on job categories according to an embodiment of the present application.

[0049] Figure 6 It is a schematic diagram of an electronic device used to implement a method for recommending job seekers' resumes based on job categories in an embodiment of the present application. DETAILED DESCRIPTION

[0050] The principles and spirit of the present application will be described below with reference to several exemplary embodiments. It should be understood that the purpose of providing these embodiments is to make the principles and spirit of the present application clearer and more thorough, so that those skilled in the art can better understand and implement the principles and spirit of the present application. The exemplary embodiments provided herein are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments herein, all other embodiments obtained by ordinary technicians of the art without creative work are within the scope of protection of this application.

[0051] Embodiments of the present application relate to terminal devices and / or servers. Those skilled in the art will appreciate that the embodiments of the present application may be implemented as a system, apparatus, device, method, computer-readable storage medium, or computer program product. Therefore, the present disclosure may be specifically implemented in at least one of the following forms: complete hardware, complete software, or a combination of hardware and software. According to the embodiments of the present application, the present application seeks protection for a method, apparatus, electronic device, computer-readable storage medium, and computer program product for recommending job seeker resumes based on job category. Figure 1 A schematic diagram of a system architecture of an embodiment of the present application is shown. Figure 1As shown, the system includes a terminal device 102 and a server 104. Among them, the terminal device 102 may include at least one of the following: a smart phone, a tablet computer, a laptop computer, a desktop computer, a smart TV, various wearable devices, an augmented reality AR device, a virtual reality VR device, etc. A client can be installed on the terminal device 102. For example, the client can be a client that specifically performs a specific function (such as an application app), or a client with multiple application applets (different functions) embedded in it, or a client logged in through a browser. The user can operate on the terminal device 102. For example, the user can open the client installed on the terminal device 102 and input instructions through the client operation, or the user can open the browser installed on the terminal device 102 and input instructions through the browser operation. After the terminal device 102 receives the instruction input by the user, the request information containing the instruction is sent to the server 104. After receiving the request information, the server 104 performs corresponding processing and then returns the processing result information to the terminal device 102. The user instruction is completed through a series of data processing and information interaction.

[0052] In this document, terms such as first, second, third, etc. are only used to distinguish one entity (or operation) from another entity (or operation), but not to require or imply any order or relationship between these entities (or operations).

[0053] Figure 2 A flow chart of a method for recommending job seekers' resumes based on job categories in an embodiment of the present application is shown, and the method includes the following steps:

[0054] S110: Obtaining resume data of a job seeker; wherein the resume data of a job seeker includes one or more of the following dimensional information: basic information, educational background, work experience, work skills and job-seeking intention of the job seeker.

[0055] Specifically, the job seeker can input the basic information of the job seeker according to the template of the resume text on the terminal device 102, and after filling in and submitting successfully, it can be sent to the server 104, and the server 104 will parse and store the resume data of the job seeker in the talent database; or, after the job seeker browses the job description of the job to be recruited posted by the recruiter on the terminal device 102, the job seeker can click the submit resume button for the job that meets the job search intention to send the resume to the recruiter; therefore, by obtaining the resume sent by each job seeker on the recruitment platform after browsing different job descriptions on the terminal device 102, the server 104 will parse and store the resume data of the job seeker in the talent database, so that the resume data of the job seeker can be obtained from the talent database. Among them, the resume data of the job seeker may include one or more of the following dimensional information: the basic information, education experience, work experience, work skills and job search intention of the job seeker; the basic information of the job seeker may include the name, age, city of residence, etc. of the job seeker; the job search intention may include the job search position, industry, area where the work address is located, etc.

[0056] S120: Determine the functional category of the job to be applied for based on the job-seeking intention, and construct a label calculation strategy based on the functional category; wherein the label calculation strategy includes setting different weight scores for the same dimension information in the job seeker's resume data under different functional categories.

[0057] Specifically, in the recruitment field, functional categories are the classification of positions. Functional categories can be used to classify positions according to the nature of the job, scope of responsibilities, and required professional skills. For example, "sales representative" and "sales director" can be classified as management positions. Therefore, different functional categories have different requirements for job seekers' educational experience, work experience, work skills, etc. When evaluating job seekers, the importance of the same ability or experience in different positions may vary. Therefore, when assigning points to each dimension of information in the job seeker's resume data, the weight scores assigned under different functional categories can be set to be different.

[0058] S130: Obtaining the job description information posted by the recruiter to obtain the query conditions.

[0059] Specifically, corporate recruiters can post job description information on the terminal device 102 to obtain resume data of job seekers that meet the recruitment requirements; the job description may include job information such as job ID, functional category, industry, working city, salary range and benefits, and the query conditions may include one or more of the following: skill information, functional category and industry to which the job belongs.

[0060] S140: Screening the resume data of job seekers according to the query conditions to obtain a list of candidate resume data matching the query conditions.

[0061] Specifically, by preliminarily screening the resume data of numerous job seekers according to the query conditions, a list of candidate resume data matching the recruitment requirements can be obtained, which can improve recruitment efficiency.

[0062] S150: Assign scores to each dimension of information in each candidate resume data according to the constructed label calculation strategy to obtain a weight score for each dimension of information.

[0063] Specifically, for example, "sales representative" can be classified as a management position. The label calculation strategy constructed for this type of management position includes work experience as the main calculation dimension and professional skills. Educational experience is not the main calculation indicator, so the weight scores assigned to work experience, professional skills and educational experience are different; among them, for example, the weight score of work experience can be set to 20 points at most, the weight score of professional skills can be set to 15 points at most, and the weight score of educational experience can be set to 10 points at most.

[0064] S160: Calculate the weight score of each dimension information to obtain the total weight score.

[0065] S170: Filter the candidate resume data list according to the weighted total score to obtain a recommended resume data list.

[0066] Specifically, the weighted total score of the resume data of each job seeker in the candidate resume data list is sorted from large to small, and the resume data of multiple job seekers with the highest ranking can be screened out as recommended resume data, or the resume data of job seekers whose weighted total score reaches a set threshold can be used as recommended resume data. In this way, the recommended resume data is more in line with recruitment needs and can improve recruitment efficiency.

[0067] S180: triggering a display card according to the recommended resume data list; wherein, the display card is used to display the basic information of the job seeker and the weighted total score of the job seeker, and the weighted total score of the resume data of the same job seeker is different under different functional categories, so that the weighted total score of the resume data of the same job seeker changes dynamically according to different positions.

[0068] In the embodiment of the present application, by constructing a label calculation strategy, the weight scores assigned to the same dimension information in the job seeker's resume data under different functional categories can be set to be different, so as to achieve different total weight scores for the same job seeker's resume data under different functional categories, so that the total weight score of the same job seeker's resume data can change dynamically according to different positions; when the same job seeker submits resumes to different positions, due to the different functional categories to which different positions belong, the weight scores assigned to each dimension information in the job seeker's resume data are different, and the total weight scores calculated for each weight score are also different. For different positions distributed by each corporate recruiter, the total weight score of the displayed resume data of the same job seeker changes dynamically, and is correspondingly displayed to each corporate recruiter who posts different positions through a display card, and the recommended resume data can be screened out through the total weight score. In this way, quantitative calculation of the job seeker's resume data can improve the accuracy of job seeker resume recommendations, thereby improving recruitment efficiency; it can avoid reducing the exposure opportunities of job seekers' resumes due to a certain preset condition not meeting recruitment requirements. Especially for many very outstanding senior professionals with strong professional knowledge, when choosing re-employment, they can choose more positions in their job-seeking intentions. By quantitatively evaluating the information of various dimensions in their resume data under different functional categories, there will be more opportunities to show the resumes of senior professionals to corporate recruiters, so as to tap the competitiveness of senior professionals and increase the exposure opportunities of their resumes.

[0069] Currently, many very excellent and professionally qualified senior professionals encounter various bottlenecks in their re-employment choices, which results in few opportunities for senior professionals to expose their resumes. In view of this, the method may further include the following steps:

[0070] S191: Generate a number of label information corresponding to the education experience, work experience, and work skills in the resume data of the job seeker according to a preset generation strategy to obtain target resume data; wherein the target resume data is the recommended resume data marked with label information;

[0071] S192: Triggering the display card according to the target resume data; wherein the display card is also used to display tag information and a link to the resume data of the job seeker.

[0072] In the embodiment of the present application, a label system can be constructed based on the resume data of job seekers stored in the talent database, such as Figure 3As shown, by using the preset generation strategy to generate several label information corresponding to the education experience, work experience, work skills, etc. in the resume data of the job seeker, for example, if the working years are 5 years or more than 10 years, the label information can be generated as "experienced"; for the job level of director or senior director in the work skills, the label information can be generated as "industry veteran"; by displaying the label information of the job seeker on the display card, the advantages of the job seeker in the recommended resume data can be more clearly seen by the company's recruiters, which can improve the recruitment efficiency; especially for senior people who may have more label information, the corresponding label information can be displayed on the positions under different functional categories to improve the exposure opportunities of the resumes of senior people. Correspondingly, the education experience, work experience, work skills, etc. in the resume data of the job seeker can be assigned weight scores according to different functional categories.

[0073] In an exemplary embodiment, Figure 3 As shown, the label information includes any of the following: famous university, senior industry personnel, experienced, highly educated talent or excellent resume. Among them, a database of famous universities can be constructed. For example, the school codes of some key universities can be added to the database of famous universities, and the job seeker's graduation school code can be queried from the database of famous universities. If the job seeker's graduation school belongs to the set famous university category, the corresponding label information can be marked in the job seeker's resume data; a database of large companies can also be constructed. If the job seeker has a corresponding large company resume in his work experience, the label information of "excellent resume" can be marked in the job seeker's resume data.

[0074] In the present application embodiment, Figure 4 As shown, the display card triggered by the recommended resume data list can have the job seeker's name, skill information, tag information, weighted total score and the job seeker's resume data link, etc., which can make the company's recruiters see the advantages of the job seekers in the recommended resume data at a glance, thereby improving recruitment efficiency. Depending on the job seeker's application position, the tag information and weighted total score of the same job seeker displayed on the display card will change dynamically.

[0075] In some embodiments, step S120: determining the job category of the job to be applied for according to the job-seeking intention and constructing a label calculation strategy according to the job category includes the following specific steps:

[0076] There are multiple first-level functional categories for functional categories, including blue-collar positions and white-collar positions;

[0077] For blue-collar positions, education experience is not included in the scoring, and age, work experience and work skills are given different weights according to their respective attribute values;

[0078] There are several second-level functional categories under the white-collar category, including technical positions and management positions;

[0079] For technical positions, the weight of age setting is set to be smaller than the weight of education experience, work experience and work skills setting;

[0080] For management positions, the weight score set for education experience is set lower than the weight scores set for age, work experience, and work skills.

[0081] Specifically, different positions are classified according to their commonalities to obtain functional categories. For example, the first-level functional categories may include blue-collar positions and white-collar positions; among them, blue-collar positions tend to consider the age of job seekers. The younger the age of the job seeker, the higher the weight score can be set, and the educational experience can be set as not involved in the scoring; white-collar positions tend to consider the educational experience of job seekers. The higher the education level of the job seeker, the higher the weight score can be set; among them, white-collar positions can be divided into technical positions and management positions. For technical positions: the job seeker's professional skills, education level, graduation school, age, past positions in work experience, etc. need to be evaluated, and more detailed evaluation can be set. Scoring rules; for management positions, such as "sales positions", the main calculation dimensions can be work experience and then professional skills, and the weight score set for educational experience is relatively low; by setting more detailed scoring rules for different functional categories, it is possible to automatically calculate each weight score of the job seeker, and sort the resumes of job seekers in different functional categories according to the total weight score. For different positions distributed by corporate recruiters, the total weight score of the same job seeker resume data displayed changes dynamically to improve the accuracy of job seeker resume recommendations, and then assist in recruitment decisions. This not only improves recruitment efficiency, but also ensures the fairness and transparency of the evaluation process.

[0082] In some embodiments, the method further comprises the following specific steps:

[0083] S190: In the recommended resume data list, the recommended resume data is re-sorted according to a preset sorting and scattering strategy to generate different sorting positions.

[0084] Specifically, recommended resume data with the same weighted total score can be sorted in random order; in order to maintain the freshness and diversity of the data and prevent corporate recruiters from visual fatigue when searching for job seekers' resumes, in the recommended resume data list, the recommended resume data can be sorted in order according to the length of time between the generation time of the job seeker's resume and the current time; or, the recommended resume data can be sorted in order according to the length of time between the update time of the job seeker's resume and the current time; or, the recommended resume data can be sorted in order according to the age of the job seeker from oldest to youngest.

[0085] In some embodiments, step S192: triggering the display card according to the target resume data may include the following specific steps:

[0086] S1921: Determine whether to mark label information for the target resume data in the display card according to the functional category; wherein, for dimension information that does not participate in scoring, the corresponding label information is not displayed in the display card; and / or,

[0087] S1922: Sort multiple label information in a display card according to the functional category.

[0088] Specifically, a label calculation strategy is constructed according to the functional category to achieve different scoring for each dimensional information in the resume data of the job seeker. For dimensional information that does not participate in the scoring for positions under certain functional categories, the corresponding label information will not be displayed in the display card. For example, for blue-collar positions, the educational experience can be set to not participate in the scoring. Even if the label information of "famous university" can be marked in the resume data of a job seeker in the recommended resume data list, the label information of "famous university" will not be displayed in the display card accordingly to improve the accuracy of the recommended resume. When multiple label information can be marked in the resume data of a job seeker in the recommended resume data list, the multiple label information can be sorted in the display card according to the weight score of each dimensional information, so that the corresponding label information can be dynamically displayed for positions under different functional categories.

[0089] The above describes the implementation methods and advantages of the embodiments of the present application through multiple embodiments. The following describes the specific processing process of the embodiments of the present application in detail with reference to specific examples.

[0090] Scenario 1: Blue-collar positions:

[0091] For example, the job recruitment information posted by the HR recruiter of Company A is as follows: Cantonese chef, Sichuan chef, experience in star-rated hotels, and relevant grade certificates.

[0092] After preliminary screening, the candidate resume data list that matches the recruitment requirements includes the following job seeker resume data:

[0093] 1. Mr. Zhang intends to be a chef. He is good at Sichuan cuisine, has a senior chef technician certificate, has a high school education, has work experience in a well-known five-star hotel, and is 35 years old.

[0094] 2. Mr. Li also intends to be a chef. He is good at Cantonese cuisine. He does not have any relevant technician certificate. He has an ordinary bachelor's degree and has work experience in a well-known five-star hotel. He is 35 years old.

[0095] According to the label calculation strategy, the candidate resume data is scored and label information is obtained as follows:

[0096] 1. Mr. Zhang: 20 points for skills + 20 points for work experience in a famous company + 20 points for age = 60 points. Obtain label information: Excellent resume and rich experience.

[0097] 2. Mr. Li: 15 points for skills + 20 points for work experience in a famous company + 20 points for age = 55 points. Obtain label information: Excellent resume and rich experience.

[0098] From this we can see that Mr. Li, who has an advantage in academic qualifications, has a lower weighted total score because academic qualifications are not included in the scoring.

[0099] If the candidate resume data whose weighted total score exceeds the set threshold of 50 points is used as recommended resume data, the weighted total score of Mr. Zhang and Mr. Li both exceed the set threshold of 50 points, and the resumes of Mr. Zhang and Mr. Li are used as recommended resumes; when the recruiter HR of Company A enters the page to browse the resumes of job seekers, Mr. Zhang will be ranked ahead of Mr. Li because of his higher weighted total score.

[0100] Scenario 2: Technical positions under white-collar positions:

[0101] For example, the job recruitment information posted by the HR recruiter of Company B is as follows: Internet Technology Manager, required to be proficient in Java development language and MySQL database.

[0102] After preliminary screening, the candidate resume data list that matches the recruitment requirements includes the following job seeker resume data:

[0103] 1. Mr. Wang: Graduated from a top 2 university with a bachelor's degree, Internet software architect, has software development related skills (such as Java, MySQL), has worked in famous companies, and is 35 years old.

[0104] 2. Mr. Zhao: Graduated from a key university with a bachelor's degree, majored in Internet research and development, has software development related skills (such as Java, MySQL), has worked in famous companies, and is 35 years old.

[0105] According to the label calculation strategy, the candidate resume data is scored and label information is obtained as follows:

[0106] 1. Mr. Wang: 20 points for education + 20 points for skills + 20 points for work experience in a famous company + 20 points for age = 80 points. Obtain tag information: famous university, excellent resume, rich experience, senior industry personnel.

[0107] 2. Mr. Zhao: 15 points for education + 20 points for skills + 20 points for work experience in a famous company + 20 points for age = 75 points. Obtain label information: excellent resume, rich experience, senior industry personnel.

[0108] If the candidate resume data whose total weighted score exceeds the set threshold of 70 points is used as recommended resume data, the total weighted scores of Mr. Wang and Mr. Zhao both exceed the set threshold of 70 points, and the resumes of Mr. Wang and Mr. Zhao are used as recommended resumes; when the recruiter HR of Company B enters the page to browse the resumes of job seekers, Mr. Wang will be ranked ahead of Mr. Zhao because of his higher total weighted score.

[0109] Scenario 3: Management positions under white-collar positions:

[0110] For example, the job recruitment information posted by the HR recruiter of Company C is as follows: Internet industry, sales director position, requiring the ability to build and manage teams, and business negotiations.

[0111] After preliminary screening, the candidate resume data list that matches the recruitment requirements includes the following job seeker resume data:

[0112] 1. Ms. Liu: Graduated from an ordinary university with a bachelor's degree, works in the Internet industry, software sales position, has the following skills: team building and management, business negotiation, sales planning and strategy formulation; once worked in a large Internet company, won the sales champion many times, the title is sales director, 35 years old.

[0113] 2. Ms. Wei: Graduated from a key university with a master's degree, works in the Internet industry, software sales position, has the following skills: team building and management, business negotiation; once worked in a large Internet company with the title of sales manager, 35 years old.

[0114] 3. Ms. Zhang: Graduated from a key university with a master's degree, works in the Internet industry, software sales position, has the following skills: business negotiation, sales planning and strategy formulation; once worked in a large Internet company with the title of sales manager, 35 years old.

[0115] According to the label calculation strategy, the candidate resume data is scored and label information is obtained as follows:

[0116] 1. Ms. Liu: Educational experience 8 points + Skills 20 points + Work experience in a famous company 20 points + Age 20 points + Position level (20) = 88 points. Obtain tags: Excellent resume, rich experience, senior industry personnel.

[0117] 2. Ms. Wei's education experience 10 points + skills 15 points + work experience in famous companies 20 points + age 20 points + position level (15) = 75 points. Obtain tags: famous university, highly educated talent, excellent resume, rich experience.

[0118] 3. Ms. Zhang's education experience 10 points + skills 15 points + work experience in famous companies 20 points + age 20 points + job level (15) = 75 points. Obtain tags: famous university, highly educated talent, excellent resume, rich experience.

[0119] From this, we can see that Ms. Wei and Ms. Zhang both have better educational experience than Ms. Liu, but the weight score of educational experience is set relatively low for the sales position. After calculation, the total weight score of Ms. Wei and Ms. Zhang does not have an advantage and is still lower than the total weight score of Ms. Liu.

[0120] If the candidate resume data with a total weight score exceeding the set threshold of 70 points is used as recommended resume data, the total weight scores of Ms. Liu, Ms. Wei and Ms. Zhang all exceed the set threshold of 70 points, and their resumes are all recommended resumes; when the HR recruiter of Company C enters the page to browse job seekers' resumes, Ms. Liu will be ranked first because of her highest total weight score; Ms. Wei and Ms. Zhang have the same total weight score, and their ranking positions can change according to the current random sorting rules.

[0121] Corresponding to the method embodiment of the present application, the present application also provides a device for recommending job seekers' resumes based on job categories, such as Figure 5 As shown, it may specifically include:

[0122] The first acquisition module 510 is used to acquire the resume data of the job seeker; wherein the resume data of the job seeker includes one or more of the following dimensional information: basic information, education experience, work experience, work skills and job-seeking intention of the job seeker;

[0123] A construction module 520 is used to determine the job category of the job application according to the job application intention, and to construct a label calculation strategy according to the job application category; wherein the label calculation strategy includes setting different weight scores for the same dimension information in the job applicant's resume data under different job application categories;

[0124] A second acquisition module 530 is used to acquire job description information posted by recruiters to obtain query conditions;

[0125] A screening module 540 is used to screen the resume data of job seekers according to the query conditions to obtain a list of candidate resume data matching the query conditions;

[0126] A scoring module 550 is used to score each dimension of information in each candidate resume data according to the constructed label calculation strategy to obtain a weighted score for each dimension of information;

[0127] A calculation module 560 is used to calculate the weight score of each dimension information to obtain a weighted total score;

[0128] The recommendation module 570 is used to filter the candidate resume data list according to the weighted total score to obtain a recommended resume data list;

[0129] Display module 580 is used to trigger a display card according to a recommended resume data list; wherein, the display card is used to display the basic information of the job seeker and the weighted total score of the job seeker. The weighted total score of the resume data of the same job seeker is different under different functional categories, so that the weighted total score of the resume data of the same job seeker changes dynamically according to different positions.

[0130] The electronic device in the embodiment of the present application may be a user terminal device, a server, other computing devices, or a cloud server. Figure 6 A schematic diagram of the hardware structure of an electronic device according to an embodiment of the present application is shown. The electronic device may include a processor 601 and a memory 602 storing computer program instructions. When the processor 601 executes the computer program instructions, the process or function of any of the above-mentioned embodiments of the method is implemented.

[0131] Specifically, the processor 601 may include a central processing unit (CPU), or an application-specific integrated circuit (ASIC), or may be configured to implement one or more integrated circuits of the embodiments of the present application. The memory 602 may include a large-capacity memory for data or instructions. For example, the memory 602 may be at least one of the following: a hard disk drive (HDD), a read-only memory (ROM), a random access memory (RAM), a floppy disk drive, a flash memory, an optical disk, a magneto-optical disk, a tape, a universal serial bus (USB) drive or other physical / tangible memory storage device. For another example, the memory 602 may include a removable or non-removable (or fixed) medium. For another example, the memory 602 may be inside or outside the integrated gateway disaster recovery device. The memory 602 may be a non-volatile solid-state memory. In other words, the memory 602 usually includes a tangible (non-transitory) computer-readable storage medium (such as a memory device) encoded with computer-executable instructions, and when the software is executed (such as executed by one or more processors), the operation described in the method of the embodiment of the present application can be performed. The processor 601 implements the process or function of any method in the above embodiments by reading and executing the computer program instructions stored in the memory 602.

[0132] In one example, Figure 6 The electronic device shown may also include a communication interface 603 and a bus 610. Among them, the processor 601, the memory 602, and the communication interface 603 are connected through the bus 610 and complete the communication between each other. The communication interface 603 is mainly used to realize the communication between each module, device, unit and / or device in the embodiment of the present application. The bus 610 includes hardware, software or both, and can couple the components of the online data traffic billing device to each other. For example, the bus may include at least one of the following: an accelerated graphics port (AGP) or other graphics bus, an enhanced industrial standard architecture (EISA) bus, a front-end bus (FSB), a hypertransport (HT) interconnect, an industrial standard architecture (ISA) bus, an infinite bandwidth interconnect, a low pin count (LPC) bus, a memory bus, a micro channel architecture (MCA) bus, a peripheral component interconnect (PCI) bus, a PCI-Express (PCI-X) bus, a serial advanced technology attachment (SATA) bus, a video electronics standard association local (VLB) bus or other suitable buses. The bus 610 may include one or more buses. Although the embodiments of the present application describe or illustrate a specific bus, the embodiments of the present application may consider any suitable bus or interconnection method.

[0133] In combination with the method in the above embodiments, an embodiment of the present application also provides a computer-readable storage medium, on which computer program instructions are stored. When the computer program instructions are executed by a processor, the process or function of any method in the above embodiments is implemented.

[0134] In addition, an embodiment of the present application further provides a computer program product, on which computer program instructions are stored. When the computer program instructions are executed by a processor, the process or function of any one of the methods in the above embodiments is implemented.

[0135] The above exemplarily describes the flowcharts and / or block diagrams of the methods, devices, systems and computer program products of the embodiments of the present application, and describes the relevant various aspects. It should be understood that each box or combination thereof in the flowchart and / or block diagram can be implemented by computer program instructions, or by dedicated hardware that performs a specified function or action, or by a combination of dedicated hardware and computer instructions. For example, these computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer or other programmable data processing device to form a machine that enables these instructions executed by such a processor to enable the implementation of the functions / actions specified in each box or combination thereof in the flowchart and / or block diagram. Such a processor can be a general-purpose processor, a special-purpose processor, a special application processor or a field programmable logic circuit.

[0136] The functional blocks shown in the structured block diagram of the embodiment of the present application can be implemented as hardware, software, firmware or a combination thereof. When implemented in hardware, it can be, for example, an electronic circuit, an application-specific integrated circuit (ASIC), appropriate firmware, a plug-in, a function card, etc.; when implemented in software, it is a program or code segment used to perform the required task. The program or code segment can be stored in a memory, or transmitted on a transmission medium or a communication link via a data signal carried in a carrier. The code segment can be downloaded via a computer network such as the Internet, an intranet, etc.

[0137] It should be noted that the present application is not limited to the specific configurations and processes described above or shown in the figures. The above is only a specific implementation mode of the present application. Those skilled in the art can clearly understand that for the convenience and brevity of description, the specific working process of the described system, device, module or unit can refer to the corresponding process in the method embodiment without further description. It should be understood that the scope of protection of the present application is not limited to this. Any technician familiar with the technical field can think of various equivalent modifications or substitutions within the technical scope disclosed in the present application, and these modifications or substitutions should be included in the scope of protection of the present application.

Claims

1. A method for recommending job seekers' resumes based on job categories, characterized in that: include: Obtaining resume data of job seekers; wherein the resume data of job seekers includes one or more of the following dimensional information: basic information, education experience, work experience, work skills and job-seeking intention of job seekers; Determine the functional category of the job to which the job is applied based on the job application intention, and construct a label calculation strategy based on the functional category; wherein the label calculation strategy includes setting different weight scores for the same dimension information in the job applicant's resume data under different functional categories; Obtain job description information posted by recruiters to obtain query conditions; Screening the resume data of job seekers according to the query conditions to obtain a list of candidate resume data matching the query conditions; According to the established label calculation strategy, each dimension of information in each candidate's resume data is scored to obtain the weighted score of each dimension of information; Calculate the weighted scores of each dimension information to obtain the total weighted score; Filter the candidate resume data list according to the weighted total score to obtain a recommended resume data list; A display card is triggered according to the recommended resume data list; wherein, the display card is used to display the basic information of the job seeker and the weighted total score of the job seeker. The weighted total score of the resume data of the same job seeker is different under different functional categories, so that the weighted total score of the resume data of the same job seeker changes dynamically according to different positions.

2. The method according to claim 1, characterized in that Also includes: Generate a number of label information corresponding to the education experience, work experience, and work skills in the resume data of the job seeker according to a preset generation strategy to obtain target resume data; wherein the target resume data is the recommended resume data that has been marked with label information; The display card is triggered according to the target resume data, and the display card is also used to display tag information and a link to the resume data of the job seeker.

3. The method according to claim 1, characterized in that Determining the functional category of the job to be applied for based on the job-seeking intention and constructing a label calculation strategy based on the functional category includes: There are multiple first-level functional categories for functional categories, including blue-collar positions and white-collar positions; For blue-collar positions, education experience is not included in the scoring, and age, work experience and work skills are given different weights according to their respective attribute values; There are several second-level functional categories under the white-collar category, including technical positions and management positions; For technical positions, the weight of age setting is set to be smaller than the weight of education experience, work experience and work skills setting; For management positions, the weight score set for education experience is set lower than the weight scores set for age, work experience, and work skills.

4. The method according to claim 1, characterized in that: The query conditions include one or more of the following: skill information, job function category and industry.

5. The method according to claim 1, characterized in that Also includes: In the recommended resume data list, the recommended resume data is re-sorted according to a preset sorting and scattering strategy to generate different sorting positions.

6. The method according to claim 1, characterized in that The label information includes any of the following: a prestigious university, a senior industry insider, rich experience, a highly educated talent, or an excellent resume.

7. The method according to claim 2, characterized in that The triggering of the display card according to the target resume data includes: Determine whether to mark the target resume data with label information in the display card according to the functional category; wherein, for the dimension information not involved in the scoring, the corresponding label information is not displayed in the display card; and / or, Sort multiple tab information in a display card by functional category.

8. A device for recommending job seekers' resumes based on job categories, characterized in that: include: The first acquisition module is used to acquire the resume data of the job seeker; wherein the resume data of the job seeker includes one or more of the following dimensional information: basic information, education experience, work experience, work skills and job-seeking intention of the job seeker; A construction module is used to determine the functional category of the job to be applied for according to the job-seeking intention, and to construct a label calculation strategy according to the functional category; wherein the label calculation strategy includes setting different weight scores for the same dimension information in the resume data of the job seeker under different functional categories; The second acquisition module is used to acquire the job description information posted by the recruiter to obtain the query conditions; A screening module is used to screen the resume data of job seekers according to the query conditions to obtain a list of candidate resume data that matches the query conditions; The scoring module is used to score each dimension of information in each candidate resume data according to the established label calculation strategy to obtain the weighted score of each dimension of information; A calculation module is used to calculate the weight score of each dimension information to obtain the total weight score; The recommendation module is used to filter the candidate resume data list according to the weighted total score to obtain a recommended resume data list; A display module is used to trigger a display card based on a recommended resume data list; wherein, the display card is used to display the basic information of the job seeker and the weighted total score of the job seeker, and the weighted total score of the resume data of the same job seeker is different under different functional categories, so that the weighted total score of the resume data of the same job seeker changes dynamically according to different positions.

9. An electronic device, characterized in that: The electronic device comprises: a processor and a memory storing computer program instructions; when the electronic device executes the computer program instructions, the method according to any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer program instructions, and when the computer program instructions are executed by a processor, the method according to any one of claims 1 to 7 is implemented.

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