Resume screening method and device based on AI resume assistant and readable storage medium
Through the AI resume assistant, the sentences entered by the recruiter are analyzed semantically, and the screening conditions are automatically generated and the resume is scored. This solves the problems of cumbersome and poor accuracy in the existing technology of screening resumes, and realizes efficient and accurate resume screening and talent match.
Patent Information
- Application Number
- CN202411057161.4
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-08-02
- Publication Date
- 2024-12-10
AI Technical Summary
In the prior art, when screening job seekers' resumes, the recruiting unit needs to set different filter conditions for multiple positions, resulting in cumbersome operations and poor accuracy. Updating the filter conditions requires developers to redevelop them, resulting in high costs.
Using AI-based resume assistants, semantic analysis of the target statements entered by recruiters, automatically generate filtering conditions, and score user resumes, filter target resumes based on the total score, reduce filtering of inappropriate resumes, and improve matching accuracy. .
It simplifies the operation process of recruiters, reduces development costs, improves the accuracy and efficiency of resume screening, and helps recruiters quickly find the right talents.
Smart Images
Figure CN119107054A_ABST
Abstract
Description
Technical Field
[0001] The present application relates to the field of artificial intelligence technology, and in particular to a resume screening method, device and readable storage medium based on an AI resume assistant. Background Art
[0002] Currently, when screening job seekers' resumes, a filtering scheme is generally adopted. Recruiters are usually required to input and save the resume filtering conditions. When processing data, the search recommendation engine will filter out resumes that are not of interest according to the resume filtering conditions set by the recruiter, thereby improving the recruiter's resume processing efficiency.
[0003] However, for recruiting companies that are recruiting for multiple positions at the same time, they may need to set different resume screening conditions for different positions, which is cumbersome and increases the workload of recruiters. In addition, resume screening conditions can only be selected from a few preset screening conditions, which has certain restrictions, making it difficult to screen out resumes that meet the requirements of recruiters, that is, the accuracy of the screened resumes is poor. In addition, when updating the product, if the preset screening conditions are updated, developers usually need to redevelop them, which in turn consumes a lot of development costs. Summary of the invention
[0004] In view of this, an embodiment of the present application provides a resume screening method, device and readable storage medium based on an AI resume assistant, which is used to solve at least one of the above technical problems.
[0005] The embodiment of the present application provides a resume screening method based on an AI resume assistant, the method comprising: in response to a first user setting or default setting for a first screening condition, setting a first screening condition corresponding to a target position, the first screening condition being used to screen user resumes, and the first screening condition including at least one first screening item; receiving a first target statement input by the first user, and semantically parsing the first target statement based on the AI resume assistant to obtain a second screening condition corresponding to the target position, the second screening condition being used to screen user resumes and including at least one second screening item, the second screening item being different from the first screening item; after receiving user resumes of multiple second users, for any user resume, determining whether the user resume satisfies the first screening item and the second screening item; wherein, for any first screening item, if the user If the user resume meets the first filtering item, the basic score corresponding to the first filtering item will be given, if not, the basic score corresponding to the first filtering item will not be given; for any second filtering item, if the user resume meets the second filtering item, the highlight score corresponding to the second filtering item will be given, if not, the highlight score corresponding to the second filtering item will not be given; for any user resume, the sum of the basic score corresponding to each first filtering item and the highlight score corresponding to each second filtering item is calculated to obtain the total score of the user resume; in order of total scores from large to small, the user resumes with total scores greater than the first score threshold and ranked in the top N are taken as target resumes, and the target resume and / or user information of the second user corresponding to the target resume is displayed on the screen, and the user information at least includes the user name and / or user ID, and N is a positive integer.
[0006] According to some embodiments of the present application, optionally, after obtaining the total score of the user's resume, the resume screening method based on the AI resume assistant also includes: automatically executing the resume processing task corresponding to the score range according to the score range in which the total score of the user's resume is located, the resume processing task including marking the user's resume as inappropriate, marking the user's resume as suitable, placing the user's resume in an interview pending list, sending an interview invitation to the second user corresponding to the user's resume, and actively initiating a chat with the second user corresponding to the user's resume.
[0007] According to some embodiments of the present application, optionally, according to the score range in which the total score of the user resume is located, the resume processing task corresponding to the score range is automatically executed, including: judging whether the total score is greater than a first score threshold, if it is less than or equal to the first score threshold, marking the user resume as inappropriate, and if it is greater than the first score threshold, marking the user resume as appropriate; judging whether the total score is greater than a second score threshold, if it is greater than the first score threshold and less than or equal to the second score threshold, placing the user resume in an interview pending list, and if it is greater than the second score threshold, sending an interview invitation to the second user corresponding to the user resume; judging whether the total score is greater than a third score threshold, if it is greater than the third score threshold, actively initiating a chat with the second user corresponding to the user resume; the third score threshold is greater than the second score threshold, and the second score threshold is greater than the first score threshold.
[0008] According to some embodiments of the present application, optionally, a semantic analysis is performed on the first target sentence based on the AI resume assistant to obtain a second filtering condition corresponding to the target position, including: extracting keywords in the first target sentence, and generating at least one second filtering item based on the keywords; if it is detected that the first user inputs a highlight score corresponding to the second filtering item, then in response to the first user's input, the highlight score corresponding to the second filtering item is set; if the first user is not detected to input a highlight score corresponding to the second filtering item, then based on the default assigned score of the highlight score, the highlight score corresponding to the second filtering item is set; inquire the first user whether the second filtering condition is only applicable to the target position or to multiple positions including the target position. If the first user feedback is that it is only applicable to the target position, then the second filtering condition is used only as the second filtering condition corresponding to the target position; if the first user feedback is that it is applicable to multiple positions including the target position, then the second filtering condition is used only as the second filtering condition corresponding to multiple positions.
[0009] According to some embodiments of the present application, optionally, before displaying the target resume and / or the user information of the second user corresponding to the target resume on the screen, the resume screening method based on the AI resume assistant also includes: for any user resume, calculating the sum of the highlight scores corresponding to each second screening item to obtain the total highlight score of the user resume; displaying the target resume and / or the user information of the second user corresponding to the target resume on the screen, including: highlighting the target resume and / or the user information of the second user corresponding to the target resume whose total highlight score is greater than a fourth score threshold.
[0010] According to some embodiments of the present application, optionally, the resume screening method based on the AI resume assistant also includes: in response to the second target statement input by the first user, semantically parsing the second target statement based on the AI resume assistant, obtaining a third filtering condition corresponding to the target position and / or a deletion instruction of the second filtering item, the third filtering condition includes a method for filtering user resumes and includes at least one third filtering item; in response to the deletion instruction of the second filtering item, deleting the corresponding second filtering item; for any third filtering item, determining whether the third filtering item is the same as the existing second filtering item, if the same, deleting the third filtering item; if different, updating the third filtering item to the second filtering item, and returning to the step of determining whether the user resume satisfies the first filtering item and the second filtering item for any user resume.
[0011] According to some embodiments of the present application, optionally, the first screening condition includes at least one first screening item among major, education, age, gender, place of residence, salary requirements and industry; the second screening condition includes at least one second screening item among work experience, personality and hobbies, skills and certificates.
[0012] According to some embodiments of the present application, optionally, the window of the AI resume assistant is displayed floating in a preset area of the screen, and the window of the AI resume assistant remains displayed when the page is updated.
[0013] The embodiment of the present application provides a resume screening device based on an AI resume assistant, the device comprising:
[0014] A first setting module, configured to set a first screening condition corresponding to a target position in response to a first user setting or a default setting for a first screening condition, wherein the first screening condition is used to screen user resumes, and the first screening condition includes at least one first screening item;
[0015] A semantic parsing module, used to receive a first target sentence input by a first user, and perform semantic parsing on the first target sentence based on the AI resume assistant to obtain a second screening condition corresponding to the target position, where the second screening condition is used to screen the user resume and includes at least one second screening item, and the second screening item is different from the first screening item;
[0016] A judgment module is used to, after receiving the user resumes of the plurality of second users, judge, for any user resume, whether the user resume satisfies the first filter item and the second filter item; wherein, for any first filter item, if the user resume satisfies the first filter item, a basic score corresponding to the first filter item is given, and if not, no basic score corresponding to the first filter item is given; for any second filter item, if the user resume satisfies the second filter item, a highlight score corresponding to the second filter item is given, and if not, no highlight score corresponding to the second filter item is given;
[0017] A calculation module, for calculating, for any user resume, the sum of the basic scores corresponding to each first screening item and the highlight scores corresponding to each second screening item, to obtain a total score of the user resume;
[0018] The display module is used to select the user resumes with total scores greater than the first score threshold and ranked in the top N order as target resumes in descending order of total scores, and display the target resume and / or user information of the second user corresponding to the target resume on the screen, wherein the user information at least includes the user name and / or user ID, and N is a positive integer.
[0019] 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.
[0020] 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.
[0021] 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.
[0022] By using the resume screening method, device and readable storage medium based on the AI resume assistant provided in the embodiments of the present application, on the one hand, the first target statement input by the first user can be semantically parsed through the AI resume assistant to obtain the second screening condition for screening the user resume corresponding to the target position. If the first user wants to set the second screening condition he or she expects, he or she only needs to enter the corresponding first target statement, which is simple to operate and reduces the workload of the recruiter; at the same time, there is no need for developers to redevelop, which reduces the development cost; on the other hand, based on the set first screening condition and the generated second screening condition, each user resume is scored to obtain the total score of each user resume, and then the target resume is screened out according to the total score of the user resume. In this way, on the basis of filtering out inappropriate resumes, user resumes that are more in line with the requirements of the first target statement (i.e., the second screening condition) can be matched first, thereby improving the accuracy of screening user resumes and helping recruiters quickly find suitable talents. BRIEF DESCRIPTION OF THE DRAWINGS
[0023] 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.
[0024] Figure 1 A schematic diagram of a system architecture of an embodiment of the present application.
[0025] Figure 2 A flowchart of a resume screening method based on an AI resume assistant according to an embodiment of the present application.
[0026] Figure 3 Another flowchart of the resume screening method based on the AI resume assistant according to an embodiment of the present application.
[0027] Figure 4 This is a flow chart of S202 in the resume screening method based on the AI resume assistant in an embodiment of the present application.
[0028] Figure 5 A structural schematic diagram of a resume screening device based on an AI resume assistant provided in an embodiment of the present application.
[0029] Figure 6 A schematic diagram of an electronic device used to implement the resume screening method based on an AI resume assistant according to an embodiment of the present application. DETAILED DESCRIPTION
[0030] 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.
[0031] 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 requests protection for a resume screening method, apparatus, electronic device, computer-readable storage medium, and computer program product based on an AI resume assistant. 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.
[0032] 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).
[0033] Before describing the technical solutions provided by the embodiments of the present application, in order to facilitate the understanding of the embodiments of the present application, the present application first specifically describes the problems existing in the related art:
[0034] Currently, when screening job seekers' resumes, a filtering scheme is generally adopted. Recruiters are usually required to input and save the resume filtering conditions. When processing data, the search recommendation engine will filter out resumes that are not of interest according to the resume filtering conditions set by the recruiter, thereby improving the recruiter's resume processing efficiency.
[0035] However, for recruiting companies that are recruiting for multiple positions at the same time, they may need to set different resume screening conditions for different positions, which is cumbersome and increases the workload of recruiters. In addition, resume screening conditions can only be selected from a few preset screening conditions, which has certain restrictions, making it difficult to screen out resumes that meet the requirements of recruiters, that is, the accuracy of the screened resumes is poor. In addition, when updating the product, if the preset screening conditions are updated, developers usually need to redevelop them, which in turn consumes a lot of development costs.
[0036] In order to solve at least one of the above technical problems, the embodiments of the present application provide a resume screening method, device and readable storage medium based on an AI resume assistant.
[0037] AI Resume Assistant is a tool based on artificial intelligence technology, designed to help recruiters screen high-quality user resumes. AI Resume Assistant can be used to analyze the target statement describing the recruitment requirements entered by the recruiter, automatically generate screening conditions that meet the requirements, and score the user resume based on the screening conditions to obtain the total score of the user resume, and then screen out the target resume based on the total score of the user resume. In addition, AI Resume Assistant can also push target resumes to recruiters to help recruiters quickly find suitable talents. With AI Resume Assistant, recruiters can save time, improve efficiency, and better find suitable user resumes and their corresponding talents.
[0038] The following first introduces the resume screening method based on AI resume assistant provided in the embodiment of the present application.
[0039] Figure 2 Schematic diagram of a resume screening method based on AI resume assistant according to an embodiment of the present application. Figure 2 As shown, the method comprises the following steps:
[0040] S201: In response to a first user setting or a default setting for a first screening condition, setting a first screening condition corresponding to a target position.
[0041] Among them, the first screening condition can be used to screen user resumes. The first screening condition can also be called a basic screening condition. The first screening condition can include at least one first screening item. For example, in some examples, the first screening condition can include at least one first screening item in major, education, age, gender, place of residence, salary requirements, and industry. For example, in some specific examples, the first screening condition can be limited to major as "computer", education as "bachelor's degree or above", age as "18 to 40 years old", and gender is not limited.
[0042] The target position can be any position, and this application does not limit this. The first screening conditions corresponding to different positions can be different or the same, and can be flexibly adjusted according to actual conditions. For example, in some specific examples, the first screening conditions corresponding to multiple positions can be set uniformly (i.e., the same), thereby reducing the workload of repeatedly setting each position.
[0043] In S201, the first screening condition corresponding to the target position may be set in response to the first user's setting of the first screening condition. Of course, if the first user does not personalize the first screening condition, the first screening condition corresponding to the target position may also be set based on the default setting of the first screening condition. The default setting may be flexibly adjusted according to actual conditions, and this application does not limit this.
[0044] S202: Receive a first target sentence input by a first user, and perform semantic analysis on the first target sentence based on the AI resume assistant to obtain a second screening condition corresponding to the target position.
[0045] For example, the first user can be a recruiter or a recruiter. The first user can enter a first target statement on the page or window of the AI resume assistant. The first target statement can be any statement used to describe the job requirements, such as the job seeker needs to work in the target company or target position for more than 3 years, the skills and / or certificates that the job seeker needs to have, etc. This application does not limit this. The target company and the target position can be any company and any position. After receiving the first target statement input by the first user, the AI resume assistant can perform semantic analysis on the first target statement and generate a second screening condition corresponding to the target position. The second screening condition can be used to screen user resumes. The second screening condition can also be called a highlight screening condition. The second screening condition may include at least one second screening item, and the second screening item is different from the first screening item. For example, in some examples, the second screening condition may include at least one second screening item in work experience, personality hobbies, skills, and certificates.
[0046] In some specific embodiments, optionally, a trained natural language processing (NLP) model is provided in the AI resume assistant, and the first target sentence is semantically parsed through the natural language processing model to generate a second screening condition corresponding to the target position.
[0047] S203: After receiving user resumes of multiple second users, for any one of the user resumes, determine whether the user resume satisfies the first filter item and the second filter item; wherein, for any one of the first filter items, if the user resume satisfies the first filter item, a basic score corresponding to the first filter item is given, and if not, no basic score corresponding to the first filter item is given; for any one of the second filter items, if the user resume satisfies the second filter item, a highlight score corresponding to the second filter item is given, and if not, no highlight score corresponding to the second filter item is given.
[0048] One or more first filter items can be set, and each first filter item can be set with a corresponding basic score. The basic scores corresponding to different first filter items may be different or the same, and this application does not limit this. For any first filter item, if the user's resume meets the first filter item, the basic score corresponding to the first filter item is given, and if it does not meet the first filter item, the basic score corresponding to the first filter item is not given. Taking the first filter item as an example in which the academic qualification is limited to undergraduate or above, if the academic qualification in the user's resume is undergraduate or above, such as undergraduate, master or doctoral, the basic score corresponding to the first filter item is given, otherwise the basic score corresponding to the first filter item is not given.
[0049] One or more second filter items can be set, and each second filter item can be set with a corresponding highlight score. The highlight scores corresponding to different second filter items can be different or the same, and this application does not limit this. For any second filter item, if the user's resume meets the second filter item, the highlight score corresponding to the second filter item is given, and if it does not meet the second filter item, the highlight score corresponding to the second filter item is not given. Taking the second filter item that requires mastering skill A as an example, if the user's resume has skill A, the highlight score corresponding to the second filter item is given, otherwise the highlight score corresponding to the second filter item is not given.
[0050] The size of the basic score set for each first filtering item and the size of the highlight score set for each second filtering item can be flexibly adjusted according to actual conditions, and this application does not impose any limitation on this.
[0051] S204: For any user resume, the sum of the basic scores corresponding to each first filter item and the highlight scores corresponding to each second filter item is calculated to obtain a total score of the user resume.
[0052] For any user resume, the basic scores corresponding to the first screening items obtained by the user resume and the highlight scores corresponding to the second screening items obtained by the user resume can be added together to obtain the total score of the user resume.
[0053] S205: In descending order of total scores, select the top N user resumes with total scores greater than the first score threshold as target resumes, and display the target resume and / or user information of the second user corresponding to the target resume on the screen, where the user information at least includes the user name and / or user ID, and N is a positive integer.
[0054] Multiple user resumes can be sorted in descending order of total scores, and the top N user resumes with total scores greater than the first score threshold are used as target resumes. The size of the first score threshold can be flexibly adjusted according to actual conditions, and this application does not limit this. After determining the target resume, the target resume and / or user information of the second user corresponding to the target resume can be displayed on the screen, and the user information can at least include the user name and / or user ID for the first user to view.
[0055] The resume screening method based on AI resume assistant provided by the embodiment of the present application, on the one hand, can perform semantic analysis on the first target statement input by the first user through the AI resume assistant, and obtain the second screening condition corresponding to the target position for screening the user resume. If the first user wants to set the second screening condition he / she expects, he / she only needs to enter the corresponding first target statement, which is simple to operate and reduces the workload of the recruiter; at the same time, there is no need for developers to redevelop, which reduces the development cost; on the other hand, based on the set first screening condition and the generated second screening condition, each user resume is scored to obtain the total score of each user resume, and then the target resume is screened out according to the total score of the user resume. In this way, on the basis of filtering out inappropriate resumes, user resumes that are more in line with the requirements of the first target statement (i.e., the second screening condition) can be matched first, thereby improving the accuracy of screening user resumes and helping recruiters quickly find suitable talents.
[0056] According to some embodiments of the present application, optionally, the AI resume assistant can cooperate with the resume filter to jointly perform resume screening. The resume filter is a tool for screening and filtering out a large number of job seekers' resumes. It can automatically screen and filter out resumes that meet the requirements according to pre-set conditions and keywords. For example, in some examples, in S201, a first screening condition can be set in the resume filter. In S203, the resume filter can first be used to filter out user resumes that do not meet the first screening condition, and retain user resumes that meet the first screening condition. Then, only the user resumes that meet the first screening condition are scored. In this way, the number of user resumes that need to be scored can be reduced, and the efficiency of resume screening can be improved.
[0057] The inventors of this application have further discovered that, currently, recruiters mainly manually process the screened user resumes, such as sending interview invitations to job seekers and / or initiating chats with job seekers, which results in a large workload for recruiters and low efficiency in processing user resumes.
[0058] Figure 3 Another flowchart of the resume screening method based on the AI resume assistant of the embodiment of the present application is shown in FIG. Figure 3 As shown, according to some embodiments of the present application, optionally, after S204: obtaining the total score of the user resume, the resume screening method based on the AI resume assistant may further include the following steps:
[0059] S206: Automatically execute the resume processing task corresponding to the score interval according to the score interval of the total score of the user resume.
[0060] Specifically, multiple score intervals may be pre-divided, and different score intervals may correspond to different resume processing tasks. For example, the resume processing task may include at least one of marking the user resume as unsuitable, marking the user resume as suitable, placing the user resume in an interview pending list, sending an interview invitation to the second user corresponding to the user resume, and actively initiating a chat with the second user corresponding to the user resume.
[0061] For example, in some examples, when the total score of the user resume is in score interval a, the user resume can be marked as unsuitable. When the total score of the user resume is in score interval b, the user resume can be marked as suitable, and the user resume can be included in the interview waiting list. For the user resumes included in the interview waiting list, although the total scores of these user resumes are qualified but still low, the recruiter can judge whether to send an interview invitation and / or initiate a chat. When the total score of the user resume is in score interval c, the user resume can be marked as suitable, and an interview invitation can be automatically sent to the second user corresponding to the user resume. When the total score of the user resume is in score interval d, the user resume can be marked as suitable, and an interview invitation can be automatically sent to the second user corresponding to the user resume, and a chat can be initiated with the second user corresponding to the user resume. Score interval a, score interval b, score interval c and score interval d are different score intervals, and the minimum value of score interval d>the minimum value of score interval c>the minimum value of score interval b>the minimum value of score interval a. It can be understood that the target resume can be the top N user resumes in the user resume marked as suitable, sorted in order from large to small according to the total score.
[0062] In this way, according to the score range in which the total score of the user's resume lies, the resume processing task corresponding to the score range is automatically executed, which can improve the processing efficiency of user resumes in the entire recruitment process and reduce the workload of recruiters.
[0063] In some specific embodiments, optionally, S206: automatically executing the resume processing task corresponding to the score interval according to the score interval in which the total score of the user resume is located, may include the following steps 1 to 3.
[0064] Step 1: Determine whether the total score is greater than a first score threshold. If it is less than or equal to the first score threshold, mark the user resume as inappropriate. If it is greater than the first score threshold, mark the user resume as appropriate.
[0065] Step 2: Determine whether the total score is greater than the second score threshold. If it is greater than the first score threshold and less than or equal to the second score threshold, the user resume is included in the interview pending list. If it is greater than the second score threshold, an interview invitation is sent to the second user corresponding to the user resume.
[0066] Step three: determine whether the total score is greater than a third score threshold, and if so, actively initiate a chat with a second user corresponding to the user profile.
[0067] The third score threshold is greater than the second score threshold, and the second score threshold is greater than the first score threshold. The first score threshold, the second score threshold, and the third score threshold can be flexibly adjusted according to actual conditions, and this application does not limit this.
[0068] In this way, by repeatedly judging the total score of the user resume by the first score threshold, the second score threshold and the third score threshold, it is possible to effectively avoid omission of the resume processing task corresponding to the user resume, and better match one or more resume processing tasks corresponding to the user resume. On the other hand, for a user resume whose total score is greater than the second score threshold or the third score threshold, automatically sending an interview invitation to the second user corresponding to the user resume, and / or actively initiating a chat with the second user corresponding to the user resume, can help recruiters find suitable talents in a timely and rapid manner, and reduce the probability of missing talents.
[0069] Figure 4 Schematic diagram of a process of S202 in the resume screening method based on AI resume assistant in the embodiment of the present application. Figure 4 As shown, according to some embodiments of the present application, optionally, S202: semantically parsing the first target sentence based on the AI resume assistant to obtain a second screening condition corresponding to the target position may include the following steps S401 to S403.
[0070] S401: extract keywords from a first target sentence, and generate at least one second filter item based on the keywords.
[0071] The first target sentence can be any sentence used to describe the job requirements. The AI resume assistant can extract one or more keywords in the first target sentence, such as "working in the target position for more than 3 years", "skills A required" and / or "certificate B required", etc. The AI resume assistant can generate one or more corresponding second filter items based on the one or more keywords.
[0072] For example, in some examples, a trained natural language processing model is provided in the AI resume assistant, through which one or more keywords in the first target sentence can be extracted, and one or more corresponding second filter items can be generated based on the one or more keywords.
[0073] S402: If it is detected that the first user inputs the highlight score corresponding to the second filter item, the highlight score corresponding to the second filter item is set in response to the input of the first user; if it is not detected that the first user inputs the highlight score corresponding to the second filter item, the highlight score corresponding to the second filter item is set based on the default assigned score of the highlight score.
[0074] In some examples, the first user may input the highlight score corresponding to each second filter item. If it is detected that the first user inputs the highlight score corresponding to the second filter item, the highlight score corresponding to the second filter item is set in response to the first user's input. Of course, the first user may not input the highlight score corresponding to the second filter item. If it is not detected that the first user inputs the highlight score corresponding to the second filter item, the highlight score corresponding to the second filter item is set based on the default assigned score of the highlight score. The size of the default assigned score of the highlight score can be flexibly adjusted according to the actual situation, and this application does not limit this.
[0075] S403: Inquire the first user whether the second filtering condition is applicable only to the target position or to multiple positions including the target position. If the first user feedback is that it is applicable only to the target position, the second filtering condition is used only as the second filtering condition corresponding to the target position; if the first user feedback is that it is applicable to multiple positions including the target position, the second filtering condition is used only as the second filtering condition corresponding to multiple positions.
[0076] The second screening condition can be applicable only to the target position or to multiple positions including the target position, thereby reducing the operation and workload of the recruiter. In S403, the AI resume assistant can ask the first user whether the second screening condition is applicable only to the target position or to multiple positions including the target position. If the first user feedback is applicable only to the target position, the second screening condition is used only as the second screening condition corresponding to the target position. If the first user feedback is applicable to multiple positions including the target position, the second screening condition is used only as the second screening condition corresponding to multiple positions.
[0077] In this way, if the first user wants to set the second screening condition he or she desires, he or she only needs to enter the corresponding first target statement, which is simple to operate and reduces the workload of the first user; at the same time, there is no need for developers to redevelop, which reduces development costs. On the other hand, the highlight score corresponding to the second screening item can be adjusted according to the highlight score corresponding to the second screening item entered by the first user, so that user resumes that better meet the requirements of the recruiter can be screened out, thereby improving the accuracy of screening user resumes. On another hand, according to the choice of the first user, the second screening condition can be applied only to the target position or to multiple positions including the target position, which can further reduce the operation and workload of the recruiter.
[0078] According to some embodiments of the present application, optionally, before S205: displaying the target resume and / or the user information of the second user corresponding to the target resume on the screen, the resume screening method based on the AI resume assistant may further include the following steps:
[0079] For any user resume, the sum of the highlight scores corresponding to each second filter item is calculated to obtain the total highlight score of the user resume.
[0080] For any user resume, the highlight scores corresponding to the second filter items obtained by the user resume may be added together to obtain the total highlight score of the user resume.
[0081] Accordingly, S205: displaying the target resume and / or the user information of the second user corresponding to the target resume on the screen may include the following steps:
[0082] The target resume and / or the user information of the second user corresponding to the target resume whose total highlight score is greater than the fourth score threshold are highlighted. The size of the fourth score threshold can be flexibly adjusted according to actual conditions, and this application does not limit this.
[0083] Specifically, since the second filter item is obtained based on the first target statement input by the first user, the higher the total highlight score of the user resume, the more the user resume meets the first user's personal recruitment needs or highlight needs. Therefore, by highlighting the target resume and / or the user information of the second user corresponding to the target resume whose total highlight score is greater than the fourth score threshold, the first user can more intuitively and quickly find the target resume and / or the second user corresponding to the target resume that he or she expects to have highlights, thereby improving the user experience.
[0084] According to some embodiments of the present application, optionally, the resume screening method based on the AI resume assistant may also include the following steps four to six.
[0085] Step 4: In response to the second target sentence input by the first user, the second target sentence is semantically parsed based on the AI resume assistant to obtain a third filtering condition corresponding to the target position and / or a deletion instruction of the second filtering item, where the third filtering condition includes a condition for filtering user resumes and includes at least one third filtering item.
[0086] Specifically, the first user can modify the second filtering condition, such as adding or deleting a second filtering item. For example, the first user can enter the second target statement in the AI resume assistant. The AI resume assistant can perform semantic analysis on the second target statement to obtain the third filtering condition corresponding to the target position and / or the deletion instruction of the second filtering item. The third filtering condition may include at least one third filtering item. For example, the second target statement may be "add skill a1, delete certificate b1", then the third filtering condition may include a third filtering item of "need to have skill a1", and the deletion instruction of the second filtering item may be to delete the second filtering item that requires certificate b1.
[0087] Step 5: In response to the deletion instruction of the second filtering item, delete the corresponding second filtering item.
[0088] If there is a deletion instruction for the second filter item, the corresponding second filter item may be deleted in response to the deletion instruction for the second filter item.
[0089] Step 6: For any third filter item, determine whether the third filter item is the same as the existing second filter item. If they are the same, delete the third filter item; if they are different, update the third filter item to the second filter item, and return to the step of determining whether the user resume meets the first filter item and the second filter item for any user resume.
[0090] In step 6, it can be determined whether the third filter item is the same as the existing second filter item, that is, whether they are repeated. If they are the same, the third filter item is deleted. If they are different, the third filter item can be updated to the second filter item, that is, the updated second filter item is added to the second filter condition, and the steps of determining whether the user resume meets the first filter item and the second filter item for any user resume are returned, and S203 to S205 are re-executed to obtain a new target resume, and the new target resume and / or the user information of the second user corresponding to the new target resume are displayed on the screen.
[0091] In this way, if the first user wants to modify the second filtering condition, he only needs to enter the corresponding second target statement, which is simple to operate and reduces the workload of the first user. At the same time, there is no need for developers to redevelop, which reduces development costs.
[0092] According to some embodiments of the present application, the window of the AI resume assistant is optionally displayed in a floating position in a preset area of the screen, and the window of the AI resume assistant remains displayed when the page is updated. The size and position of the window of the AI resume assistant can be flexibly adjusted according to actual conditions, and this application does not limit this.
[0093] Specifically, the window of the AI resume assistant can be resident on multiple pages, such as the resume search page, the recommended resume page, and the talent management page, etc., which is not limited in this application. The window of the AI resume assistant can remain displayed when the page is updated. In this way, the first user can enter the first target statement or the second target statement at any time, and use the AI resume assistant to set or modify the second screening condition. In this way, the first user can add and modify his specific employment needs description at any time, and the AI resume assistant can accurately recommend a suitable user resume to the first user based on the parsed conditions.
[0094] According to some embodiments of the present application, optionally, the resume screening method based on the AI resume assistant may also include the following steps:
[0095] The statistical data of the previous time period is sent to the first user at preset intervals, and the data of the automatically processed user resumes is pushed, so that the first user can view and correct the processing flow in time. The statistical data may include the number of screened target resumes and the user information of the second user corresponding to the target resumes. The data of the automatically processed user resumes may include the number of user resumes that automatically execute resume processing tasks and the user information of the second user corresponding to them.
[0096] In this way, with the help of AI resume assistant to analyze recruitment needs and accurately recommend resume services at preset time intervals, recruitment efficiency can be improved.
[0097] According to some embodiments of the present application, optionally, the resume screening method based on the AI resume assistant may also include the following steps:
[0098] When it is detected that the content of the user resume is updated, S203 to S205 are re-executed. That is, the updated user resume is re-scored, and a new target resume is obtained, and the new target resume and / or the user information of the second user corresponding to the new target resume are displayed on the screen.
[0099] Based on the same technical concept as the resume screening method based on the AI resume assistant provided in the above embodiment, accordingly, the present application also provides a specific implementation method of a resume screening device based on the AI resume assistant. Please refer to the following embodiments.
[0100] Figure 5 A structural diagram of a resume screening device based on an AI resume assistant provided in an embodiment of the present application. Figure 5 As shown, the resume screening device 50 based on the AI resume assistant provided in the embodiment of the present application may include the following modules:
[0101] A first setting module 501, configured to set a first screening condition corresponding to a target position in response to a first user setting or a default setting of a first screening condition, wherein the first screening condition is used to screen user resumes, and the first screening condition includes at least one first screening item;
[0102] The semantic parsing module 502 is used to receive a first target sentence input by a first user, and perform semantic parsing on the first target sentence based on the AI resume assistant to obtain a second screening condition corresponding to the target position, where the second screening condition is used to screen the user resume and includes at least one second screening item, and the second screening item is different from the first screening item;
[0103] The judgment module 503 is used to judge whether the user resume meets the first filter item and the second filter item for any user resume after receiving the user resumes of multiple second users; wherein, for any first filter item, if the user resume meets the first filter item, the basic score corresponding to the first filter item is given, and if not, the basic score corresponding to the first filter item is not given; for any second filter item, if the user resume meets the second filter item, the highlight score corresponding to the second filter item is given, and if not, the highlight score corresponding to the second filter item is not given;
[0104] A calculation module 504 is used to calculate the sum of the basic scores corresponding to each first screening item and the highlight scores corresponding to each second screening item for any user resume, so as to obtain a total score of the user resume;
[0105] Display module 505 is used to select the user resumes with total scores greater than the first score threshold and ranked in the top N order as target resumes in descending order of total scores, and display the target resume and / or user information of the second user corresponding to the target resume on the screen, where the user information at least includes the user name and / or user ID, and N is a positive integer.
[0106] The embodiment of the present application provides a resume screening device based on an AI resume assistant. On the one hand, the AI resume assistant can perform semantic analysis on the first target statement input by the first user to obtain the second screening condition corresponding to the target position for screening the user resume. If the first user wants to set the second screening condition he or she expects, he or she only needs to enter the corresponding first target statement. The operation is simple, which reduces the workload of the recruiter. At the same time, there is no need for developers to redevelop, which reduces the development cost. On the other hand, based on the set first screening condition and the generated second screening condition, each user resume is scored to obtain the total score of each user resume, and then the target resume is screened out according to the total score of the user resume. In this way, on the basis of filtering out inappropriate resumes, user resumes that are more in line with the requirements of the first target statement (i.e., the second screening condition) can be matched first, thereby improving the accuracy of screening user resumes and helping recruiters quickly find suitable talents.
[0107] According to some embodiments of the present application, optionally, the resume screening device 50 based on the AI resume assistant may also include an automatic processing module for automatically executing a resume processing task corresponding to the score range according to the score range in which the total score of the user resume is located, and the resume processing task includes marking the user resume as unsuitable, marking the user resume as suitable, placing the user resume in an interview pending list, sending an interview invitation to the second user corresponding to the user resume, and actively initiating a chat with the second user corresponding to the user resume.
[0108] According to some embodiments of the present application, optionally, the automatic processing module can be specifically used to determine whether the total score is greater than a first score threshold. If it is less than or equal to the first score threshold, the user resume is marked as inappropriate; if it is greater than the first score threshold, the user resume is marked as appropriate; determine whether the total score is greater than a second score threshold. If it is greater than the first score threshold and less than or equal to the second score threshold, the user resume is included in the interview pending list; if it is greater than the second score threshold, an interview invitation is sent to the second user corresponding to the user resume; determine whether the total score is greater than a third score threshold. If it is greater than the third score threshold, actively initiate a chat with the second user corresponding to the user resume; the third score threshold is greater than the second score threshold, and the second score threshold is greater than the first score threshold.
[0109] According to some embodiments of the present application, optionally, the semantic parsing module 502 can be specifically used to extract keywords in the first target sentence, and generate at least one second filter item based on the keywords; if it is detected that the first user inputs a highlight score corresponding to the second filter item, then in response to the first user's input, the highlight score corresponding to the second filter item is set; if it is not detected that the first user inputs a highlight score corresponding to the second filter item, then based on the default assigned score of the highlight score, the highlight score corresponding to the second filter item is set; the first user is asked whether the second filter condition is only applicable to the target position or to multiple positions including the target position. If the first user feedback is that it is only applicable to the target position, then the second filter condition is used only as the second filter condition corresponding to the target position; if the first user feedback is that it is applicable to multiple positions including the target position, then the second filter condition is used only as the second filter condition corresponding to multiple positions.
[0110] According to some embodiments of the present application, optionally, the calculation module 504 can also be used to calculate the sum of the highlight scores corresponding to each second filter item for any user resume, and obtain the total highlight score of the user resume. The display module 505 can be used to highlight the target resume whose total highlight score is greater than the fourth score threshold and / or the user information of the second user corresponding to the target resume.
[0111] According to some embodiments of the present application, optionally, the semantic parsing module 502 can also be used to respond to the second target statement input by the first user, perform semantic parsing on the second target statement based on the AI resume assistant, and obtain a third filtering condition corresponding to the target position and / or a deletion instruction of the second filtering item, wherein the third filtering condition includes a method for filtering user resumes and includes at least one third filtering item; in response to the deletion instruction of the second filtering item, delete the corresponding second filtering item; for any third filtering item, determine whether the third filtering item is the same as the existing second filtering item, and if so, delete the third filtering item; if different, update the third filtering item to the second filtering item, and return to the step of determining whether the user resume satisfies the first filtering item and the second filtering item for any user resume.
[0112] According to some embodiments of the present application, optionally, the first screening condition includes at least one first screening item among major, education, age, gender, place of residence, salary requirements and industry; the second screening condition includes at least one second screening item among work experience, personality and hobbies, skills and certificates.
[0113] According to some embodiments of the present application, optionally, the window of the AI resume assistant is displayed floating in a preset area of the screen, and the window of the AI resume assistant remains displayed when the page is updated.
[0114] Figure 5 Each module / unit in the shown device has the function of implementing each step in the resume screening method based on AI resume assistant provided in the above method embodiment, and can achieve its corresponding technical effect. For the sake of concise description, it will not be repeated here.
[0115] 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.
[0116] 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.
[0117] 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.
[0118] 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.
[0119] 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.
[0120] 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.
[0121] 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.
[0122] 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 resume screening method based on AI resume assistant, characterized in that: include: In response to the first user's setting or default setting of the first screening condition, setting the first screening condition corresponding to the target position, the first screening condition is used to screen the user resume, and the first screening condition includes at least one first screening item; Receive a first target sentence input by a first user, and perform semantic analysis on the first target sentence based on the AI resume assistant to obtain a second screening condition corresponding to the target position, where the second screening condition is used to screen the user resume and includes at least one second screening item, and the second screening item is different from the first screening item; After receiving the user resumes of multiple second users, for any one of the user resumes, determine whether the user resume satisfies the first filter item and the second filter item; wherein, for any one of the first filter items, if the user resume satisfies the first filter item, a basic score corresponding to the first filter item is given, and if not, no basic score corresponding to the first filter item is given; for any one of the second filter items, if the user resume satisfies the second filter item, a highlight score corresponding to the second filter item is given, and if not, no highlight score corresponding to the second filter item is given; For any user resume, calculate the sum of the basic scores corresponding to each first filter item and the highlight scores corresponding to each second filter item to obtain the total score of the user resume; In descending order of total scores, the top N user resumes with total scores greater than the first score threshold are taken as target resumes, and the target resume and / or user information of the second user corresponding to the target resume are displayed on the screen, where the user information includes at least the user name and / or user ID, and N is a positive integer.
2. The method according to claim 1, characterized in that After obtaining the total score of the user's resume, the method further includes: According to the score range in which the total score of the user's resume lies, the resume processing task corresponding to the score range is automatically executed, and the resume processing task includes at least one of marking the user's resume as unsuitable, marking the user's resume as suitable, placing the user's resume in an interview pending list, sending an interview invitation to a second user corresponding to the user's resume, and actively initiating a chat with the second user corresponding to the user's resume.
3. The method according to claim 2, characterized in that According to the score range of the total score of the user's resume, automatically execute the resume processing tasks corresponding to the score range, including: Determine whether the total score is greater than a first score threshold, if it is less than or equal to the first score threshold, mark the user resume as inappropriate, if it is greater than the first score threshold, mark the user resume as appropriate; Determine whether the total score is greater than a second score threshold; if the total score is greater than the first score threshold and less than or equal to the second score threshold, place the user resume in an interview pending list; if the total score is greater than the second score threshold, send an interview invitation to the second user corresponding to the user resume; Determine whether the total score is greater than a third score threshold, and if so, actively initiate a chat with a second user corresponding to the user profile; The third score threshold is greater than the second score threshold, and the second score threshold is greater than the first score threshold.
4. The method according to claim 1, characterized in that The AI resume assistant performs semantic analysis on the first target sentence to obtain the second screening conditions corresponding to the target position, including: Extracting keywords from the first target sentence, and generating at least one second filter item based on the keywords; If it is detected that the first user inputs a highlight score corresponding to the second filter item, the highlight score corresponding to the second filter item is set in response to the input of the first user; if it is not detected that the first user inputs a highlight score corresponding to the second filter item, the highlight score corresponding to the second filter item is set based on a default assigned score of the highlight score; The first user is asked whether the second filtering condition is applicable only to the target position or to multiple positions including the target position. If the first user feedback is that it is applicable only to the target position, the second filtering condition is used only as the second filtering condition corresponding to the target position; if the first user feedback is that it is applicable to multiple positions including the target position, the second filtering condition is used only as the second filtering condition corresponding to multiple positions.
5. The method according to claim 1, characterized in that Before displaying the target resume and / or the user information of the second user corresponding to the target resume on the screen, the method further includes: For any user resume, calculate the sum of the highlight scores corresponding to each second filter item to obtain the total highlight score of the user resume; Displaying the target resume and / or the user information of the second user corresponding to the target resume on the screen includes: The target resume whose total highlight score is greater than the fourth score threshold and / or the user information of the second user corresponding to the target resume is highlighted.
6. The method according to claim 1, characterized in that The method further comprises: In response to a second target sentence input by the first user, the second target sentence is semantically parsed based on the AI resume assistant to obtain a third screening condition corresponding to the target position and / or a deletion instruction of the second screening item, wherein the third screening condition includes a method for screening user resumes and includes at least one third screening item; In response to a delete instruction of the second filter item, deleting the corresponding second filter item; For any third filter item, determine whether the third filter item is the same as the existing second filter item. If they are the same, delete the third filter item; if they are different, update the third filter item to the second filter item, and return to the step of determining whether the user resume meets the first filter item and the second filter item for any user resume.
7. The method according to claim 1, characterized in that The first screening condition includes at least one first screening item among major, education background, age, gender, place of residence, salary requirement and industry; The second screening condition includes at least one second screening item of work experience, personality and hobbies, skills and certificates.
8. The method according to claim 1, characterized in that The AI Resume Assistant's window is displayed floating in the preset area of the screen, and the AI Resume Assistant's window remains displayed when the page is updated.
9. A resume screening device based on AI resume assistant, characterized in that: include: A first setting module, configured to set a first screening condition corresponding to a target position in response to a first user setting or a default setting for a first screening condition, wherein the first screening condition is used to screen user resumes, and the first screening condition includes at least one first screening item; A semantic parsing module, used to receive a first target sentence input by a first user, and perform semantic parsing on the first target sentence based on the AI resume assistant to obtain a second screening condition corresponding to the target position, where the second screening condition is used to screen the user resume and includes at least one second screening item, and the second screening item is different from the first screening item; A judgment module is used to, after receiving the user resumes of the plurality of second users, judge, for any user resume, whether the user resume satisfies the first filter item and the second filter item; wherein, for any first filter item, if the user resume satisfies the first filter item, a basic score corresponding to the first filter item is given, and if not, no basic score corresponding to the first filter item is given; for any second filter item, if the user resume satisfies the second filter item, a highlight score corresponding to the second filter item is given, and if not, no highlight score corresponding to the second filter item is given; A calculation module, used for calculating the sum of the basic scores corresponding to each first screening item and the highlight scores corresponding to each second screening item for any user resume, to obtain a total score of the user resume; The display module is used to select the user resumes with total scores greater than the first score threshold and ranked in the top N order as target resumes in descending order of total scores, and display the target resume and / or user information of the second user corresponding to the target resume on the screen, wherein the user information at least includes the user name and / or user ID, and N is a positive integer.
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 8 is implemented.