User resume matching report generation method and device, equipment and program product

Abstract

The invention provides a user resume matching report generation method and device, equipment and a program product. The method comprises the steps that after resume data of a user is obtained through a user side, an evaluation page is pushed to the user side, and the evaluation page comprises a plurality of evaluation items and evaluation options corresponding to the evaluation items; the evaluation page is generated according to a character requirement model matched with the target post in a back-end database; in response to a self-evaluation operation of the user for the evaluation page, obtaining character test data of the user, and associatively storing the character test data of the user and resume data to a back-end database; and generating a visual matching report according to the test radar map and the preset range radar map, obtaining the visual matching report, and pushing the visual matching report to terminal equipment of a manager. Through introduction of the character test data, the character characteristics of the user can be evaluated, and managers are assisted in determining the matching condition of the user and post requirements.

Description

Technical Field

[0001] The present application relates to the technical field of information processing, and in particular to a method, device and equipment, and program product for generating a matching report of a user resume. Background Art

[0002] The current website recruitment system mainly meets the talent recruitment needs of enterprises through online job posting and collecting applicants' resumes, and often relies only on keyword matching or simple screening conditions to post positions and match talents. Especially for large companies' recruitment, the high employment standards lead to very low recruitment efficiency. They only consider the matching degree between skills and positions, and do not obtain the matching degree between the user's personality and the position from the user when submitting the resume.

[0003] That is to say, many positions require not only specific skills, but also specific personality traits to ensure that employees can integrate into the team and perform well in a specific work environment. The existing resume matching method, taking the person-job matching method disclosed in application number CN202010690664.0 as an example, extracts structured features and unstructured features from the resume delivery data, and uses the structured features and unstructured features as input to match positions and resumes. The obtained person-job matching results not only match numerical features and category features, but also take into account the semantic information and interactive information between positions and resume delivery, effectively utilize the information in the resume delivery data, and improve the accuracy of person-job matching. However, the current resume matching method cannot evaluate and match the personality characteristics of applicants and provide them to management personnel, which affects the recruitment progress.

[0004] Based on this, the present application provides a method, device and equipment, and program product for generating a matching report of a user resume to solve the above-mentioned problems. Summary of the invention

[0005] The purpose of this application is to solve the shortcomings of the prior art that resume matching cannot evaluate and match the personality characteristics of applicants, affecting the recruitment progress, and to propose a method, device and equipment for generating a matching report of a user resume, and a program product.

[0006] In order to achieve the above purpose, this application adopts the following technical solutions: In a first aspect, the present application provides a method for generating a matching report of a user resume, the method comprising: After obtaining the resume data of the user through the user terminal, an evaluation page is pushed to the user terminal, wherein the evaluation page includes multiple evaluation items and evaluation options corresponding to each evaluation item; the resume data includes name, contact information and target position; the evaluation page is generated according to the personality requirement model matching the target position in the back-end database; In response to the user's self-assessment operation on the assessment page, obtaining the user's personality test data, and associating the user's personality test data with resume data and storing them in a backend database; A test radar chart is generated according to the personality test data, a preset range radar chart is generated according to the preset range data of the target position, a visual matching report is generated according to the test radar chart and the preset range radar chart, and the visual matching report is obtained and pushed to the terminal device of the manager.

[0007] The beneficial effect of this technical solution is that the evaluation provided by this application not only relies on the work experience and skills on the resume, but also takes into account the personality characteristics of the candidate, and the personality test data makes the evaluation more personalized. Each position requires not only skills, but also personality characteristics that match the position team culture and work environment. The introduction of personality test data can evaluate the user's personality characteristics and assist managers in determining their match with job requirements. By comparing the user's personality test data with the preset range data of the target position, the generated matching report helps managers to more accurately evaluate whether the candidate (user) is suitable for the job requirements. Through personality test data analysis, the degree of fit between the applicant's personality characteristics and the position can be comprehensively considered, that is, by generating a visual matching report, managers can make decisions based on visual graphs, improve the objectivity of the recruitment process, and speed up the recruitment progress. The entire process from resume acquisition to evaluation page push and then to generating matching reports is automated, reducing manual intervention and workload, and can improve recruitment efficiency.

[0008] In some possible implementations, the user's self-evaluation operation on the evaluation page is a qualitative selection operation of evaluation options for each evaluation item; The evaluation options of each evaluation item include a first evaluation option, a second evaluation option, a third evaluation option and a fourth evaluation option which are randomly arranged, and each evaluation option corresponds to a personality trait.

[0009] The beneficial effect of this technical solution is that by randomly arranging the evaluation options, user bias caused by fixed option positions can be eliminated, ensuring the objectivity and accuracy of the evaluation results. Each evaluation item corresponds to a personality trait, and the comprehensive selection of multiple evaluation items can fully reflect the user's personality characteristics. The random arrangement and qualitative selection of evaluation options make the evaluation process more fair and transparent, and enhance the management staff's trust in the matching report corresponding to the evaluation results.

[0010] In summary, through qualitative selection operations and random arrangement of assessment options, the objectivity and accuracy of personality test results are ensured, user participation and trust are enhanced, and scientific data support is provided for the recruitment process, improving recruitment efficiency and decision-making quality.

[0011] In some possible implementations, before obtaining the resume data of the user, the method further includes: When a user accesses a job posting page through a user terminal, determining whether the language currently used by the job posting page is the target language; When the currently used language is not the target language, the text content corresponding to the target language is obtained from a preset language package, and the fixed text on the job posting page is dynamically replaced; wherein the language package includes multiple groups of key-value pairs, the key in each group of key-value pairs represents an identifier of the fixed text, and the value represents the text content in the corresponding language.

[0012] The beneficial effect of this technical solution is that it can provide a more user-friendly experience by automatically detecting and adapting to the user's language preference. Users can browse and operate in a familiar language environment, which improves the usability and friendliness of the page. Through preset language packages and dynamic text replacement, supported languages ​​can be flexibly added or modified. The key-value pair structure of the language package is simple and easy to expand, and text content can be easily updated and managed. By dynamically replacing fixed text on the job posting page, the needs of users of different languages ​​can be quickly responded to, reducing user waiting time. Based on language adaptation, the resume data obtained is more accurate, providing reliable data support for subsequent resume matching and evaluation, thereby improving the overall efficiency of the recruitment process.

[0013] In some possible implementations, the associating and storing the user's personality test data and resume data in a backend database includes: When the user uploads resume data through the user terminal, the resume data is saved to the back-end database; When the personality test data of the user is obtained, the personality test data is saved in the back-end database and associated with the resume data; and the result is returned to the user end in response; The method further comprises: The personality test data is sent to a queue and data analysis is performed to obtain the predicted personality profile of the user and push it to the terminal device.

[0014] The beneficial effect of this technical solution is that by combining the user's resume data and personality test data, a more comprehensive user portrait can be generated to improve job matching. By associating and storing resume data and personality test data, the consistency and integrity of the data are ensured. The data is stored in the back-end database to ensure data security and privacy protection.

[0015] In some possible implementations, the data analysis includes: according to the weight of each personality trait in all evaluation items, obtaining a personality profile corresponding to a combination of two personality traits with the highest weight as a predicted personality profile of the user; Among them, personality traits include power traits, active traits, peaceful traits and perfect traits, and personality profiles include natural combination profiles, complementary combination profiles and contradictory combination profiles. The personality trait combinations corresponding to the natural combination profiles include power traits and active traits, peaceful traits and perfect traits. The complementary combination profiles include power traits and perfect traits, active traits and peaceful traits. The contradictory combination profiles include active traits and perfect traits, power traits and peaceful traits.

[0016] The beneficial effect of this technical solution is that through the correlation analysis of detailed personality test data and resume data, the generated personality profile can more accurately reflect the personality characteristics of the user, which helps to improve the matching degree between the user and the target position. The visual matching report generated based on the user's personality test data provides managers with intuitive and detailed reference information, which helps to personalize the recommendation and screening of candidates. Through the correlation analysis of the user's resume data and personality test data, an accurate personality profile and matching report are generated, thereby improving the accuracy of job matching and recommendation. Even if the current user does not match the target position, the manager can consider whether the user is suitable for other positions through the user's predicted personality profile.

[0017] In some possible implementations, the assessment page is generated according to the personality requirement model of the target position, and the personality requirement model is obtained according to a model classification rule, and the model classification rule includes: Using the personality requirement model indicated by the model attribute corresponding to the target position as the personality requirement model of the target position; When the personality requirement model indicated by the model attribute corresponding to the target position is empty, taking the personality requirement model indicated by the model attribute corresponding to the position of the parent category of the target position as the personality requirement model of the target position, until the personality requirement model of the target position is obtained; If no personality requirement model for the target position is found, model vacancy information is pushed to the terminal device.

[0018] The beneficial effect of this technical solution is that the evaluation page is generated according to the specific personality requirement model of the target position, ensuring that the evaluation content is more in line with the job requirements, and improving the matching degree between users and positions. When the target position does not have a clear personality requirement model, the personality requirement model of the parent classification position can be queried level by level to flexibly deal with the situation where the job classification is unclear. If no suitable personality requirement model is found in the level by level query, the model vacancy information is pushed to facilitate managers to handle and improve job classification in a timely manner.

[0019] Through the precise determination of the target position personality requirement model and the step-by-step query mechanism, the generation of the assessment page is ensured to be highly matched with the position requirements. The correlation analysis between the user personality test data and the resume data, as well as the flexible multi-language support and efficient data processing mechanism in the above technical solutions, jointly improve the user experience. Managers can simplify the screening process and improve the accuracy of job matching through intuitive visual matching reports.

[0020] In a second aspect, the present application further provides a device for generating a matching report of a user resume, the device comprising: A page push module is used to push an evaluation page to the user terminal after obtaining the user's resume data through the user terminal, wherein the evaluation page includes multiple evaluation items and evaluation options corresponding to each evaluation item; the resume data includes name, contact information and target position; the evaluation page is generated according to the personality requirement model matching the target position in the back-end database; A data storage module, for obtaining the user's personality test data in response to the user's self-assessment operation on the assessment page, and storing the user's personality test data and resume data in association with each other in a back-end database; The report push module is used to generate a test radar chart according to the personality test data, generate a preset range radar chart according to the preset range data of the target position, generate a visual matching report according to the test radar chart and the preset range radar chart, obtain the visual matching report and push it to the terminal device of the manager.

[0021] In a third aspect, the present application provides an electronic device, comprising a memory and at least one processor, the memory storing a computer program, and the at least one processor being configured to implement a method as described in any one of the first aspects when executing the computer program.

[0022] In a fourth aspect, the present application provides a computer program product, wherein the computer program product comprises a computer program, and when the computer program is executed by at least one processor, the steps of any of the above methods are implemented. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] The present application is further described below in conjunction with the accompanying drawings and embodiments.

[0024] Figure 1 A flowchart of a method for generating a matching report of a user resume provided in an embodiment of the present application.

[0025] Figure 2 A schematic diagram of a visual matching report provided in an embodiment of the present application.

[0026] Figure 3 A flowchart of another method for generating a matching report of a user resume provided in an embodiment of the present application.

[0027] Figure 4 A schematic diagram of a process for storing data association in a back-end database provided in an embodiment of the present application.

[0028] Figure 5 A schematic diagram of the structure of a matching report generating device provided in an embodiment of the present application.

[0029] Figure 6 It is a structural block diagram of an electronic device provided in an embodiment of the present application.

[0030] Figure 7 It is a structural diagram of a computer program product provided in an embodiment of the present application. DETAILED DESCRIPTION

[0031] The technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments.

[0032] In the embodiments of the present application, the words "exemplary" or "for example" are used to indicate examples, illustrations or descriptions. Any implementation or design scheme described as "exemplary" or "for example" in the embodiments of the present application should not be interpreted as being more preferred or more advantageous than other implementations or designs. Specifically, the use of words such as "exemplary" or "for example" is intended to present related concepts in a specific way.

[0033] The first, second, etc. descriptions appearing in the embodiments of the present application are only used for illustration and distinction of the description objects. There is no order, nor does it indicate any special limitation on the quantity in the embodiments of the present application, and cannot constitute any limitation on the embodiments of the present application.

[0034] The present application provides a method, device and equipment, and program product for generating a matching report of a user resume to improve related technologies. The following will be combined with the accompanying drawings and specific implementation methods to specifically describe in detail the technical solutions of the embodiments of the present application and how the technical solutions of the embodiments of the present application solve the above-mentioned technical problems. It should be noted that the embodiments described below or the technical features can be arbitrarily combined to form new embodiments, and the same or similar concepts or processes may not be repeated in some embodiments. Obviously, the described embodiments are part of the embodiments of the present application, not all of them.

[0035] Embodiment 1.

[0036] See also Figure 1 and Figure 2 , Figure 1 A flowchart of a method for generating a matching report of a user resume provided in an embodiment of the present application is provided. Figure 2 A schematic diagram of a visual matching report provided in an embodiment of the present application.

[0037] The matching report generation method of the user resume includes: S101, after obtaining the resume data of the user through the user terminal, pushing an evaluation page to the user terminal, the evaluation page including multiple evaluation items and evaluation options corresponding to each evaluation item; the resume data includes name, contact information and target position; the evaluation page is generated according to the personality requirement model matching the target position in the backend database; S102, in response to the user's self-assessment operation on the assessment page, obtaining the user's personality test data, and associating the user's personality test data with resume data and storing them in a backend database; S103, generating a test radar chart according to the personality test data, generating a preset range radar chart according to the preset range data of the target position, generating a visual matching report according to the test radar chart and the preset range radar chart, obtaining the visual matching report and pushing it to the terminal device of the manager.

[0038] User devices and terminal devices refer to physical hardware devices used by users and managers to access the Internet or run applications, such as desktop computers, mobile computers, etc. The user end refers to the application or software running on the user device, which is used to access server resources or services. The user end includes, for example, a web browser, a desktop application, and a mobile application. Correspondingly, the visual matching report pushed to the terminal device of the manager can be displayed by the server end of the terminal device (web browser, desktop application, and mobile application).

[0039] Users can make selections through user devices (such as computers, tablets, or mobile phones), such as selecting a target position on a recruitment website and submitting a resume. Specific steps may include: the user browses the position of interest on the user side, clicks to view detailed information, and clicks the "Apply" or "Submit Resume" button to upload or fill out the resume. The server receives the resume submission request and stores it in the database, and sends a confirmation email to the user. The company's management personnel (such as a human resources manager) obtains the user's resume from the server side through the server side of the terminal device, screens it, and arranges an interview.

[0040] According to the target position submitted by the user, the personality requirement model that matches the position is retrieved from the backend database. Based on the personality requirement model, an assessment page is generated, which contains multiple assessment items and assessment options for each item, and is pushed to the user. The user performs self-assessment on the assessment page to complete the personality test. The user's personality test data and resume data are associated, and the associated data is stored in the backend database. Based on the user's personality test data, the user's test radar chart is generated; based on the preset range data of the target position, the preset range radar chart of the position is generated. The user's test radar chart is matched and analyzed with the preset range radar chart of the target position to generate a visual matching report. The visual matching report can intuitively show the degree of matching between the user's personality and the target position, and the report is pushed to the terminal device of the manager.

[0041] It can be considered that the visual matching report provided by this application is not pushed to the user end. This is because managers can control the flow of information and the timing of disclosure to ensure the orderly progress of the recruitment process. Managers usually have professional recruitment and evaluation capabilities and can interpret matching reports more accurately to make more reasonable recruitment decisions. If candidates see the matching report, they may selectively present themselves based on the report results, which may affect their self-presentation during the recruitment process and thus affect the accuracy of the evaluation. Users may feel stressed or disappointed because of unsatisfactory matching results. Managers can convey information in a more humane way to help users understand the situation and provide further guidance. Managers can conduct a comprehensive evaluation based on the matching report and other evaluation tools (such as interviews, skill tests, etc.) to obtain a more comprehensive user portrait.

[0042] This embodiment has the following advantages: the evaluation not only depends on the work experience and skills on the resume, but also takes into account the personality characteristics of the candidate, and the personality test data makes the evaluation more personalized. Each position requires not only skills, but also personality characteristics that match the position team culture and work environment. The introduction of personality test data can evaluate the personality characteristics of the user and assist managers in determining their matching with the job requirements. By comparing the user's personality test data with the preset range data of the target position, the generated matching report helps managers to more accurately evaluate whether the candidate (user) is suitable for the job requirements. Through the analysis of personality test data, the compatibility of the applicant's personality characteristics with the position can be comprehensively considered, that is, by generating a visual matching report, managers can make decisions based on the visual graph, improve the objectivity of the recruitment process, and speed up the recruitment progress. The entire process from resume acquisition to evaluation page push and then to generating a matching report is automated, reducing manual intervention and workload, and can improve recruitment efficiency.

[0043] In one embodiment, the user's self-evaluation operation on the evaluation page is a qualitative selection operation of evaluation options for each evaluation item; The evaluation options of each evaluation item include a first evaluation option, a second evaluation option, a third evaluation option and a fourth evaluation option which are randomly arranged, and each evaluation option corresponds to a personality trait.

[0044] It can be understood that the user performs self-evaluation operations on each evaluation item on the evaluation page. Each evaluation item contains four evaluation options, namely the first evaluation option, the second evaluation option, the third evaluation option and the fourth evaluation option. The evaluation options are randomly arranged, and each option corresponds to a personality trait. The evaluation options in each evaluation item are randomly arranged to ensure that users will not be biased due to the fixed position of the options, thereby ensuring the objectivity of the evaluation results. For each evaluation item, the user performs a qualitative selection operation from the four randomly arranged evaluation options, that is, selects the option that best suits their own situation through subjective judgment, and selects an option that best suits their own situation.

[0045] This embodiment has the following advantages: by randomly arranging the evaluation options, user bias caused by fixed option positions can be eliminated, ensuring the objectivity and accuracy of the evaluation results. Each evaluation item corresponds to a personality trait, and the comprehensive selection of multiple evaluation items can fully reflect the personality characteristics of the user. The random arrangement and qualitative selection of evaluation options make the evaluation process more fair and transparent, and enhance the management personnel's trust in the matching report corresponding to the evaluation results.

[0046] In summary, through qualitative selection operations and random arrangement of assessment options, the objectivity and accuracy of personality test results are ensured, user participation and trust are enhanced, and scientific data support is provided for the recruitment process, improving recruitment efficiency and decision-making quality.

[0047] Among them, the randomly arranged first evaluation option, second evaluation option, third evaluation option and fourth evaluation option may refer to random arrangement using JavaScript on the client side as needed, allowing each user's client (browser) to generate different sorting.

[0048] It is worth noting that the evaluation options for each evaluation item in the embodiment of the present application must be arranged randomly. This is because the matching report generation method provided in the present application focuses more on the problem of user bias caused by the fixed position of options when the options correspond one-to-one to the personality indicators.

[0049] See also Figure 3 , Figure 3 A flowchart of another method for generating a matching report of a user resume provided in an embodiment of the present application.

[0050] In one embodiment, before obtaining the resume data of the user, the method further includes: S104, when a user accesses a job posting page through a user terminal, it is determined whether the language currently used by the job posting page is the target language; when the language currently used is the target language, S101 is executed.

[0051] S105, when the currently used language is not the target language, obtain text content corresponding to the target language from a preset language package, and dynamically replace the fixed text on the job posting page; wherein the language package includes multiple groups of key-value pairs, the key in each group of key-value pairs represents an identifier of the fixed text, and the value represents the text content in the corresponding language.

[0052] The target language refers to the standard language that users want or need to use, which is used to ensure that the user interface, text content and interactive information can be accurately understood and used by the target users. For example, the user end has a language setting option, and the user can select the preferred language as the target language in the system settings. Another example is to infer the country or region where the user is located through the user's IP address or GPS location, and then select the main language of the region as the target language. Another example is to read the default language setting of the browser and use it as the target language.

[0053] When a user accesses a job posting page through a client (such as a computer, tablet, or mobile phone), it will first detect whether the language used by the current user is the target language (i.e., the system preset standard language, such as English, Chinese, etc.). If the current language is not the target language (the preset standard language, such as English or Chinese), a dynamic replacement operation is performed. The text content corresponding to the target language is obtained from the preset language package. It can be considered that the language package contains multiple sets of key-value pairs, and the key in each key-value pair represents the identifier of the fixed text, and the value represents the text content of the identifier in the target language. The fixed text on the job posting page is dynamically replaced with the text content corresponding to the target language, thereby ensuring that the page content meets the user's language requirements. After the job posting page is correctly displayed in the target language, the user can upload his resume data through the client. Among them, the language package can be an i18n language package, thereby solving the problem of system language internationalization.

[0054] This embodiment has the following benefits: By automatically detecting and adapting to the user's language preference, a more user-friendly experience can be provided. Users can browse and operate in a familiar language environment, which improves the usability and friendliness of the page. Through preset language packages and dynamic text replacement, supported languages ​​can be flexibly added or modified. The key-value pair structure of the language package is simple and easy to expand, and text content can be easily updated and managed. By dynamically replacing fixed text on the job posting page, the needs of users of different languages ​​can be quickly responded to, reducing user waiting time. Based on language adaptation, the resume data obtained is more accurate, providing reliable data support for subsequent resume matching and evaluation, thereby improving the overall efficiency of the recruitment process.

[0055] See also Figure 4 , Figure 4 A schematic diagram of a process for storing data association in a back-end database provided in an embodiment of the present application.

[0056] In one embodiment, the associating and storing the user's personality test data and resume data in a backend database includes: S201, when the user uploads resume data through the user terminal, the resume data is saved to the backend database; S202, when the personality test data of the user is obtained, the personality test data is saved in the back-end database and associated with the resume data; and the result is returned to the user end in response; The method further comprises: S105, sending the personality test data to a queue and performing data analysis to obtain the predicted personality profile of the user and push it to the terminal device. Specifically, it can be displayed on the terminal device in the form of text or image.

[0057] A personality test page is pushed to the user end, and the page contains multiple assessment items and corresponding assessment options. The user performs self-assessment on the page and selects options for each assessment item. Personality test data is generated according to the user's selection. After the personality test data is generated, it is saved to the back-end database and associated with the previously uploaded resume data. The associated data includes resume information and personality test results. At the same time, the personality test data is sent to the data analysis queue, and the user's predicted personality profile is generated through data analysis. The generated predicted personality profile and visual matching report are pushed to the manager through the terminal device and combined to help him make decisions. In a specific application, the personality test data can be sent to the redis queue model.

[0058] The back-end database can be deployed on the enterprise's own physical server, or on a physical or virtual server provided by a third party. The provider is responsible for hardware maintenance and network management. It can also be deployed on a public cloud platform to provide flexible on-demand expansion and high availability.

[0059] This embodiment has the following advantages: By combining the user's resume data and personality test data, a more comprehensive user profile can be generated to improve job matching. By associating and storing resume data and personality test data, data consistency and integrity are ensured. Data is stored in the backend database to ensure data security and privacy protection.

[0060] At the same time, the above technical solution can assist managers in more accurately evaluating the positions suitable for candidates (users) based on their target positions. It can be understood that before the user enters the resume data, the manager does not know the user's target position, nor does he know the user's evaluation page. After the user enters the resume data, the evaluation page is automatically obtained according to the user's target position. The acquisition of the above evaluation page reduces manual intervention.

[0061] When executing S104, the obtained visual matching report is a visual report of a test radar chart and a preset range radar chart generated for the user's personality test data, which is used by managers to judge the matching between the user and the target position; at the same time, the predicted personality profile obtained in S105 is an analysis and prediction of the user's personality characteristics. It can be understood that the predicted personality profile is intended to provide a comprehensive understanding of individual personality traits and is used by managers to judge the impact of individual personality traits on other positions. Even if the current user does not match the target position, the manager can consider whether the user is suitable for other positions through the user's predicted personality profile.

[0062] In specific applications, for example, a user has many years of work experience (e.g., ten or twenty years), and the manager believes that the personality requirements of the position are not highly matched through the visual matching report. In this case, the visual matching report focuses on the requirements of the target position, and is used by the manager to judge the matching between the user and the target position; at the same time, the predicted personality profile pushed focuses on the analysis and prediction results of the user's personality characteristics. Even if the current user does not match the target position, the manager can consider whether he is suitable for other positions through the user's predicted personality profile, avoid the waste of talents, and assist the manager to more accurately evaluate the position suitable for the candidate. That is, compared with the related technology, the administrator already knows the situation of the user's evaluation page before the user enters the resume data (fills in personal identity identification information). After the user submits the resume data, this technical solution automatically generates a personality evaluation page according to the target position in the resume, ensuring the relevance and personalization of the evaluation. After the user completes the personality self-assessment, a visual matching report for the target position is generated to intuitively display the matching degree between the user and the position, and at the same time analyzes the personality test data, predicts the user's personality profile, and considers his adaptability to other potential positions.

[0063] As an example, the resume (resume data and personality test data) submitted by the user is stored in the c_resume table. The main fields include the basic information of the resume (name, phone number, work experience) and personality profile data. When the user submits the resume and saves it in the back-end database, it will be returned to a queue model for personality and job matching analysis. The queue model uses asynchronous processing and saves the results to the c_resume_analysis table. The main fields of this table include personality profile data analysis results, application job matching analysis results, and the primary key of the resume. In the form of master and child tables, managers can obtain the data of the resume and the results of the resume analysis through associated queries.

[0064] In one embodiment, the data analysis includes: according to the weight of each personality feature in all evaluation items, obtaining the personality profile corresponding to the combination of two personality features with the highest weight as the predicted personality profile of the user; Among them, personality traits include power traits, active traits, peaceful traits and perfect traits, and personality profiles include natural combination profiles, complementary combination profiles and contradictory combination profiles. The personality trait combinations corresponding to the natural combination profiles include power traits and active traits, peaceful traits and perfect traits. The complementary combination profiles include power traits and perfect traits, active traits and peaceful traits. The contradictory combination profiles include active traits and perfect traits, power traits and peaceful traits.

[0065] The user conducts self-assessment on the assessment page and selects the assessment options for each assessment item. Each assessment option corresponds to a personality trait (power trait, active trait, peaceful trait, perfect trait), and the user's personality test data is associated with the resume data and stored in the backend database. The user's personality test data is analyzed, the proportion of each personality trait in all assessment items is calculated, the combination of the two personality traits with the highest proportion is obtained, and the user's predicted personality profile is determined based on the combination.

[0066] This embodiment has the following benefits: for the user's target position, in order to solve the problem of how to assist managers to more accurately evaluate the position that candidates are suitable for, the predicted personality profile is combined with the visual matching report, and through the correlation analysis of detailed personality test data and resume data, the generated personality profile can more accurately reflect the user's personality characteristics, which helps to improve the matching degree between the user and the target position. The visual matching report generated based on the user's personality test data provides intuitive and detailed reference information for managers, which helps to personalize recommendations and screen candidates. Through the correlation analysis of the user's resume data and personality test data, an accurate personality profile and matching report are generated, thereby improving the accuracy of job matching and recommendations. Even if the current user does not match the target position, the manager can consider whether he is suitable for other positions through the user's predicted personality profile.

[0067] As an example, the user resume matching in the related technology is to divide the comprehensive matching degree of resume analysis into the following conditions: educational requirements and person-job matching results, and the weight ratio between them is, for example, 5:5. Educational requirements can be set in the added job requirements. When obtaining the resume submitted by the user, the current highest educational qualification is obtained based on data such as educational experience to match it. If it meets the requirements, 20 points will be awarded. Person-job matching is further divided into personality-job matching and work experience matching, and the proportion is defined, for example, 6:4. At the same time, after the user submits, the manager obtains a collection of the user's work experience, splits each work experience to average the proportion score; the user's years of work and whether the work experience is long are obtained through the resume data, and finally assists in keyword matching of work experience. When submitting a job, the years of work are required. For example, 3 years of work experience is required, and the job seeker's work experience is 1 year, and the score is one-third.

[0068] Unlike related technologies, the personality profile results (predicted personality profile) are brought into the comprehensive matching degree calculation of user resume matching, which occupies a certain weight. For example, the predicted personality profile has contradictory combinations (emotional fluctuations), natural combinations (potential combinations), and complementary combinations (business talents), and the scores are defined as 0, 20, and 30 points. Therefore, the personality characteristics of applicants are evaluated and matched and provided to management personnel, and resume matching is performed based on the predicted personality profile obtained, which improves the recruitment progress.

[0069] In one embodiment, the assessment page is generated based on the personality requirement model of the target position, and the personality requirement model is obtained based on a model classification rule, and the model classification rule includes: Using the personality requirement model indicated by the model attribute corresponding to the target position as the personality requirement model of the target position; When the personality requirement model indicated by the model attribute corresponding to the target position is empty, taking the personality requirement model indicated by the model attribute corresponding to the position of the parent category of the target position as the personality requirement model of the target position, until the personality requirement model of the target position is obtained; If no personality requirement model for the target position is found, model vacancy information is pushed to the terminal device.

[0070] When the model attribute corresponding to the target position clearly indicates the personality requirement model, the personality requirement model is directly used to generate the assessment page. When the model attribute corresponding to the target position does not indicate a specific personality requirement model, the personality requirement model corresponding to the parent classification position of the target position is queried upward step by step until a suitable personality requirement model is found. If no suitable personality requirement model is found in the step-by-step query, the model vacancy information is pushed to the terminal device of the manager.

[0071] This embodiment has the following advantages: an assessment page is generated according to the specific personality requirement model of the target position, ensuring that the assessment content is more in line with the position requirements, thereby improving the matching degree between the user and the position. When the target position does not have a clear personality requirement model, the personality requirement model of the parent classification position can be queried level by level to flexibly deal with the situation where the position classification is unclear. If no suitable personality requirement model is found in the level by level query, the model vacancy information is pushed to facilitate the management personnel to handle and improve the position classification in a timely manner.

[0072] Through the precise determination of the target position personality requirement model and the step-by-step query mechanism, the generation of the assessment page is ensured to be highly matched with the position requirements. The correlation analysis between the user personality test data and the resume data, as well as the flexible multi-language support and efficient data processing mechanism in the above technical solutions, jointly improve the user experience. Managers can simplify the screening process and improve the accuracy of job matching through intuitive visual matching reports.

[0073] As an example, the target position "Software Development Engineer" is detected, and the model attributes of the position are searched, and the indicated personality requirement model is found to be "Developer Model". According to the "Developer Model", the assessment items are determined to include "Problem Solving Ability", "Teamwork Spirit", "Innovation Ability", etc. Under the "Problem Solving Ability" item, four assessment options are generated, such as "I can quickly find the root cause of the problem" (corresponding to the power-type characteristics), "I like to solve problems together as a team" (corresponding to the peace-type characteristics), etc., and the order of the options is randomly arranged. Generate a page containing the above assessment items and options for users to conduct self-assessment. The user selects an option under each item, and the user's selection data is collected. The user's selection data is associated with their resume data and stored in the back-end database. Generate an assessment page based on the personality requirement model to ensure that the assessment content matches the job requirements.

[0074] Embodiment 2.

[0075] This embodiment provides a device for generating a matching report of a user resume. The specific embodiment and the technical effects achieved by the device are consistent with those described in the above-mentioned embodiment 1, and some contents will not be repeated here.

[0076] See also Figure 5 , Figure 5 A schematic diagram of the structure of a matching report generating device provided in an embodiment of the present application.

[0077] The device comprises: A page push module is used to push an evaluation page to the user terminal after obtaining the user's resume data through the user terminal, wherein the evaluation page includes multiple evaluation items and evaluation options corresponding to each evaluation item; the resume data includes name, contact information and target position; the evaluation page is generated according to the personality requirement model matching the target position in the back-end database; A data storage module, for obtaining the user's personality test data in response to the user's self-assessment operation on the assessment page, and storing the user's personality test data and resume data in association with each other in a back-end database; The report push module is used to generate a test radar chart according to the personality test data, generate a preset range radar chart according to the preset range data of the target position, generate a visual matching report according to the test radar chart and the preset range radar chart, obtain the visual matching report and push it to the terminal device of the manager.

[0078] In one embodiment, the user's self-evaluation operation on the evaluation page is a qualitative selection operation of evaluation options for each evaluation item; The evaluation options of each evaluation item include a first evaluation option, a second evaluation option, a third evaluation option and a fourth evaluation option which are randomly arranged, and each evaluation option corresponds to a personality trait.

[0079] In one embodiment, the device further comprises: The language update module is used to determine whether the language currently used by the job posting page is the target language when the user accesses the job posting page through the user terminal; when the currently used language is not the target language, obtain the text content corresponding to the target language from the preset language package, and dynamically replace the fixed text on the job posting page; wherein the language package includes multiple groups of key-value pairs, the key in each group of key-value pairs represents the identifier of the fixed text, and the value represents the text content in the corresponding language.

[0080] In one embodiment, the data storage module includes: A resume storage unit, used for saving resume data to the back-end database when the user uploads resume data through the user terminal; A test data storage unit is used to save the personality test data to the back-end database and associate it with the resume data when the personality test data of the user is obtained; and return the result to the user end in response; The device also includes: The personality profile push module is used to send the personality test data to a queue and perform data analysis to obtain the predicted personality profile of the user and push it to the terminal device.

[0081] In one embodiment, the data analysis includes: according to the weight of each personality feature in all evaluation items, obtaining the personality profile corresponding to the combination of two personality features with the highest weight as the predicted personality profile of the user; Among them, personality traits include power traits, active traits, peaceful traits and perfect traits, and personality profiles include natural combination profiles, complementary combination profiles and contradictory combination profiles. The personality trait combinations corresponding to the natural combination profiles include power traits and active traits, peaceful traits and perfect traits. The complementary combination profiles include power traits and perfect traits, active traits and peaceful traits. The contradictory combination profiles include active traits and perfect traits, power traits and peaceful traits.

[0082] In one embodiment, the assessment page is generated based on the personality requirement model of the target position, and the personality requirement model is obtained based on a model classification rule, and the model classification rule includes: Using the personality requirement model indicated by the model attribute corresponding to the target position as the personality requirement model of the target position; When the personality requirement model indicated by the model attribute corresponding to the target position is empty, taking the personality requirement model indicated by the model attribute corresponding to the position of the parent category of the target position as the personality requirement model of the target position, until the personality requirement model of the target position is obtained; If no personality requirement model for the target position is found, model vacancy information is pushed to the terminal device.

[0083] Embodiment three.

[0084] The embodiment of the present application also provides an electronic device, the specific embodiment of which is consistent with the embodiment described in the above-mentioned embodiment 1 and the technical effects achieved, and some contents will not be repeated here.

[0085] The electronic device includes a memory and at least one processor, the memory stores a computer program, and the at least one processor is configured to implement the method as described in any one of the above-mentioned embodiments when executing the computer program.

[0086] See also Figure 6 , Figure 6 It is a structural block diagram of an electronic device provided in an embodiment of the present application.

[0087] The electronic device 10 may include, for example, at least one memory 11 , at least one processor 12 , and a bus 13 connecting different platform systems.

[0088] The memory 11 may include a (computer) readable medium in the form of a volatile memory, such as a random access memory (RAM) 111 and / or a cache memory 112 , and may further include a read-only memory (ROM) 113 .

[0089] The memory 11 also stores a computer program, which can be executed by the processor 12 so that the processor 12 implements the steps of any of the above methods.

[0090] The memory 11 may also include a utility 114 having at least one program module 115, such program module 115 including but not limited to: an operating system, one or more application programs, other program modules and program data, each of which or some combination may include the implementation of a network environment.

[0091] Accordingly, the processor 12 may execute the above-mentioned computer program, and may execute the utility 114 .

[0092] The processor 12 may be implemented by one or more application specific integrated circuits (ASICs), DSPs, programmable logic devices (PLDs), complex programmable logic devices (CPLDs), field programmable gate arrays (FPGAs), or other electronic components.

[0093] Bus 13 may represent one or more of several types of bus structures, including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, a processor or a local bus using any of a variety of bus architectures.

[0094] The electronic device 10 may also communicate with one or more external devices such as a keyboard, a pointing device, a Bluetooth device, etc., and may also communicate with one or more devices that can interact with the electronic device 10, and / or communicate with any device (such as a router, a modem, etc.) that enables the electronic device 10 to communicate with one or more other computing devices. Such communication may be performed through an input / output interface 14. In addition, the electronic device 10 may also communicate with one or more networks (such as a local area network (LAN), a wide area network (WAN) and / or a public network, such as the Internet) through a network adapter 15. The network adapter 15 may communicate with other modules of the electronic device 10 through the bus 13. It should be understood that, although not shown in the figure, other hardware and / or software modules may be used in conjunction with the electronic device 10 in actual applications, including but not limited to: microcode, device drivers, redundant processors, external disk drive arrays, RAID systems, tape drives, and data backup storage platforms.

[0095] Embodiment 4.

[0096] The embodiment of the present application also provides a computer program product, the specific embodiment of which is consistent with the embodiment described in the above-mentioned embodiment 1 and the technical effects achieved, and some contents will not be repeated here.

[0097] The present application provides a computer program product, which includes a computer program. When the computer program is executed by at least one processor, the steps of any of the above methods or the functions of any of the above electronic devices are implemented.

[0098] See also Figure 7 , Figure 7 It is a structural diagram of a computer program product provided in an embodiment of the present application.

[0099] The computer program product is used to implement the steps of any of the above methods or to implement the functions of any of the above electronic devices. The computer program product may be a portable compact disk read-only memory (CD-ROM) and include program code, and may be run on a terminal device, such as a personal computer. However, the computer program product of the present invention is not limited thereto, and the computer program product may be any combination of one or more computer-readable media.

[0100] This application is explained from the perspectives of purpose of use, effectiveness, progress and novelty, and has met the functional enhancement and usage requirements emphasized by the Patent Law. The above description and drawings of this application are only the preferred embodiments of this application, and are not intended to limit this application. Therefore, all structures, devices, features, etc. that are similar or identical to this application, that is, all equivalent replacements or modifications made in accordance with the scope of the patent application of this application, should fall within the scope of protection of the patent application of this application.

Claims

1. A method for generating a matching report of a user resume, characterized in that: The method comprises: After obtaining the resume data of the user through the user terminal, an evaluation page is pushed to the user terminal, wherein the evaluation page includes multiple evaluation items and evaluation options corresponding to each evaluation item; the resume data includes name, contact information and target position; the evaluation page is generated according to the personality requirement model matching the target position in the back-end database; In response to the user's self-assessment operation on the assessment page, obtaining the user's personality test data, and associating the user's personality test data with resume data and storing them in a back-end database; A test radar chart is generated according to the personality test data, a preset range radar chart is generated according to the preset range data of the target position, a visual matching report is generated according to the test radar chart and the preset range radar chart, and the visual matching report is obtained and pushed to the terminal device of the manager.

2. The method for generating a matching report of a user resume according to claim 1, characterized in that: The user's self-evaluation operation on the evaluation page is a qualitative selection operation of the evaluation options for each evaluation item; The evaluation options of each evaluation item include a first evaluation option, a second evaluation option, a third evaluation option and a fourth evaluation option which are randomly arranged, and each evaluation option corresponds to a personality trait.

3. The method for generating a matching report of a user resume according to claim 1, characterized in that: Before obtaining the resume data of the user, the method further includes: When a user accesses a job posting page through a user terminal, determining whether the language currently used by the job posting page is the target language; When the currently used language is not the target language, the text content corresponding to the target language is obtained from a preset language package, and the fixed text on the job posting page is dynamically replaced; wherein the language package includes multiple groups of key-value pairs, the key in each group of key-value pairs represents an identifier of the fixed text, and the value represents the text content in the corresponding language.

4. The method for generating a matching report of a user resume according to claim 3, characterized in that: The associating and storing the user's personality test data and resume data in a backend database includes: When the user uploads resume data through the user terminal, the resume data is saved to the back-end database; When the personality test data of the user is obtained, the personality test data is saved in the back-end database and associated with the resume data; and the result is returned to the user end in response; The method further comprises: The personality test data is sent to a queue and data analysis is performed to obtain the predicted personality profile of the user and push it to the terminal device.

5. The method for generating a matching report of a user resume according to claim 4, characterized in that: The data analysis includes: according to the proportion of each personality feature in all evaluation items, obtaining the personality profile corresponding to the combination of two personality features with the highest proportion as the predicted personality profile of the user; Among them, personality traits include power traits, active traits, peaceful traits and perfect traits, and personality profiles include natural combination profiles, complementary combination profiles and contradictory combination profiles. The personality trait combinations corresponding to the natural combination profiles include power traits and active traits, peaceful traits and perfect traits. The complementary combination profiles include power traits and perfect traits, active traits and peaceful traits. The contradictory combination profiles include active traits and perfect traits, power traits and peaceful traits.

6. The method for generating a matching report of a user resume according to claim 1, characterized in that: The assessment page is generated according to the personality requirement model of the target position, and the personality requirement model is obtained according to the model classification rules, and the model classification rules include: Using the personality requirement model indicated by the model attribute corresponding to the target position as the personality requirement model of the target position; When the personality requirement model indicated by the model attribute corresponding to the target position is empty, taking the personality requirement model indicated by the model attribute corresponding to the position of the parent category of the target position as the personality requirement model of the target position, until the personality requirement model of the target position is obtained; If no personality requirement model for the target position is found, model vacancy information is pushed to the terminal device.

7. A device for generating a matching report of a user resume, characterized in that: The device comprises: A page push module is used to push an evaluation page to the user terminal after obtaining the user's resume data through the user terminal, wherein the evaluation page includes multiple evaluation items and evaluation options corresponding to each evaluation item; the resume data includes name, contact information and target position; the evaluation page is generated according to the personality requirement model matching the target position in the back-end database; A data storage module, for obtaining the user's personality test data in response to the user's self-assessment operation on the assessment page, and storing the user's personality test data and resume data in association with each other in a back-end database; The report push module is used to generate a test radar chart according to the personality test data, generate a preset range radar chart according to the preset range data of the target position, generate a visual matching report according to the test radar chart and the preset range radar chart, obtain the visual matching report and push it to the terminal device of the manager.

8. The device for generating a matching report of a user resume according to claim 7, characterized in that: The device also includes: The language update module is used to determine whether the language currently used by the job posting page is the target language when the user accesses the job posting page through the user terminal; when the currently used language is not the target language, obtain the text content corresponding to the target language from the preset language package, and dynamically replace the fixed text on the job posting page; wherein the language package includes multiple groups of key-value pairs, the key in each group of key-value pairs represents the identifier of the fixed text, and the value represents the text content in the corresponding language.

9. An electronic device, characterized in that: The electronic device comprises a memory and at least one processor, the memory stores a computer program, and the at least one processor is configured to implement the method according to any one of claims 1 to 6 when executing the computer program.

10. A computer program product, characterized in that The computer program product comprises a computer program, and when the computer program is executed by at least one processor, the method according to any one of claims 1 to 6 is implemented.

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