Human resource (HR) shared resume and talent management function platform

Abstract

The application discloses a kind of HR shared resume and talent management function platform, to solve the technical problems of low recruitment efficiency, inaccuracy matching, information silos and waste of human resources in current recruitment system, including resume uploading module: for HR uploads candidate resume, resume uploading module supports multiple file formats, and can import resume data from other platforms or databases;Resume processing and labeling module: based on natural language processing (NLP) technology, the uploaded resume is automatically parsed, analyzed and classified, and each resume is labeled according to the content of the resume;Intelligent matching and recommendation module: this module uses machine learning and deep learning algorithms to analyze enterprise job requirements and resume data.The application platform breaks the information barrier between traditional HRs, improves the sharing efficiency of resumes and human resources, and provides a wider resource pool for HRs between enterprises.

Description

Technical Field

[0001] This invention relates to the field of human resource management technology, specifically to a functional platform for HR to share resumes and manage talent. Background Technology

[0002] Current recruitment platforms and human resource management systems generally rely on traditional resume screening methods, where HR personnel manually view and screen resumes, along with some basic search functions, to complete the recruitment process.

[0003] In the process of developing the invention, the inventors discovered that at least the following problems remain unresolved in existing technologies: traditional talent management platforms are inefficient in resume management, lack precise recruitment matching, have a lack of flexible resume classification and screening mechanisms, insufficient incentive mechanisms and sharing motivation, and face difficulties in talent pool management and subsequent utilization, making it difficult to integrate and analyze recruitment data. Therefore, a new technical solution needs to be designed to address these issues. Summary of the Invention

[0004] The purpose of this invention is to provide a functional platform for HR to share resumes and manage talent, in order to solve the technical problems of low recruitment efficiency, inaccurate matching, information silos and waste of talent resources that are common in current recruitment systems.

[0005] To achieve the above objectives, the present invention provides the following technical solution: a functional platform for HR to share resumes and manage talent, including a resume upload module: used by HR to upload candidate resumes, the resume upload module supports multiple file formats and can import resume data from other platforms or databases;

[0006] Resume Processing and Tagging Module: This module is based on Natural Language Processing (NLP) technology to automatically parse, analyze, and classify uploaded resumes, and tag each resume according to its content;

[0007] Intelligent Matching and Recommendation Module: This module uses machine learning and deep learning algorithms to analyze enterprise job requirements and resume data to achieve accurate matching between resumes and job openings. The matching results will generate a candidate recommendation list for HR to view.

[0008] Incentives and Rewards Module: This module rewards HR personnel who upload resumes with points based on resume matching results and candidate interview pass rates. Rewards can be in the form of cash, points, experience points, etc., to incentivize HR personnel to participate in resume sharing.

[0009] Recruitment Data Analysis and Reporting Module: This module generates multi-dimensional recruitment reports based on the platform's operational data, providing decision support for HR and enterprises;

[0010] Talent pool management module: Used for centralized management, retrieval and optimization of all resumes on the platform, supporting quick search for candidates through tags, job categories and other methods.

[0011] In a preferred embodiment of the present invention, the resume upload module includes multiple file formats such as PDF, Word, and TXT.

[0012] The resume processing and tagging module contains resume content including skills, work experience, and education. The tags assigned to each resume are "Java development", "5 years of experience" or "Master's degree".

[0013] The recruitment report in the recruitment data analysis and reporting module specifically includes recruitment effectiveness, talent demand trends, and recruitment cycle.

[0014] As a preferred embodiment of the present invention, the HR shared resume and talent management functional platform further includes a user authentication and permission management unit, a resume upload and data storage unit, an intelligent matching algorithm unit, a candidate screening and interview unit, an incentive mechanism unit, a talent pool management and data analysis unit, a feedback and optimization unit, and a platform operation and management unit.

[0015] In a preferred embodiment of the present invention, the user authentication and access control unit includes:

[0016] HR Registration Module: HR professionals can register a platform account via email or mobile phone number, complete personal information verification, and gain access to resume upload, management, and participation in incentive mechanisms.

[0017] Enterprise Authentication Module: Enterprise administrators can authenticate their companies through the platform to ensure the legality and accuracy of recruitment needs.

[0018] In a preferred embodiment of the present invention, the resume uploading and data storage unit includes:

[0019] Resume Upload Module: HR can upload candidate resumes through the platform, which supports various resume formats (PDF, Word, resume templates, etc.);

[0020] Resume categorization and tagging module: HR can tag resumes according to job requirements (such as technical stack, years of experience, special skills, etc.) and manage them by category;

[0021] Privacy protection module: The platform encrypts candidate resume information to ensure data security and privacy protection.

[0022] In a preferred embodiment of the present invention, the intelligent matching algorithm unit includes:

[0023] Natural Language Processing Module: The platform uses an NLP toolkit to parse resume text, extract key information such as keywords, skills, and work experience, and achieve deep understanding and semantic matching between job descriptions and resume content;

[0024] TF-IDF (a statistical method for text feature extraction and document similarity calculation): used to evaluate important keywords in resumes, optimize the match between candidates and positions, and calculate the similarity with job descriptions by analyzing the frequency of keywords in resumes;

[0025] Deep Learning and Recommendation Algorithm Module: The platform uses a hybrid recommendation system based on deep learning models, combined with collaborative filtering and content recommendation, to accurately match resumes and job postings, improving matching accuracy and relevance;

[0026] Reinforcement learning module: Based on user behavior data, reinforcement learning algorithms are used to optimize the recommendation strategy, enabling the system to gradually adjust the recommendation method based on feedback and improve long-term matching efficiency.

[0027] In a preferred embodiment of the present invention, the candidate screening and interview unit includes:

[0028] Resume screening module: HR filters candidates based on the platform's intelligent matching results and tag classification, and selects the most suitable candidates for interview invitation;

[0029] Interview scheduling module: HR can schedule interviews through the platform, which supports online interviews, interview progress tracking and other functions;

[0030] Interview Feedback Module: After the interview, HR can evaluate and provide feedback on candidates, helping the platform improve its matching algorithm.

[0031] In a preferred embodiment of the present invention, the incentive mechanism unit includes:

[0032] Interview pass incentive module: When a candidate passes the interview and is hired by the company, the HR will receive incentive rewards provided by the platform (such as points, cash rewards, etc.);

[0033] Rewards redemption module: HR professionals can use the points they earn to redeem platform services, advertising, or cash withdrawals, incentivizing them to participate in more resume sharing and referrals;

[0034] Points Management Module: HR personnel can view individual points records, reward history, and incentive rules within the platform for easy management and use.

[0035] As a preferred embodiment of the present invention, the talent pool management and data analysis unit

[0036] Yuan includes

[0037] Talent pool update module: All uploaded resumes will be stored in the platform's intelligent talent pool, which HR can view, search and filter at any time;

[0038] Data analytics module: The platform provides recruitment effectiveness analysis reports, such as data on resume submissions, interview pass rates, and recruitment cycles, to help HR optimize recruitment strategies;

[0039] Historical data storage module: HR can view and manage historical recruitment records. The platform provides data visualization tools to help HR make decisions based on data.

[0040] In a preferred embodiment of the present invention, the feedback and optimization unit includes:

[0041] System feedback module: HR and companies can provide feedback on the matching results, incentive mechanisms, user experience, etc. provided by the platform, and the platform will continuously optimize based on the feedback;

[0042] Algorithm optimization module: The platform continuously optimizes the intelligent matching algorithm by constantly collecting user behavior data and feedback;

[0043] The platform operation and management unit includes:

[0044] Platform monitoring module: Platform administrators can monitor the platform's operation in real time, including HR activity, resume upload status, incentive distribution, etc.

[0045] Content review and management module: The platform reviews uploaded resumes and job postings to ensure the authenticity and compliance of recruitment information.

[0046] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0047] 1. This invention platform breaks down the traditional information barriers between HR professionals, improves the efficiency of resume and talent resource sharing, and provides a broader resource pool for HR professionals across enterprises.

[0048] 2. Through intelligent matching algorithms and tag classification management, the platform can accurately screen candidates, reduce manual intervention in traditional recruitment, and significantly shorten the recruitment cycle.

[0049] 3. The incentive mechanism of this invention encourages HR to share talent information, thereby improving the platform's activity and resource mobility.

[0050] 4. The tag classification and data analysis functions of this invention platform effectively improve the scientific nature and accuracy of talent pool management, providing strong support for enterprises' long-term talent planning. Attached Figure Description

[0051] Other features, objects, and advantages of the present invention will become more apparent from the following detailed description of non-limiting embodiments with reference to the accompanying drawings:

[0052] Figure 1 This is a structural diagram of the project of the present invention;

[0053] Figure 2 This is a flowchart of the present invention. Detailed Implementation

[0054] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments.

[0055] Example 1: A functional platform for HR to share resumes and manage talent, see [link to example]. Figure 1 This includes a resume upload module: used by HR to upload candidate resumes. The resume upload module supports multiple file formats and can import resume data from other platforms or databases.

[0056] Resume Processing and Tagging Module: This module is based on Natural Language Processing (NLP) technology to automatically parse, analyze, and classify uploaded resumes, and tag each resume according to its content;

[0057] Intelligent Matching and Recommendation Module: This module uses machine learning and deep learning algorithms to analyze enterprise job requirements and resume data to achieve accurate matching between resumes and job openings. The matching results will generate a candidate recommendation list for HR to view.

[0058] Incentives and Rewards Module: This module rewards HR personnel who upload resumes with points based on resume matching results and candidate interview pass rates. Rewards can be in the form of cash, points, experience points, etc., to incentivize HR personnel to participate in resume sharing.

[0059] Recruitment Data Analysis and Reporting Module: This module generates multi-dimensional recruitment reports based on the platform's operational data, providing decision support for HR and enterprises;

[0060] Talent pool management module: Used for centralized management, retrieval and optimization of all resumes on the platform, supporting quick search for candidates through tags, job categories and other methods.

[0061] Specifically, the resume upload module supports multiple file formats including PDF, Word, and TXT.

[0062] The resume processing and tagging module contains resume content including skills, work experience, and education. The tags for each resume are "Java development", "5 years of experience" or "Master's degree".

[0063] The recruitment report in the recruitment data analysis and reporting module includes recruitment effectiveness, talent demand trends, and recruitment cycle.

[0064] Example 2, see Figure 2

[0065] A functional platform for HR to share resumes and manage talent also includes a user authentication and permission management unit, a resume upload and data storage unit, an intelligent matching algorithm unit, a candidate screening and interview unit, an incentive mechanism unit, a talent pool management and data analysis unit, a feedback and optimization unit, and a platform operation and management unit.

[0066] Furthermore, the user authentication and access control unit includes:

[0067] HR Registration Module: HR professionals can register a platform account via email or mobile phone number, complete personal information verification, and gain access to resume upload, management, and participation in incentive mechanisms.

[0068] Enterprise Authentication Module: Enterprise administrators can authenticate their companies through the platform to ensure the legality and accuracy of recruitment needs.

[0069] Furthermore, the resume uploading and data storage unit includes:

[0070] Resume Upload Module: HR can upload candidate resumes through the platform, which supports various resume formats (PDF, Word, resume templates, etc.);

[0071] Resume categorization and tagging module: HR can tag resumes according to job requirements (such as technical stack, years of experience, special skills, etc.) and manage them by category;

[0072] Privacy protection module: The platform encrypts candidate resume information to ensure data security and privacy protection.

[0073] It is worth noting that the intelligent matching algorithm unit includes:

[0074] Natural Language Processing Module: The platform uses an NLP toolkit to parse resume text, extract key information such as keywords, skills, and work experience, and achieve deep understanding and semantic matching between job descriptions and resume content;

[0075] TF-IDF (a statistical method for text feature extraction and document similarity calculation): used to evaluate important keywords in resumes, optimize the match between candidates and positions, and calculate the similarity with job descriptions by analyzing the frequency of keywords in resumes;

[0076] Deep Learning and Recommendation Algorithm Module: The platform uses a hybrid recommendation system based on deep learning models, combined with collaborative filtering and content recommendation, to accurately match resumes and job postings, improving matching accuracy and relevance;

[0077] Reinforcement learning module: Based on user behavior data, reinforcement learning algorithms are used to optimize the recommendation strategy, enabling the system to gradually adjust the recommendation method based on feedback and improve long-term matching efficiency.

[0078] It is worth noting that the candidate screening and interview process includes:

[0079] Resume screening module: HR filters candidates based on the platform's intelligent matching results and tag classification, and selects the most suitable candidates for interview invitation;

[0080] Interview scheduling module: HR can schedule interviews through the platform, which supports online interviews, interview progress tracking and other functions;

[0081] Interview Feedback Module: After the interview, HR can evaluate and provide feedback on candidates, helping the platform improve its matching algorithm.

[0082] It is worth mentioning that the incentive mechanism unit includes:

[0083] Interview pass incentive module: When a candidate passes the interview and is hired by the company, the HR will receive incentive rewards provided by the platform (such as points, cash rewards, etc.);

[0084] Rewards redemption module: HR professionals can use the points they earn to redeem platform services, advertising, or cash withdrawals, incentivizing them to participate in more resume sharing and referrals;

[0085] Points Management Module: HR personnel can view individual points records, reward history, and incentive rules within the platform for easy management and use.

[0086] It is worth emphasizing that the talent pool management and data analysis unit includes:

[0087] Talent pool update module: All uploaded resumes will be stored in the platform's intelligent talent pool, which HR can view, search and filter at any time;

[0088] Data analytics module: The platform provides recruitment effectiveness analysis reports, such as data on resume submissions, interview pass rates, and recruitment cycles, to help HR optimize recruitment strategies;

[0089] Historical data storage module: HR can view and manage historical recruitment records. The platform provides data visualization tools to help HR make decisions based on data.

[0090] The feedback and optimization unit includes:

[0091] System feedback module: HR and companies can provide feedback on the matching results, incentive mechanisms, user experience, etc. provided by the platform, and the platform will continuously optimize based on the feedback;

[0092] Algorithm optimization module: The platform continuously optimizes the intelligent matching algorithm by constantly collecting user behavior data and feedback;

[0093] The platform operation and management unit includes:

[0094] Platform monitoring module: Platform administrators can monitor the platform's operation in real time, including HR activity, resume upload status, incentive distribution, etc.

[0095] Content review and management module: The platform reviews uploaded resumes and job postings to ensure the authenticity and compliance of recruitment information.

[0096] The foregoing has shown and described the basic principles, main features, and advantages of the present invention. It will be apparent to those skilled in the art that the invention is not limited to the details of the exemplary embodiments described above, and that the invention can be implemented in other specific forms without departing from its spirit or essential characteristics. Therefore, the embodiments should be considered illustrative and non-limiting in all respects, and the scope of the invention is defined by the appended claims rather than the foregoing description. Thus, all variations falling within the meaning and scope of equivalents of the claims are intended to be included within the scope of the invention. No reference numerals in the claims should be construed as limiting the scope of the claims.

[0097] Furthermore, it should be understood that although this specification describes embodiments, not every embodiment contains only one independent technical solution. This narrative style is merely for clarity. Those skilled in the art should consider the specification as a whole, and the technical solutions in each embodiment can also be appropriately combined to form other embodiments that can be understood by those skilled in the art.

Claims

1. A functional platform for HR resume sharing and talent management, characterized in that: Includes a resume upload module: used by HR to upload candidate resumes. The resume upload module supports multiple file formats and can import resume data from other platforms or databases; Resume Processing and Tagging Module: This module is based on Natural Language Processing (NLP) technology to automatically parse, analyze, and classify uploaded resumes, and tag each resume according to its content; Intelligent Matching and Recommendation Module: This module uses machine learning and deep learning algorithms to analyze enterprise job requirements and resume data to achieve accurate matching between resumes and job openings. The matching results will generate a candidate recommendation list for HR to view. Incentives and Rewards Module: This module rewards HR personnel who upload resumes with points based on resume matching results and candidate interview pass rates. Rewards can be in the form of cash, points, experience points, etc., to incentivize HR personnel to participate in resume sharing. Recruitment Data Analysis and Reporting Module: This module generates multi-dimensional recruitment reports based on the platform's operational data, providing decision support for HR and enterprises; Talent pool management module: Used for centralized management, retrieval and optimization of all resumes on the platform, supporting quick search for candidates through tags, job categories and other methods.

2. The HR shared resume and talent management functional platform according to claim 1, characterized in that: The resume upload module includes multiple file formats such as PDF, Word, and TXT. The resume processing and tagging module contains resume content including skills, work experience, and education. The tags assigned to each resume are "Java Development", "5 years of experience", or "Master's Degree". The recruitment report in the recruitment data analysis and reporting module specifically includes recruitment effectiveness, talent demand trends, and recruitment cycle.

3. The HR shared resume and talent management functional platform according to claim 1, characterized in that: It also includes a user authentication and permission management unit, a resume upload and data storage unit, an intelligent matching algorithm unit, a candidate screening and interview unit, an incentive mechanism unit, a talent pool management and data analysis unit, a feedback and optimization unit, and a platform operation and management unit.

4. The HR shared resume and talent management functional platform according to claim 3, characterized in that: The user authentication and access management unit includes: HR Registration Module: HR professionals can register a platform account via email or mobile phone number, complete personal information verification, and gain access to resume upload, management, and participation in incentive mechanisms. Enterprise Authentication Module: Enterprise administrators can authenticate their companies through the platform to ensure the legality and accuracy of recruitment needs.

5. The HR shared resume and talent management functional platform according to claim 3, characterized in that: The resume uploading and data storage unit includes: Resume Upload Module: HR can upload candidate resumes through the platform, which supports various resume formats (PDF, Word, resume templates, etc.); Resume categorization and tagging module: HR can tag resumes according to job requirements (such as technical stack, years of experience, special skills, etc.) and manage them by category; Privacy protection module: The platform encrypts candidate resume information to ensure data security and privacy protection.

6. The HR shared resume and talent management functional platform according to claim 3, characterized in that: The intelligent matching algorithm unit includes: Natural Language Processing Module: The platform uses an NLP toolkit to parse resume text, extract key information such as keywords, skills, and work experience, and achieve deep understanding and semantic matching between job descriptions and resume content; TF-IDF (a statistical method for text feature extraction and document similarity calculation): used to evaluate important keywords in resumes, optimize the match between candidates and positions, and calculate the similarity with job descriptions by analyzing the frequency of keywords in resumes; Deep Learning and Recommendation Algorithm Module: The platform uses a hybrid recommendation system based on deep learning models, combined with collaborative filtering and content recommendation, to accurately match resumes and job postings, improving matching accuracy and relevance; Reinforcement learning module: Based on user behavior data, reinforcement learning algorithms are used to optimize the recommendation strategy, enabling the system to gradually adjust the recommendation method based on feedback and improve long-term matching efficiency.

7. The HR shared resume and talent management functional platform according to claim 3, characterized in that: The candidate screening and interview unit includes: Resume screening module: HR filters candidates based on the platform's intelligent matching results and tag classification, and selects the most suitable candidates for interview invitation; Interview scheduling module: HR can schedule interviews through the platform, which supports online interviews, interview progress tracking and other functions; Interview Feedback Module: After the interview, HR can evaluate and provide feedback on candidates, helping the platform improve its matching algorithm.

8. The HR shared resume and talent management functional platform according to claim 3, characterized in that: The incentive mechanism unit includes: Interview pass incentive module: When a candidate passes the interview and is hired by the company, the HR will receive incentive rewards provided by the platform (such as points, cash rewards, etc.); Rewards redemption module: HR professionals can use the points they earn to redeem platform services, advertising, or cash withdrawals, incentivizing them to participate in more resume sharing and referrals; Points Management Module: HR personnel can view individual points records, reward history, and incentive rules within the platform for easy management and use.

9. The HR shared resume and talent management functional platform according to claim 3, characterized in that: The talent pool management and data analysis unit includes: Talent pool update module: All uploaded resumes will be stored in the platform's intelligent talent pool, which HR can view, search and filter at any time; Data analytics module: The platform provides recruitment effectiveness analysis reports, such as data on resume submissions, interview pass rates, and recruitment cycles, to help HR optimize recruitment strategies; Historical data storage module: HR can view and manage historical recruitment records. The platform provides data visualization tools to help HR make decisions based on data.

10. The HR shared resume and talent management functional platform according to claim 3, characterized in that: The feedback and optimization unit includes: System feedback module: HR and companies can provide feedback on the matching results, incentive mechanisms, user experience, etc. provided by the platform, and the platform will continuously optimize based on the feedback; Algorithm optimization module: The platform continuously optimizes the intelligent matching algorithm by constantly collecting user behavior data and feedback; The platform operation and management unit includes: Platform monitoring module: Platform administrators can monitor the platform's operation in real time, including HR activity, resume upload status, incentive distribution, etc. Content review and management module: The platform reviews uploaded resumes and job postings to ensure the authenticity and compliance of recruitment information.

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