Human resource service sharing platform

Abstract

The invention relates to the field of human resource service, in particular to a human resource service sharing platform which comprises a display layer, a business function layer, a platform technology layer and a data layer. According to the method, the MySQL database configuration is optimized, query and update operations are optimized, and hotspot data are stored by utilizing a cache technology, so that the data processing and storage efficiency is improved; a rich and visual user interface is provided, and the user experience effect is improved by providing a comprehensive service module and a concise and visual operation process; strong data security and privacy protection are realized; intelligent resource scheduling and management are realized; the system architecture and expansibility are flexible; rich resources and educational training support are provided; tracking and analyzing job application results; and decision quality is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of human resources services, and in particular to a human resources service sharing platform. Background Art

[0002] With the development of information technology, human resources platforms have become an important tool for corporate recruitment, training, resource management and data analysis. They also provide human resources services for college students' employment and are tools for effectively improving education quality and management efficiency. Such platforms not only provide job seekers with convenient job search and application channels, but also provide employers with efficient talent screening and services. With the advancement of Internet technology, especially the application of mobile Internet, big data analysis, cloud computing and other technologies, human resources platforms are gradually developing in the direction of intelligence and personalization.

[0003] The existing technology needs to be improved during use: Limited data processing capabilities: Some existing systems often face performance bottlenecks when processing large amounts of data, resulting in slow data analysis and report generation.

[0004] User experience needs to be improved: the user interface design is not intuitive enough and the operation process is complicated, which increases the user's learning cost and difficulty of use.

[0005] Insufficient personalized service capabilities: Lack of identification and response to employees' individual needs, and inability to provide customized human resources solutions.

[0006] Data security issues: Some platforms do not do enough to protect data, and there is a risk of information leakage.

[0007] Low level of intelligence: Most platforms lack an effective intelligent matching system and are unable to accurately match job seekers based on their abilities and interests.

[0008] Lack of educational resources: Many platforms lack sufficient educational resources and are unable to help job seekers improve their professional skills.

[0009] Therefore, those skilled in the art provide a human resources service sharing platform to solve the problems raised in the above background technology. Summary of the Invention

[0010] To solve the above technical problems, the present invention provides a comprehensive human resources service platform integrating recruitment, training, and resource library, aiming to promote the integration of industry and education, promote talent cultivation and social development. The platform collects a large amount of job information, covering popular positions and recommended positions, and also provides a human resources service sharing platform with abundant open courses and industry resources. Includes presentation layer, business function layer, platform technology layer and data layer; The presentation layer is used to present the presentation interface, contains static resources, processes presentation-related content and logic, and provides an external data interface; The business function layer includes a human resources front-end and back-end management system. The human resources front-end has modules such as homepage, login and registration, personal center, company positions, recruitment positions, workplace Q&A, open courses, and resource library. The back-end management system is used to manage users, roles, classes, corporate recruitment, resumes, job test questions, orders, resource library, courses, statistical analysis, etc. The platform's technical layer supports public and private cloud deployments, uses middleware products to decouple business architecture, and separates permission services, log services, monitoring services, and retrieval services. The data layer uses the relational database MySQL for data storage, optimizes database configuration to achieve efficient reading and writing, ensures transactionality through database transaction management, realizes read-write separation, uses cache technology to store hot data, ensures data consistency through synchronization mechanism, and is designed to be scalable.

[0011] Preferably, the platform has efficient data processing capabilities, adopts distributed computing architecture and memory computing technology, optimizes algorithms and data flow management, and achieves efficient processing of large-scale data sets and rapid response to real-time data analysis.

[0012] Preferably, the platform is equipped with an intelligent recommendation system, which integrates machine learning and data mining technologies to build an intelligent recommendation engine. By analyzing employee behavior data, skill preferences and career goals, it provides employees with customized career development paths, personalized training courses and precisely matched job opportunities.

[0013] Preferably, the platform builds a comprehensive security assurance system and deploys a multi-level security protection system including data encryption technology, fine-grained access control mechanism and real-time security audit to ensure the security and privacy of employee information.

[0014] Preferably, the platform is equipped with an adaptive learning and development platform, and develops a dynamic adaptive learning system to intelligently adjust the learning content and difficulty level based on the employee's learning progress, ability level and knowledge mastery, providing personalized learning experience and customized development path.

[0015] Preferably, the platform is equipped with a multi-dimensional performance evaluation system, designs a multi-dimensional performance evaluation framework, comprehensively considers dimensions such as employee work results, teamwork, and innovation capabilities for evaluation, and uses data analysis to provide performance feedback and development suggestions.

[0016] Preferably, the platform is equipped with a live broadcast processing system, and an integrated live broadcast processing platform is developed to support real-time training and teaching activities by optimizing network transmission protocols and video encoding technologies, ensuring smooth live broadcast content and high-definition quality.

[0017] Preferably, the platform adopts storage processing technology, has an efficient data storage architecture, uses data compression and deduplication technology to optimize storage efficiency, and reduces network bandwidth consumption through intelligent data transmission optimization.

[0018] Preferably, the implementation and deployment process of the platform includes: conducting business needs and technical environment analysis to determine the deployment mode, preparing corresponding resources, encapsulating services in containers, designing a system including master node servers and slave nodes, and using container orchestration tools to manage the container life cycle.

[0019] Preferably, in the logical architecture of the platform, the front end accesses the system through a browser and uses WebSocket for real-time communication, adopts WAF for security protection, the back end is equipped with a DDoS protection service, uses public RECS and public GSL to provide data processing and recommendation functions, connects to cloud services for data storage and processing, and performs data storage and asynchronous processing through OSS and message queues.

[0020] The technical effects and advantages of the present invention are as follows: 1. Efficient data processing and storage Data storage optimization: By optimizing the MySQL database configuration, we ensure efficient data read and write operations under limited hardware resources, and improve the efficiency of data storage and reading.

[0021] Read-write separation: By optimizing query and update operations, an efficient read-write separation mechanism is implemented, reducing the pressure on a single database instance, improving response speed, and enabling the system to respond to user requests more quickly.

[0022] Caching strategy: Use caching technology to store hot data, reduce direct access to the database, improve query efficiency and system throughput, and thus improve the overall performance of the system.

[0023] 2. High-quality user experience Presentation layer optimization: Provide a rich and intuitive user interface, including static resources such as images, styles, and scripts, to improve the user experience and enable users to use the platform more easily.

[0024] Improved business function layer: By providing comprehensive service modules, including human resources front-end and back-end management systems, we ensure that users can easily complete various operations and meet their diverse needs in human resources services.

[0025] Humanized design: The simple and intuitive operation process makes it easy for users to quickly master the use of the platform and reduce the user's learning cost.

[0026] 3. Strong data security and privacy protection Data encryption: Use encryption algorithms to protect sensitive information, ensure that data is not illegally stolen during transmission and storage, and ensure the security of user data.

[0027] Access control: Implement strict access control policies to ensure that only authorized users can access specific data and services, preventing unauthorized access.

[0028] Principle of least privilege: Limit the access rights of users and services to data, reduce potential security risks, and ensure data security through permission management.

[0029] Security Audit: Monitor system activities through the security audit mechanism, promptly detect and respond to security threats, and ensure the safe and stable operation of the system.

[0030] Data backup: Back up important data regularly to prevent data loss and ensure that data can be quickly restored in case of unexpected situations.

[0031] 4. Intelligent resource scheduling and management Intelligent scheduling: Through resource monitoring, priority scheduling, load balancing and other technical means, it ensures the stable operation of the system and the efficient use of resources, and improves the system reliability and resource utilization efficiency.

[0032] Data-driven decision support: Use data analysis tools to provide data support to management, helping them make more scientific decisions and improving the accuracy and scientific nature of decisions.

[0033] 5. Flexible system architecture and scalability Microservice architecture: Adopting microservice architecture design improves the flexibility and scalability of the system and facilitates system upgrades and maintenance.

[0034] Middleware application: Use middleware products to solve business architecture coupling problems, improve system scalability and maintainability, and reduce system complexity.

[0035] Modular design: Separate the permission service, log service, monitoring service, retrieval service, etc. to reduce the impact of individual asynchronous services on core functions and improve the stability and reliability of the system.

[0036] 6. Abundant resources and education and training support Resource library management: Provide open courses, industry resources, etc. to help job seekers improve their professional skills and enhance their competitiveness.

[0037] Course Management: Provide students and job seekers with diverse online learning resources to promote lifelong learning and personal growth, and meet users' needs for continuous self-improvement.

[0038] 7. Job search results tracking and analysis Job seeker tracking: Through the job seeker management module, students' employment status can be tracked, including employment companies, salaries and other information, providing schools with valuable employment data to help schools understand students' employment status.

[0039] Data analysis: By analyzing existing data in different dimensions, it helps school management better understand students' employment trends and development status, provides reference for future teaching and career guidance, and promotes the optimization of teaching and career guidance.

[0040] 8. Improve decision-making quality Data statistical analysis: Provide detailed data reports to management to support data-based decision-making, making decisions more scientific and reasonable.

[0041] Visual reports: Provide intuitive charts and reports, allowing management to quickly understand key indicators and make timely and accurate decisions. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] Figure 1 This is a system framework diagram of a human resources service sharing platform provided by an embodiment of the present application; Figure 2 This is a flowchart of the implementation and deployment of a human resources service sharing platform provided in an embodiment of the present application; Figure 3 This is a logical architecture diagram of a human resources service sharing platform provided in an embodiment of the present application; Figure 4 These are specific implementation steps of a human resources service sharing platform provided by an embodiment of the present application; Figure 5 This is a security architecture diagram of a human resources service sharing platform provided in an embodiment of the present application; Figure 6 This is a front-end interface of a human resources service sharing platform provided in an embodiment of the present application; Figure 7 It is a background management interface of a human resources service sharing platform provided in an embodiment of the present application. DETAILED DESCRIPTION

[0043] The present invention will be described in further detail below with reference to the accompanying drawings and specific embodiments. The embodiments of the present invention are provided for purposes of illustration and description and are not intended to be exhaustive or to limit the invention to the disclosed forms. Many modifications and variations will be apparent to those skilled in the art. The embodiments are chosen and described to better illustrate the principles of the invention and its practical application, and to enable those skilled in the art to understand the invention and design various embodiments with various modifications suitable for specific applications. Example

[0044] See also Figures 1 to 7 In this embodiment, a human resources service sharing platform is provided, including Presentation layer: The presentation layer is the interface presented to users, containing static resources such as images, styles, scripts, and attachments. The system mainly processes presentation-related content at the presentation layer. This layer is responsible for providing users with a rich variety of presentation pages, processing presentation-related logic, and providing the system's external data interface. Business Function Layer: The business function layer is responsible for presenting the system's related service modules to the upper layer, processing business logic, and accessing the system's capabilities. It mainly includes two parts: the human resources front-end and back-end management systems. The HR front desk mainly consists of modules such as homepage, login and registration, personal center, company positions, recruitment positions, workplace Q&A, open courses, and resource library; The backend management system is mainly responsible for the management of users, roles, classes, corporate recruitment, resumes, job test questions, orders, resource libraries, courses, statistical analysis, etc. Platform Technology Layer: The platform supports both public and private cloud deployments and utilizes multiple middleware products to address business architecture coupling. Decoupling significantly improves system scalability and maintainability. Separating out permission services (such as login verification), logging services, monitoring services, and search services helps reduce the dependency of individual asynchronous services on core functionality. This approach is particularly important in high-traffic access scenarios. Data layer: The HR platform supports deployment in private or public clouds, so the data layer design focuses on performance and reliability. Considering the resource limitations of a single-server environment, we adopted the following strategies: ①. Data storage optimization: The platform primarily uses the relational database MySQL (an open-source relational database management system) for data storage. For a single-machine environment, we have optimized the database configuration to ensure efficient data read and write operations with limited hardware resources. ② Transactional Guarantee: Despite being a stand-alone deployment, we still prioritize data transactional performance. Through carefully designed database transaction management, we ensure the atomicity, consistency, isolation, and durability of operations. ③. Read-write separation: In standalone mode, we optimize query and update operations to implement an efficient read-write separation mechanism to reduce the pressure on a single database instance and improve response speed. ④ Caching strategy: Considering the advantages of memory access speed, we use caching technology to store hot data, reducing direct access to the database, thereby improving query efficiency and system throughput; ⑤. Data consistency: In a single-machine deployment, we use a synchronization mechanism to ensure data consistency, avoiding data loss or inconsistency caused by single-machine failures. ⑥. Scalability considerations: Although currently deployed on a single machine, our design allows for easy expansion to more complex deployment architectures, such as clusters or distributed systems, based on business needs in the future.

[0045] Efficient data processing capabilities: This solution uses advanced distributed computing architecture and in-memory computing technology to significantly improve data processing speed, ensuring high accuracy and rapid response in real-time data analysis. By optimizing algorithms and data flow management, it can efficiently process large-scale data sets and meet enterprises' needs for immediate decision support.

[0046] Intelligent Recommendation System: This solution integrates machine learning and data mining technologies to build an intelligent recommendation engine that provides employees with customized career development paths, personalized training courses, and precisely matched job opportunities. The system analyzes employees' behavioral data, skill preferences, and career goals to provide personalized recommendations and promote their continuous growth and career development.

[0047] Comprehensive security: This solution deploys a multi-layered, comprehensive security system, including but not limited to data encryption technology, fine-grained access control mechanisms, and real-time security audits. These measures ensure the security and privacy of employee information and prevent potential data leaks and unauthorized access risks.

[0048] Adaptive Learning and Development Platform: This solution develops a dynamic, adaptive learning system that intelligently adjusts learning content and difficulty levels based on employees' learning progress, ability level, and knowledge acquisition. Leveraging advanced learning analytics, it provides employees with personalized learning experiences and customized development paths.

[0049] Multi-dimensional performance evaluation system: This solution designs and implements a multi-dimensional performance evaluation framework that comprehensively considers multiple dimensions such as employee work results, teamwork, and innovation capabilities to conduct a comprehensive assessment. Utilizing data analysis technology, it provides employees with in-depth performance feedback and development suggestions to promote their all-round growth.

[0050] Live broadcast processing system: This solution develops an integrated live broadcast processing platform to support real-time training and teaching activities, enhancing the interactivity and participation of training; by optimizing network transmission protocols and video encoding technology, it ensures the smoothness and high-definition quality of live broadcast content, thereby improving the quality and efficiency of remote teaching.

[0051] Storage and processing technology: This solution utilizes an efficient data storage architecture to enable fast access and secure storage of massive amounts of data. Advanced data compression and deduplication technologies are also employed to optimize storage efficiency and reduce storage space usage. Furthermore, intelligent data transmission optimization reduces network bandwidth consumption, saves data transmission costs, and shortens transmission times.

[0052] When using this solution: 1. Implementation and deployment process of the human resources platform (e.g. Figure 2 shown) The HR platform supports both private and public cloud deployments. Before deployment, a detailed analysis of business requirements and the technical environment is required to determine the deployment model (private or public cloud) and plan the required resources and configurations. For private deployments, dedicated servers, storage, and network resources are required. For public cloud deployments, a suitable cloud service provider must be selected, along with appropriate cloud service offerings based on needs. Databases, application services, and other middleware services are encapsulated in containers, leveraging the advantages of containerization technology to achieve rapid deployment, isolation, and portability. The system design includes a master node server responsible for coordinating and managing the entire platform, as well as multiple slave nodes for load balancing and improving service availability. Container orchestration tools are used to manage the container lifecycle, including starting, stopping, scaling, and updating services.

[0053] 2. Platform logical architecture description (such as Figure 3 shown) The logical architecture of the human resources platform consists of multiple interrelated components, providing a full range of services from user authentication to data processing. Users are first authenticated through the authentication service, and then data management and analysis are performed through various service components. The platform supports big data workloads, provides database services, object storage services, monitoring and metering services, and provides a user-friendly operation interface through the web interface component, such as Figure 3 shown.

[0054] Front-end: Users access the system through a browser, and data is communicated in real time through WebSocket (a protocol for full-duplex communication over a single TCP connection); Security protection: WAF (Web Application Firewall) is used for security protection to ensure the security of the system; Backend services: DDoS (Distributed Denial of Service) protection service is used to defend against distributed denial of service attacks, and public RECS (Recommendation System) and public GSL (Graph Service Layer) provide data processing and recommendation functions; Cloud service: The system connects to cloud services and uses cloud computing resources for data storage and processing; Data interaction: The system stores and asynchronously processes data through OSS (Object Storage Service) and message queues.

[0055] 3. Specific implementation steps (such as Figure 4 shown) ①. Platform Environment Setup: Use React (web development framework) + Vite (front-end build tool) to build the front-end environment, perform front-end development, configure servers, and deploy storage, network, and middleware. Use deployment tools to configure the host and computing node servers, middleware, and human resources management software environment for rapid deployment.

[0056] ② Resource Management and Allocation: Develop a resource monitoring system to monitor key platform indicators in real time and dynamically adjust resource allocation strategies. Utilize intelligent scheduling algorithms to prioritize resource supply for critical tasks when resources are limited.

[0057] ③、Data security and protection (such as Figure 5 shown) Data encryption and access control: Ensure data security during transmission and storage, using encryption algorithms such as AES (Advanced Encryption Standard) to encrypt sensitive data. At the same time, access control policies are implemented to restrict unauthorized access and ensure data security.

[0058] Backup and recovery mechanism: Back up data regularly and quickly restore services in the event of data loss or system failure to ensure data continuity and integrity.

[0059] Firewall and Intrusion Detection: Deploy professional firewalls and intrusion detection systems to prevent illegal network activities and protect the platform from attacks.

[0060] ④、User interaction and management system (such as Figure 6 、 7 shown) Provide users with personal center functions, including personal information management, job search, resume management, learning progress tracking and other modules.

[0061] The management system backend provides an audit management module for users, resumes, companies, courses and other related content, and also supports users to upload and share achievements and feedback related to career development.

[0062] The electrical components appearing in this article are all electrically connected to an external main controller and 220V AC power, and the main controller can be a conventional known device that controls a computer, etc. The specific implementation method of this disclosure omits the detailed description of known functions and known components. To ensure the compatibility of the equipment, the operating methods used are consistent with the parameters of marketed equipment.

[0063] Obviously, the embodiments described are only some of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field and related fields without making creative efforts should fall within the scope of protection of the present invention. Structures, devices, and operating methods not specifically described and explained in the present invention shall be implemented in accordance with conventional means in the field unless otherwise specified or limited.

Claims

1. A human resources service sharing platform, characterized by: Includes presentation layer, business function layer, platform technology layer and data layer; The presentation layer is used to present the presentation interface, contains static resources, processes presentation-related content and logic, and provides an external data interface; The business function layer includes a human resources front-end and back-end management system. The human resources front-end has modules such as homepage, login and registration, personal center, company positions, recruitment positions, workplace Q&A, open courses, and resource library. The back-end management system is used to manage users, roles, classes, corporate recruitment, resumes, job test questions, orders, resource library, courses, statistical analysis, etc. The platform's technical layer supports public and private cloud deployments, uses middleware products to decouple business architecture, and separates permission services, log services, monitoring services, and retrieval services. The data layer uses the relational database MySQL for data storage, optimizes database configuration to achieve efficient reading and writing, ensures transactionality through database transaction management, realizes read-write separation, uses cache technology to store hot data, ensures data consistency through synchronization mechanism, and is designed to be scalable.

2. A human resources service sharing platform according to claim 1, characterized in that: The platform has efficient data processing capabilities, adopts distributed computing architecture and memory computing technology, optimizes algorithms and data flow management, and achieves efficient processing of large-scale data sets and rapid response to real-time data analysis.

3. A human resources service sharing platform according to claim 1, characterized in that: The platform is equipped with an intelligent recommendation system that integrates machine learning and data mining technologies to build an intelligent recommendation engine. By analyzing employee behavior data, skill preferences and career goals, it provides employees with customized career development paths, personalized training courses and precisely matched job opportunities.

4. A human resources service sharing platform according to claim 1, characterized in that: The platform builds a comprehensive security assurance system and deploys a multi-level security protection system including data encryption technology, fine-grained access control mechanism and real-time security audit to ensure the security and privacy of employee information.

5. A human resources service sharing platform according to claim 1, characterized in that: The platform is equipped with an adaptive learning and development platform, and develops a dynamic adaptive learning system to intelligently adjust learning content and difficulty levels based on employees' learning progress, ability level and knowledge mastery, providing personalized learning experience and customized development paths.

6. A human resources service sharing platform according to claim 1, characterized in that: The platform has a multi-dimensional performance evaluation system and a multi-dimensional performance evaluation framework. It comprehensively considers dimensions such as employee work results, teamwork, and innovation capabilities for evaluation, and uses data analysis to provide performance feedback and development suggestions.

7. A human resources service sharing platform according to claim 1, characterized in that: The platform is equipped with a live broadcast processing system and develops an integrated live broadcast processing platform. By optimizing network transmission protocols and video encoding technologies, it supports real-time training and teaching activities, ensuring smooth live broadcast content and high-definition picture quality.

8. The human resources service sharing platform according to claim 1, characterized in that: The platform adopts storage processing technology, has an efficient data storage architecture, uses data compression and deduplication technology to optimize storage efficiency, and reduces network bandwidth consumption through intelligent data transmission optimization.

9. A human resources service sharing platform according to claim 1, characterized in that: The implementation and deployment process of the platform includes: conducting business needs and technical environment analysis to determine the deployment model, preparing corresponding resources, encapsulating services in containers, designing a system consisting of master node servers and slave nodes, and using container orchestration tools to manage the container lifecycle.

10. A human resources service sharing platform according to claim 1, characterized in that: In the logical architecture of the platform, the front-end accesses the system through a browser and uses WebSocket for real-time communication, adopts WAF for security protection, the back-end is equipped with DDoS protection services, uses public RECS and public GSL to provide data processing and recommendation functions, connects to cloud services for data storage and processing, and uses OSS and message queues for data storage and asynchronous processing.

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