Artificial intelligence driven occupational promotion navigation system based on mapping knowledge domain and STEAM education concept

Abstract

The invention discloses an artificial intelligence-driven occupational promotion navigation system based on a knowledge graph and an STEAM education concept, and relates to the technical field of occupational navigation systems. Comprising a data classification management module, an information grading evaluation module, a real-time data updating module, a data monitoring module, a micro-service architecture module, a security privacy protection module and a knowledge graph construction module, wherein the security privacy protection module adopts an advanced encryption technology access control strategy to ensure the security of data in transmission and storage processes; wherein the security privacy protection module processes personal sensitive information by using a differential privacy technology to protect user privacy, the security privacy protection module can protect personal information of a user, and the artificial intelligence-driven occupational promotion navigation system collects and analyzes a large amount of occupational information and user data to improve the user privacy. The intelligent navigation system needs to strengthen data protection and authority management, so that the use safety of the system is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of career navigation systems, and specifically to an artificial intelligence-driven career advancement navigation system based on knowledge graphs and STEAM education concepts. Background Art

[0002] A knowledge graph is a structured knowledge base that uses a graphical data structure to represent entities and the complex relationships between them. In the field of education, knowledge graphs can not only integrate subject knowledge, but also relate to learners' backgrounds, interests and abilities, forming a basic framework for personalized teaching. The STEAM education concept is a comprehensive education that integrates science, technology, engineering, art, mathematics and other fields. It is a transdisciplinary education concept that focuses on practice, aiming to cultivate children's comprehensive qualities, improve their hands-on ability, maximize the development of children's skills and instructions in all aspects, and cultivate creativity and problem-solving skills.

[0003] The AI-driven career advancement navigation system is a system that uses AI technology to help users plan and improve their careers. The AI-driven career advancement navigation system collects and analyzes a large amount of career information and user data, and uses technologies such as machine learning and natural language processing to provide users with personalized career development advice and path planning. The system can intelligently recommend suitable career directions and development strategies based on the user's career goals, skill levels, interests and hobbies. Now it is necessary to combine the AI-driven career navigation system, knowledge graphs and STEAM education concepts to help users develop career plans, further improve their career skills, and predict career development prospects.

[0004] On this basis, after searching the patent website, Chinese patent announcement number CN105279569A disclosed a career path navigation;

[0005] It can be seen that there are shortcomings in the above patent applications: However, the application of artificial intelligence technology in the career navigation system also has some challenges and problems. Due to the lack of protection measures in the career navigation system, there are data privacy and security issues in the system. The career navigation system requires a large amount of user data to provide personalized services, but it also increases the user's privacy risks accordingly.

[0006] To address the above problems, this paper proposes an artificial intelligence-driven career advancement navigation system based on knowledge graph and STEAM education concept. Summary of the invention

[0007] The purpose of the present invention is to provide an artificial intelligence-driven career advancement navigation system based on knowledge graph and STEAM education concept, and to adopt this device to work, so as to solve the above-mentioned background. The application of artificial intelligence technology in the career navigation system also has some challenges. Since the career navigation system lacks protection measures, the data privacy and security issues in the system are solved. The career navigation system requires a large amount of user data to provide personalized services, but it also increases the user's privacy risk accordingly.

[0008] To achieve the above objectives, the present invention provides the following technical solutions: an artificial intelligence-driven career advancement navigation system based on knowledge graph and STEAM education concept, which includes a data classification management module, an information classification evaluation module, a real-time data update module, a data monitoring module, a microservice architecture module, a security and privacy protection module and a knowledge graph construction module:

[0009] The data classification management module is used to classify and manage the collected occupational information data to prevent confusion among multiple groups of data, group and classify the information data, and facilitate subsequent hierarchical evaluation of the collected occupational information;

[0010] The information classification evaluation module is used to conduct in-depth analysis and interpretation of the data collected by the system, classify and evaluate the results according to the criteria of career planning, and obtain the collaborative work of each subsystem in the data classification management module, so as to help career managers better understand and respond to system operation and maintenance needs;

[0011] The real-time data update module can analyze and process the external big data occupational information, and then update the relevant data within the system to ensure that the overall system can update the occupational data in a timely manner and maintain the timeliness and accuracy of decision-making; and the real-time data update module can be connected to the microservice architecture module, and can update the relevant data of the microservice architecture module according to the actual situation of the outside world, so as to avoid the occurrence of user operation errors due to outdated occupational information;

[0012] The microservice architecture module is used to modularize data collection, processing, storage and analysis to ensure the independence and coordination of each part, so as to improve the stability of the overall system operation;

[0013] The security and privacy protection module is connected to the microservice architecture module, and adopts advanced encryption technology access control strategy to ensure the security of data during transmission and storage. The security and privacy protection module uses differential privacy technology to process personal sensitive information and protect user privacy, which greatly improves the overall system security. The security and privacy protection module can protect the user's personal information and prevent malicious users from stealing other users' personal information. It can also ensure the security of data during transmission and storage. The security and privacy protection module also includes a data monitoring module, which can monitor the data of the overall system.

[0014] The knowledge graph construction module is responsible for collecting, organizing and analyzing relevant data and information in the professional field, constructing a professional knowledge system, and using knowledge graph technology to represent entities such as occupations, skills, positions, industries, and the relationships between them.

[0015] Preferably, the microservice architecture module includes a data acquisition module and a data processing and analysis module, and the data collection module can collect external information, and the data analysis and processing module can analyze and process the data, including removing distortion and other interfering data in the data, to avoid unnecessary mistakes.

[0016] Preferably, the data monitoring module can be connected to the microservice architecture module, and can monitor the data in cooperation with the security and privacy protection module to prevent data anomalies from causing system disorders, thereby further strengthening the anti-theft function of the security and privacy protection module.

[0017] Preferably, the security and privacy protection module also includes a data classification and identification module, which is responsible for classifying and identifying data, distinguishing sensitive data, important data and general data. By labeling the data, the system can more effectively manage and protect data of different levels.

[0018] Preferably, the security and privacy protection module also includes an access control module, which is the core of the security and privacy protection system. It is responsible for controlling who can access the specified data. By implementing strict access control policies, the system can ensure that only authorized users can access and use the data, thereby preventing occupational data leakage and abuse;

[0019] The security and privacy protection module also includes an encryption technology module for encrypting data to ensure the confidentiality of data during storage and transmission, which can effectively prevent unauthorized personnel from accessing and stealing professional data.

[0020] Preferably, the knowledge graph construction module includes a user portrait construction module, which collects user information through user registration, questionnaires, behavior analysis, etc., and constructs a user portrait. The user portrait includes information such as the user's interests, abilities, experience, career planning, etc., which is used to provide personalized services to users.

[0021] Preferably, the knowledge graph construction module includes a career planning and navigation module, which is used to recommend suitable career directions, learning paths and career development strategies for users, provide functions such as career assessment, job matching, and skill improvement suggestions, and help users clarify their career goals and formulate implementation plans;

[0022] The knowledge graph construction module includes a learning resource recommendation module, which integrates online and offline learning resources, recommends relevant learning resources based on the user's learning needs and interest preferences, and helps users improve their professional skills and literacy.

[0023] Preferably, the knowledge graph construction module also includes a career consultation and communication module, which is used to provide career consultation services, answer users' questions on career planning, job hunting and employment, establish a user communication platform, and promote experience sharing and mutual assistance among users.

[0024] Compared with the prior art, the present invention has the following beneficial effects:

[0025] 1. The artificial intelligence driven career advancement navigation system of the present invention is a system that uses artificial intelligence technology to help users with career planning and advancement. The system is based on knowledge graphs and STEAM education concepts and is an innovative and practical platform that combines the advantages of knowledge graphs and STEAM education to provide users with personalized career planning and navigation services. The intelligent navigation system is based on in-depth analysis and modeling of information issues, establishes a variety of information organization mechanisms and process control mechanisms, perceives user needs in real time, grasps and utilizes user cognitive contexts, simulates human thinking, and guides users to locate their career information needs through reasoning analysis and other methods.

[0026] 2. The AI-driven career advancement navigation system collects and analyzes a large amount of career information and user data, and uses technologies such as machine learning and natural language processing to provide users with personalized career development advice and path planning. The intelligent navigation system needs to strengthen data protection and authority management to ensure the security and privacy of user data, prevent the leakage of user information and important career information, and improve the security of system use. The system can intelligently recommend suitable career directions and development strategies based on the user's career goals, skill level, interests and hobbies, help users develop career plans, improve professional skills, and predict career development.

[0027] 3. The system of the present invention has many application scenarios and groups. The system can be applied to users at various career stages, including newcomers to the workplace, to help them find their first job that suits them, provide career advancement advice and skill improvement paths for people in the workplace, and help middle and senior managers plan career transformation or further development strategies; the artificial intelligence-driven career advancement navigation system has personalized suggestions, and provides personalized career development suggestions based on the user's personal situation and career goals. It can be updated in real time, and through continuous learning and updating of data, it ensures that the suggestions provided are always the best. At the same time, multi-dimensional analysis takes into account changes in the career market and the improvement of user skills to provide a comprehensive career development path. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] Figure 1 This is a structural diagram of the artificial intelligence driven career advancement navigation system of the present invention;

[0029] Figure 2 This is a structural diagram of the security and privacy protection module of the system of the present invention;

[0030] Figure 3 This is a module structure diagram for building the knowledge graph of the present invention. DETAILED DESCRIPTION

[0031] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0032] In order to further understand the content of the present invention, the present invention is described in detail in conjunction with the accompanying drawings.

[0033] Example 1

[0034] Combination Figure 1 , an AI-driven career advancement navigation system based on knowledge graph and STEAM education concept, including data classification management module, information classification evaluation module, real-time data update module, data monitoring module, microservice architecture module, security and privacy protection module and knowledge graph construction module:

[0035] The data classification management module is used to classify and manage the collected occupational information data, prevent multiple groups of data from being confused, and group and classify the information data to facilitate the subsequent hierarchical evaluation of the collected occupational information;

[0036] The information classification evaluation module is used to conduct in-depth analysis and interpretation of the data collected by the system, classify and evaluate the results according to the criteria of career planning, and obtain the collaborative work of each subsystem in the data classification management module, which helps career managers better understand and respond to system operation and maintenance needs;

[0037] The real-time data update module can analyze and process the external big data occupational information, and then update the relevant data within the system to ensure that the overall system can update the occupational data in a timely manner and maintain the timeliness and accuracy of decision-making; and the real-time data update module can be connected to the microservice architecture module, and can update the relevant data of the microservice architecture module according to the actual situation of the outside world, avoiding the occurrence of user operation errors due to outdated occupational information;

[0038] The microservice architecture module is used to modularize data collection, processing, storage and analysis to ensure the independence and coordination of each part, so as to improve the stability of the overall system;

[0039] The security and privacy protection module is connected to the microservice architecture module and adopts advanced encryption technology access control strategy to ensure the security of data during transmission and storage. The security and privacy protection module uses differential privacy technology to process personal sensitive information and protect user privacy, which greatly improves the overall system security. The security and privacy protection module can protect the user's personal information and prevent malicious users from stealing other users' personal information. It can also ensure the security of data during transmission and storage. The security and privacy protection module also includes a data monitoring module, which can monitor the data of the entire system.

[0040] The knowledge graph construction module is responsible for collecting, organizing and analyzing relevant data and information in the professional field, building a professional knowledge system, and using knowledge graph technology to represent entities such as occupations, skills, positions, industries, and the relationships between them.

[0041] Example 2

[0042] Combination Figure 2 ,The microservice architecture module includes a data collection module and a data processing and analysis module. The data collection module can collect external information, and the data analysis and processing module can analyze and process the data, including removing distortion and other factors interfering with the data, to avoid unnecessary mistakes;

[0043] The data monitoring module can be connected to the microservice architecture module, and can monitor the data in coordination with the security and privacy protection module to prevent data anomalies from causing system disorders, and further strengthen the anti-theft function of the security and privacy protection module;

[0044] The security and privacy protection module also includes a data classification and identification module, which is responsible for classifying and identifying data, distinguishing between sensitive data, important data and general data. By labeling data, the system can more effectively manage and protect data of different levels;

[0045] The security and privacy protection module also includes an access control module, which is the core of the security and privacy protection system. It is responsible for controlling who can access the specified data. By implementing strict access control policies, the system can ensure that only authorized users can access and use data, thereby preventing occupational data leakage and abuse;

[0046] The security and privacy protection module also includes an encryption technology module, which is used to encrypt data to ensure the confidentiality of data during storage and transmission, and can effectively prevent unauthorized personnel from accessing and stealing professional data.

[0047] Example 3

[0048] Combination Figure 3 ,The knowledge graph building module includes a user portrait building module, which collects user information through user registration, questionnaire survey, behavior analysis, etc., and builds user portraits, which include information such as user’s interests, abilities, experience, career planning, etc., which are used to provide personalized services to users;

[0049] The knowledge graph construction module includes a career planning and navigation module, which is used to recommend suitable career directions, learning paths and career development strategies for users, and provides functions such as career assessment, job matching, and skill improvement suggestions to help users clarify their career goals and develop implementation plans;

[0050] The knowledge graph construction module includes a learning resource recommendation module, which integrates online and offline learning resources and recommends relevant learning resources based on users’ learning needs and interest preferences to help users improve their professional skills and literacy.

[0051] The knowledge graph construction module also includes a career consultation and communication module, which is used to provide career consultation services, answer users' questions about career planning, job hunting, etc., establish a user communication platform, and promote experience sharing and mutual assistance among users.

[0052] In summary, the invention proposes an artificial intelligence-driven career advancement navigation system based on knowledge graph and STEAM education concept: the artificial intelligence-driven career advancement navigation system of the invention is a system that uses artificial intelligence technology to help users plan and improve their careers. The system is based on knowledge graph and STEAM education concept, and is an innovative and practical platform. It combines the advantages of knowledge graph and STEAM education to provide users with personalized career planning and navigation services. The intelligent navigation system is based on in-depth analysis and modeling of problems in the field of information, and establishes a variety of information organization mechanisms and process control mechanisms, perceives user needs in real time, grasps and utilizes user cognitive context, simulates human thinking, and guides users to locate their career information needs through reasoning analysis and other methods;

[0053] The AI-driven career advancement navigation system collects and analyzes a large amount of career information and user data, and uses technologies such as machine learning and natural language processing to provide users with personalized career development advice and path planning. The intelligent navigation system needs to strengthen data protection and permission management to ensure the security and privacy of user data, prevent the leakage of user information and important career information, and improve the security of system use. The system can intelligently recommend suitable career directions and development strategies based on the user's career goals, skill levels, interests and hobbies, etc., to help users develop career plans, improve professional skills, and predict career development;

[0054] The system of the present invention has many application scenarios and groups. The system can be applied to users at various career stages, including newcomers to the workplace, to help them find their first job that suits them, to provide career advancement advice and skill improvement paths for people in the workplace, and to help middle and senior managers plan strategies for career transformation or further development. The artificial intelligence-driven career advancement navigation system has personalized suggestions, and provides personalized career development suggestions based on the user's personal situation and career goals. It can be updated in real time, and through continuous learning and updating of data, it ensures that the suggestions provided are always the best. At the same time, multi-dimensional analysis takes into account changes in the career market and the improvement of user skills, and provides a comprehensive career development path.

[0055] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0056] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. An artificial intelligence-driven career advancement navigation system based on knowledge graph and STEAM education concept, characterized by: It includes data classification management module, information classification evaluation module, real-time data update module, data monitoring module, microservice architecture module, security and privacy protection module and knowledge graph construction module: The data classification management module is used to classify and manage the collected occupational information data to prevent confusion among multiple groups of data, group and classify the information data, and facilitate subsequent hierarchical evaluation of the collected occupational information; The information classification evaluation module is used to conduct in-depth analysis and interpretation of the data collected by the system, classify and evaluate the results according to the criteria of career planning, and obtain the collaborative work of each subsystem in the data classification management module, so as to help career managers better understand and respond to system operation and maintenance needs; The real-time data update module can analyze and process the external big data occupational information, and then update the relevant data within the system to ensure that the overall system can update the occupational data in a timely manner and maintain the timeliness and accuracy of decision-making; and the real-time data update module can be connected to the microservice architecture module, and can update the relevant data of the microservice architecture module according to the actual situation of the outside world, so as to avoid the occurrence of user operation errors due to outdated occupational information; The microservice architecture module is used to modularize data collection, processing, storage and analysis to ensure the independence and coordination of each part, so as to improve the stability of the overall system operation; The security and privacy protection module is connected to the microservice architecture module, and adopts advanced encryption technology access control strategy to ensure the security of data during transmission and storage. The security and privacy protection module uses differential privacy technology to process personal sensitive information and protect user privacy, which greatly improves the overall system security. The security and privacy protection module can protect the user's personal information and prevent malicious users from stealing other users' personal information. It can also ensure the security of data during transmission and storage. The security and privacy protection module also includes a data monitoring module, which can monitor the data of the overall system. The knowledge graph construction module is responsible for collecting, organizing and analyzing relevant data and information in the professional field, constructing a professional knowledge system, and using knowledge graph technology to represent entities such as occupations, skills, positions, industries, and the relationships between them.

2. According to claim 1, an artificial intelligence-driven career advancement navigation system based on knowledge graph and STEAM education concept is characterized by: The microservice architecture module includes a data acquisition module and a data processing and analysis module. The data collection module can collect external information, and the data analysis and processing module can analyze and process the data, including removing distortion and other interfering factors in the data to avoid unnecessary errors.

3. According to claim 2, an artificial intelligence-driven career advancement navigation system based on knowledge graph and STEAM education concept is characterized by: The data monitoring module can be connected to the microservice architecture module, and can monitor the data in coordination with the security and privacy protection module to prevent data anomalies from causing system disorders, thereby further strengthening the anti-theft function of the security and privacy protection module.

4. According to claim 3, an artificial intelligence-driven career advancement navigation system based on knowledge graph and STEAM education concept is characterized by: The security and privacy protection module also includes a data classification and identification module, which is responsible for classifying and identifying data, distinguishing sensitive data, important data and general data. By labeling the data, the system can more effectively manage and protect data of different levels.

5. According to claim 4, an artificial intelligence driven career advancement navigation system based on knowledge graph and STEAM education concept is characterized by: The security and privacy protection module includes an access control module, which is the core of the security and privacy protection system. It is responsible for controlling who can access designated data. By implementing strict access control policies, the system can ensure that only authorized users can access and use data, thereby preventing the leakage and abuse of professional data; the security and privacy protection module also includes an encryption technology module, which is used to encrypt data to ensure the confidentiality of data during storage and transmission, and can effectively prevent unauthorized personnel from accessing and stealing professional data.

6. According to claim 5, an artificial intelligence driven career advancement navigation system based on knowledge graph and STEAM education concept is characterized by: The knowledge graph construction module includes a user portrait construction module, which collects user information through user registration, questionnaires, behavior analysis, etc., and constructs user portraits. The user portraits include information such as user interests, abilities, experiences, and career plans, and are used to provide personalized services to users.

7. The artificial intelligence driven career advancement navigation system based on knowledge graph and STEAM education concept according to claim 6 is characterized by: The knowledge graph construction module includes a career planning and navigation module, which is used to recommend suitable career directions, learning paths and career development strategies for users, and provide functions such as career assessment, job matching, and skill improvement suggestions to help users clarify their career goals and develop implementation plans; The knowledge graph construction module includes a learning resource recommendation module, which integrates online and offline learning resources, recommends relevant learning resources based on the user's learning needs and interest preferences, and helps users improve their professional skills and literacy.

8. According to claim 7, an artificial intelligence driven career advancement navigation system based on knowledge graph and STEAM education concept is characterized by: The knowledge graph construction module also includes a career consultation and communication module, which is used to provide career consultation services, answer users' questions about career planning, job hunting and employment, establish a user communication platform, and promote experience sharing and mutual assistance among users.

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