Information generation method and device, computer equipment and storage medium

Abstract

The invention belongs to the technical field of artificial intelligence, and relates to an information generation method and device, computer equipment and a storage medium. Determining a corresponding target workplace experience space and a target space plot based on the data information; collecting comprehensive behavior data of the user in the target workplace experience space; preprocessing the comprehensive behavior data to obtain target comprehensive behavior data; analyzing and processing the target comprehensive behavior data based on an analysis rule, and generating character index characteristics, environment index characteristics and technical index characteristics of the user; performing portrait construction on the character index features, the environment index features and the technical index features based on a portrait generation model to obtain an occupational portrait; and processing the occupational portrait based on a planning tool to generate an occupational planning suggestion of the user. In addition, the invention also relates to a block chain technology, and occupational planning suggestions can be stored in a block chain. According to the invention, the accuracy of the generated occupational planning suggestions is effectively improved.

Description

Technical Field

[0001] The present application relates to the field of artificial intelligence development technology and financial technology, and in particular to information generation methods, devices, computer equipment and storage media. Background Art

[0002] In the insurance industry, the application of career planning systems has become increasingly widespread. Specifically, it can be applied to evaluate the relevant information input by insurance agents to be hired and provide career planning suggestions for agents. However, although this career planning system can provide personalized guidance to a certain extent, it still has obvious low accuracy in actual application.

[0003] The current career planning systems on the market mainly formulate career planning suggestions for insurance agents by analyzing their basic career information, such as their professional personality, professional interests, and professional values. However, the core problem of such career planning systems is that their evaluation methods are often oversimplified and fail to fully and deeply consider the complexity and diversity of the insurance industry, which leads to low accuracy of the generated career planning suggestions. Summary of the invention

[0004] The purpose of the embodiments of the present application is to propose an information generation method, apparatus, computer device and storage medium to solve the technical problem that the career planning suggestions generated by the existing career planning system are of low accuracy.

[0005] In order to solve the above technical problems, the present application provides an information generation method, which adopts the following technical solution:

[0006] Obtaining user profile information; wherein the profile information at least includes basic information, career interests and career goals;

[0007] Determine a corresponding target workplace experience space based on the profile information, and determine a target space plot corresponding to the target workplace experience space;

[0008] In the process of the user entering the target workplace experience space and experiencing the target space according to the plot of the target space, collecting comprehensive behavior data of the user in the target workplace experience space;

[0009] Preprocessing the comprehensive behavior data to obtain corresponding target comprehensive behavior data;

[0010] Analyze and process the target comprehensive behavior data based on preset analysis rules to generate personality index characteristics, environmental index characteristics, and technical index characteristics corresponding to the user;

[0011] Based on a preset portrait generation model, a portrait of the personality index feature, the environmental index feature, and the technical index feature is constructed to obtain a corresponding occupational portrait;

[0012] The career profile is processed based on a preset planning tool to generate career planning suggestions corresponding to the user.

[0013] Furthermore, the step of performing portrait construction processing on the personality index characteristics, the environmental index characteristics and the technical index characteristics based on the preset portrait generation model to obtain the corresponding professional portrait specifically includes:

[0014] Get the preset career profile formula;

[0015] Get the preset model constants;

[0016] Substituting the personality index characteristics, the environmental index characteristics, the technical index characteristics and the model constants into the occupational portrait formula, and solving the occupational portrait formula through the portrait generation model to obtain a corresponding solution result;

[0017] The occupational portrait is generated based on the solution result.

[0018] Furthermore, the step of analyzing and processing the target comprehensive behavior data based on preset analysis rules to generate personality index characteristics, environmental index characteristics and technical index characteristics corresponding to the user specifically includes:

[0019] Performing personality analysis on the comprehensive behavior data based on a preset personality analysis model to generate the personality indicator characteristics corresponding to the user;

[0020] Performing environmental analysis on the comprehensive behavior data based on a preset environmental analysis strategy to generate the environmental indicator features corresponding to the user;

[0021] The comprehensive behavior data is subjected to technical analysis based on a preset technical analysis strategy to generate the technical indicator features corresponding to the user.

[0022] Furthermore, the step of preprocessing the comprehensive behavior data to obtain corresponding target comprehensive behavior data specifically includes:

[0023] Performing data cleaning processing on the comprehensive behavior data to obtain corresponding first behavior data;

[0024] Performing standardization processing on the first behavior data to obtain corresponding second behavior data;

[0025] The second behavior data is used as the target comprehensive behavior data.

[0026] Furthermore, the step of determining the corresponding target workplace experience space based on the profile information specifically includes:

[0027] Filtering out designated information corresponding to a designated information type from the data information;

[0028] Call the preset workplace experience space template library;

[0029] Filtering out a designated workplace experience space template matching the designated information from the workplace experience space template library;

[0030] The target workplace experience space is generated based on the designated workplace experience space template.

[0031] Furthermore, after the step of processing the career profile based on the preset planning tool to generate a career planning suggestion corresponding to the user, the method further includes:

[0032] Acquire career planning related data corresponding to the user;

[0033] Performing format conversion processing on the career planning related data to obtain corresponding target career planning related data;

[0034] Get a preset career planning template;

[0035] Filling the career planning template based on the target career planning related data to obtain a corresponding target career planning document;

[0036] The target career planning document is sent to the user.

[0037] Furthermore, after the step of sending the target career plan to the user, the method further includes:

[0038] Determining whether a modification request for the target career plan returned by the user is received;

[0039] If so, receiving modification data input by the user;

[0040] Modify the target career plan accordingly based on the modification data to obtain a modified target career plan;

[0041] The modified target career planning book is stored and processed.

[0042] In order to solve the above technical problems, the embodiment of the present application further provides an information generating device, which adopts the following technical solution:

[0043] The first acquisition module is used to acquire the user's profile information; wherein the profile information at least includes basic information, career interests and career goals;

[0044] A determination module, used to determine a corresponding target workplace experience space based on the data information, and determine a target space plot corresponding to the target workplace experience space;

[0045] A collection module, configured to collect comprehensive behavior data of the user in the target workplace experience space when the user enters the target workplace experience space and experiences the target space according to the plot of the target space;

[0046] A preprocessing module, used for preprocessing the comprehensive behavior data to obtain corresponding target comprehensive behavior data;

[0047] An analysis module, used to analyze and process the target comprehensive behavior data based on preset analysis rules to generate personality index characteristics, environmental index characteristics and technical index characteristics corresponding to the user;

[0048] A construction module, used to construct a portrait of the personality index feature, the environmental index feature and the technical index feature based on a preset portrait generation model to obtain a corresponding occupational portrait;

[0049] A generation module is used to process the career portrait based on a preset planning tool to generate career planning suggestions corresponding to the user.

[0050] In order to solve the above technical problems, the embodiment of the present application further provides a computer device, which adopts the following technical solution:

[0051] Obtaining user profile information; wherein the profile information at least includes basic information, career interests and career goals;

[0052] Determine a corresponding target workplace experience space based on the profile information, and determine a target space plot corresponding to the target workplace experience space;

[0053] In the process of the user entering the target workplace experience space and experiencing the target space according to the plot of the target space, collecting comprehensive behavior data of the user in the target workplace experience space;

[0054] Preprocessing the comprehensive behavior data to obtain corresponding target comprehensive behavior data;

[0055] Analyze and process the target comprehensive behavior data based on preset analysis rules to generate personality index characteristics, environmental index characteristics, and technical index characteristics corresponding to the user;

[0056] Based on a preset portrait generation model, a portrait of the personality index feature, the environmental index feature, and the technical index feature is constructed to obtain a corresponding occupational portrait;

[0057] The career profile is processed based on a preset planning tool to generate career planning suggestions corresponding to the user.

[0058] In order to solve the above technical problems, the embodiment of the present application further provides a computer-readable storage medium, which adopts the following technical solution:

[0059] Obtaining user profile information; wherein the profile information at least includes basic information, career interests and career goals;

[0060] Determine a corresponding target workplace experience space based on the profile information, and determine a target space plot corresponding to the target workplace experience space;

[0061] In the process of the user entering the target workplace experience space and experiencing the target space according to the plot of the target space, collecting comprehensive behavior data of the user in the target workplace experience space;

[0062] Preprocessing the comprehensive behavior data to obtain corresponding target comprehensive behavior data;

[0063] Analyze and process the target comprehensive behavior data based on preset analysis rules to generate personality index characteristics, environmental index characteristics, and technical index characteristics corresponding to the user;

[0064] Based on a preset portrait generation model, a portrait of the personality index feature, the environmental index feature, and the technical index feature is constructed to obtain a corresponding occupational portrait;

[0065] The career profile is processed based on a preset planning tool to generate career planning suggestions corresponding to the user.

[0066] Compared with the prior art, the embodiments of the present application have the following beneficial effects:

[0067] The present application first obtains the user's profile information; wherein the profile information includes at least basic information, career interests and career goals; then, based on the profile information, a corresponding target workplace experience space is determined, and a target space plot corresponding to the target workplace experience space is determined; in the process of the user entering the target workplace experience space and experiencing according to the target space plot, the user's comprehensive behavior data is collected in the target workplace experience space; then, the comprehensive behavior data is preprocessed to obtain corresponding target comprehensive behavior data; subsequently, the target comprehensive behavior data is analyzed and processed based on preset analysis rules to generate personality indicator characteristics, environmental indicator characteristics and technical indicator characteristics corresponding to the user; further, the personality indicator characteristics, the environmental indicator characteristics and the technical indicator characteristics are portrait-constructed based on a preset portrait generation model to obtain a corresponding career portrait; finally, the career portrait is processed based on a preset planning tool to generate a career planning suggestion corresponding to the user. The present application determines the corresponding target workplace experience space based on the acquired user information, and determines the target space plot corresponding to the target workplace experience space. Then, when the user enters the target workplace experience space and experiences it according to the target space plot, the application automatically collects the user's comprehensive behavior data. Thereafter, the target comprehensive behavior data is analyzed and processed based on the use of analysis rules. Furthermore, the personality indicator characteristics, environmental indicator characteristics, and technical indicator characteristics generated through the analysis and processing are then constructed based on the use of a portrait generation model to obtain a multi-dimensional career portrait. Finally, the career portrait is processed based on the use of a planning tool, so that career planning suggestions that match the multi-dimensional career portrait can be quickly and accurately generated, effectively improving the accuracy of the generated career planning suggestions. BRIEF DESCRIPTION OF THE DRAWINGS

[0068] In order to more clearly illustrate the scheme in the present application, a brief introduction is given below to the drawings required for use in the description of the embodiments of the present application. Obviously, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0069] Figure 1 is an exemplary system architecture diagram to which the present application may be applied;

[0070] Figure 2 A flowchart of an embodiment of the information generation method according to the present application;

[0071] Figure 3 is a schematic structural diagram of an embodiment of an information generating device according to the present application;

[0072] Figure 4It is a structural diagram of an embodiment of a computer device according to the present application. DETAILED DESCRIPTION

[0073] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by technicians in the technical field of the present application; the terms used in the specification of the application herein are only for the purpose of describing specific embodiments and are not intended to limit the present application; the terms "including" and "having" and any variations thereof in the specification and claims of the present application and the above-mentioned drawings are intended to cover non-exclusive inclusions. The terms "first", "second", etc. in the specification and claims of the present application or the above-mentioned drawings are used to distinguish different objects, not to describe a specific order.

[0074] Reference to "embodiments" herein means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present application. The appearance of the phrase in various locations in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described herein may be combined with other embodiments.

[0075] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the accompanying drawings.

[0076] like Figure 1 As shown, the system architecture 100 may include a terminal device 101, a network 102 and a server 103. The terminal device 101 may be a laptop 1011, a tablet computer 1012 or a mobile phone 1013. The network 102 is used to provide a medium for a communication link between the terminal device 101 and the server 103. The network 102 may include various connection types, such as wired, wireless communication links or optical fiber cables, etc.

[0077] The user can use the terminal device 101 to interact with the server 103 through the network 102 to receive or send messages, etc. Various communication client applications can be installed on the terminal device 101, such as web browser applications, shopping applications, search applications, instant messaging tools, email clients, social platform software, etc.

[0078] The terminal device 101 can be any electronic device with a display screen and supporting web browsing. In addition to the laptop computer 1011, tablet computer 1012 or mobile phone 1013, the terminal device 101 can also be an e-book reader, an MP3 player (Moving Picture Experts Group Audio Layer III), an MP4 (Moving Picture Experts Group Audio Layer IV), a laptop computer, a desktop computer, etc.

[0079] The server 103 may be a server that provides various services, such as a background server that provides support for a web page displayed on the terminal device 101 .

[0080] It should be noted that the information generating method provided in the embodiment of the present application is generally executed by a server / terminal device, and accordingly, the information generating device is generally arranged in the server / terminal device.

[0081] It should be understood that Figure 1 The number of terminal devices, networks and servers in the embodiment is only for illustration. Any number of terminal devices, networks and servers may be provided according to implementation requirements.

[0082] Continue to refer Figure 2 , shows a flow chart of an embodiment of the information generation method according to the present application. According to different requirements, the order of the steps in the flow chart can be changed, and some steps can be omitted. The information generation method provided in the embodiment of the present application can be applied to any scenario where information generation is required, and the information generation method can be applied to products in these scenarios, for example, information generation in the financial insurance field. The information generation method includes the following steps:

[0083] Step S201, obtaining user profile information; wherein the profile information at least includes basic information, career interests and career goals.

[0084] In this embodiment, the electronic device (eg, Figure 1The server / terminal device shown in the figure) can obtain data information through a wired connection or a wireless connection. It should be noted that the above-mentioned wireless connection method may include but is not limited to 3G / 4G / 5G connection, WiFi connection, Bluetooth connection, WiMAX connection, Zigbee connection, UWB (ultra wideband) connection, and other wireless connection methods currently known or to be developed in the future. The execution subject of this application may be a processing system for the generation function of career planning suggestions, or simply referred to as a system. In the business scenario of the insurance field, the above-mentioned user may be an insurance agent to be employed in an insurance company, also known as a prospective recruit. Users can create personal profile information in the system in advance, including basic information (such as name, age, gender, etc.), career interests and career goals. Among them, the system can provide a user-friendly interface to guide users to enter basic information, such as name, age, gender, educational background, work experience, etc. In addition, users are also required to fill in their career interests and career goals, which can be selected through a drop-down menu or entered as free text. The system stores this information in a database for subsequent analysis and use. In addition, the system can also use natural language processing technology (NLP), such as word frequency analysis, sentiment analysis, syntactic analysis, etc., to analyze the user's language style and word usage habits when filling out information, and based on the analysis results, further infer the user's personality characteristics, such as extroversion, openness, conscientiousness, etc., thereby improving the intelligence and accuracy of the generation of the user's personality characteristics.

[0085] Step S202: determining a corresponding target workplace experience space based on the data information, and determining a target space plot corresponding to the target workplace experience space.

[0086] In this embodiment. The specific implementation process of determining the corresponding target workplace experience space based on the profile information will be described in further detail in subsequent specific embodiments of this application, and will not be elaborated on here. In addition, the system can select content related to the user's interests from a preset scenario library based on the read user's profile information, such as career interests, educational background, work experience, etc., and generate a personalized target space scenario. Among them, the target space scenario may include role-playing, project collaboration, problem solving, etc. in a virtual office scene, aiming to simulate a real workplace environment. In addition, by collecting and analyzing the user's basic information, career interests, and behavioral data, the system can provide a highly personalized simulated workplace experience to meet the needs of different users.

[0087] Step S203, when the user enters the target workplace experience space and experiences the target space according to the plot of the target space, the comprehensive behavior data of the user is collected in the target workplace experience space.

[0088] In this embodiment, the system provides users with a set of pre-set simulated workplace experience spaces based on the analysis of user information. The space has pre-developed monitoring functions for the behavior of prospective recruits, so the audio data and click behaviors of prospective recruits in the space will be collected. The comprehensive behavioral data will provide a reliable basis for analysis for the system, reduce the subjective human influence factors introduced by traditional scale tests, and maximize the restoration of the true situation of prospective recruits. The plot of the space is based on the basic information of prospective recruits, avoiding the use of the same experience template for role feedback under different ages, genders, and career expectations. After the prospective recruits experience the complete process, the system will collect multi-dimensional data for subsequent accurate derivation of the prospective recruits' career portraits.

[0089] Specifically, the user enters the simulated target workplace experience space and experiences it according to the target space plot generated by the system. During the experience, the system collects comprehensive behavioral data such as audio data, video data, click behavior, eye movement trajectory, etc. of the user through sensors, cameras, microphones and other devices. These data are integrated into a unified data structure, and the integrated data obtained include but are not limited to: Task completion status: such as task completion time, quality, accuracy, etc. Interaction status: such as the frequency and quality of communication with colleagues and superiors, team collaboration, etc. Feedback and adjustment: such as user feedback on task difficulty and workplace environment, and self-adjustment based on feedback.

[0090] This application combines augmented reality technology to provide a more realistic and interactive workplace experience, allowing prospective recruits to simulate professional activities in the real world, enhancing the user's sense of immersion and learning effect, and thus making the system have long-term value for continued use. In addition, the system not only analyzes traditional data, but also integrates multimodal data such as audio analysis, eye tracking, and physiological response monitoring, which is conducive to the subsequent construction of a comprehensive multi-dimensional professional portrait.

[0091] Step S204, preprocessing the comprehensive behavior data to obtain corresponding target comprehensive behavior data.

[0092] In this embodiment, the specific implementation process of preprocessing the comprehensive behavior data to obtain the corresponding target comprehensive behavior data will be described in further detail in subsequent specific embodiments of the present application, and will not be elaborated on here.

[0093] Step S205, analyzing and processing the target comprehensive behavior data based on preset analysis rules to generate personality index characteristics, environmental index characteristics and technical index characteristics corresponding to the user.

[0094] In this embodiment, the above-mentioned specific implementation process of analyzing and processing the target comprehensive behavior data based on preset analysis rules to generate personality indicator characteristics, environmental indicator characteristics and technical indicator characteristics corresponding to the user will be further described in detail in subsequent specific embodiments of the present application and will not be elaborated in detail here.

[0095] Step S206, constructing a portrait of the personality index feature, the environmental index feature and the technical index feature based on a preset portrait generation model to obtain a corresponding occupational portrait.

[0096] In this embodiment, the above-mentioned specific implementation process of constructing portraits of the personality indicator characteristics, the environmental indicator characteristics and the technical indicator characteristics based on the preset portrait generation model to obtain the corresponding professional portrait will be further described in detail in the subsequent specific embodiments of this application and will not be elaborated here.

[0097] Step S207: Process the career profile based on a preset planning tool to generate career planning suggestions corresponding to the user.

[0098] In this embodiment, the above-mentioned planning tool is a pre-built advisory module for intelligent career planning based on the career profile of prospective recruits. The planning tool uses technologies such as knowledge graphs to provide users with personalized career development suggestions. Career development suggestions may include career path selection, skill improvement plans, career development goals, etc. Among them, a knowledge graph covering information such as career paths, skill requirements, and industry trends is pre-built. This includes collecting information from multiple channels such as public data sources, industry reports, and expert interviews, and performing structured processing. And develop a recommendation algorithm based on the knowledge graph, which can retrieve and match the most relevant career development suggestions from the knowledge graph based on the user's career profile.

[0099] Specifically, the generation method of career path selection may include: based on the career profile of the prospective recruit, the planning tool recommends suitable career paths from the knowledge graph, including possible career transitions, promotion paths, etc. The generation method of skill improvement plan may include: based on the user's current skill level and the skill requirements of the target career, generate a personalized skill improvement plan, including recommended learning resources, training courses, etc. The generation method of career development goals may include: combining the user's personal vision and market trends, setting short-term and long-term career development goals, and providing recommended steps to achieve these goals.

[0100] By leveraging machine learning and natural language processing technologies, the system can provide intelligent career planning suggestions to help prospective recruits make more informed career decisions.

[0101] In addition, an easy-to-use user interface can be designed to enable users to easily view and understand career planning suggestions. Feedback from prospective recruits on career planning suggestions can be collected through questionnaires, online comments, etc., so as to continuously optimize and improve them.

[0102] The present application first obtains the user's profile information; wherein the profile information includes at least basic information, career interests and career goals; then, based on the profile information, a corresponding target workplace experience space is determined, and a target space plot corresponding to the target workplace experience space is determined; in the process of the user entering the target workplace experience space and experiencing according to the target space plot, the user's comprehensive behavior data is collected in the target workplace experience space; then, the comprehensive behavior data is preprocessed to obtain corresponding target comprehensive behavior data; subsequently, the target comprehensive behavior data is analyzed and processed based on preset analysis rules to generate personality indicator characteristics, environmental indicator characteristics and technical indicator characteristics corresponding to the user; further, the personality indicator characteristics, the environmental indicator characteristics and the technical indicator characteristics are portrait-constructed based on a preset portrait generation model to obtain a corresponding career portrait; finally, the career portrait is processed based on a preset planning tool to generate a career planning suggestion corresponding to the user. The present application determines the corresponding target workplace experience space based on the acquired user information, and determines the target space plot corresponding to the target workplace experience space. Then, when the user enters the target workplace experience space and experiences it according to the target space plot, the application automatically collects the user's comprehensive behavior data. Thereafter, the target comprehensive behavior data is analyzed and processed based on the use of analysis rules. Furthermore, the personality indicator characteristics, environmental indicator characteristics, and technical indicator characteristics generated through the analysis and processing are then constructed based on the use of a portrait generation model to obtain a multi-dimensional career portrait. Finally, the career portrait is processed based on the use of a planning tool, so that career planning suggestions that match the multi-dimensional career portrait can be quickly and accurately generated, effectively improving the accuracy of the generated career planning suggestions.

[0103] In some optional implementations, through the use of planning tools, a corresponding set of dynamic development interpretations can be generated for users based on their career profiles and market trends. The dynamic development interpretation includes multiple dimensions such as future business, management, and social contribution, and is presented in detail on an annual basis. The system can also dynamically adjust and optimize the dynamic development interpretation based on the feedback from prospective recruits and actual conditions.

[0104] Specifically, we regularly collect and analyze industry reports, job market data, etc. to understand career development trends in the next few years. Then, we update the user's career profile based on the user's latest career data (such as newly acquired skills, work experience, etc.).

[0105] Then, based on the updated career profile and market trends, the user's future career development interpretation is generated from multiple dimensions such as business, management, and social contribution. The interpretation is subdivided into annual units to show the goals, challenges, and possible opportunities at each stage. Specifically, visualization tools such as charts and timelines can be used to intuitively display the career development path and expected results of prospective recruits.

[0106] In addition, a feedback mechanism can be established to allow users to comment on and make suggestions for the dynamic development interpretation. The dynamic development interpretation can be dynamically adjusted and optimized based on the feedback from prospective recruits and actual conditions (such as market changes, personal development, etc.). In addition, machine learning technology can be used to analyze user feedback and the actual results of career development paths, thereby continuously optimizing the recommendation algorithm and interpretation generation process of the planning tool.

[0107] In some optional implementations, step S206 includes the following steps:

[0108] Get the preset career profile formula.

[0109] In this embodiment, the above-mentioned occupational portrait formula specifically includes: f(x)=b0+x+y+z, wherein b0 is a model constant, x is a personality indicator feature, y is an environmental indicator feature, and z is a technical indicator feature.

[0110] Gets the preset model constants.

[0111] In this embodiment, the model constant b0 can be determined by a training data set (including sample data of known occupational profiles). The training data set should include personality indicators, environmental indicators, technical indicators, and corresponding occupational profile labels. Then, a machine learning algorithm (such as linear regression, logistic regression, etc.) is used to fit the training data set to obtain the optimal value of the model constant b0.

[0112] The personality index characteristics, the environmental index characteristics, the technical index characteristics and the model constants are substituted into the occupational portrait formula, and the occupational portrait formula is solved by the portrait generation model to obtain a corresponding solution result.

[0113] In this embodiment, the personality index feature x, the environmental index feature y, and the technical index feature z can be substituted into the occupational portrait formula for calculation, and the occupational portrait formula can be solved using the portrait generation model, and the solution obtained is the corresponding occupational portrait. Specifically, the above-mentioned portrait generation model can adopt models such as regression analysis, neural network, and support vector machine.

[0114] The occupational portrait is generated based on the solution result.

[0115] In this embodiment, the generated solution result can be directly used as the user's professional portrait.

[0116] This application obtains a preset career portrait formula; then obtains a preset model constant; then substitutes the personality index characteristics, the environmental index characteristics, the technical index characteristics and the model constant into the career portrait formula, and solves the career portrait formula through the portrait generation model to obtain a corresponding solution result; and subsequently generates the career portrait based on the solution result. This application can realize the portrait construction processing of personality index characteristics, environmental index characteristics and technical index characteristics based on the use of the career portrait formula and the portrait generation model, so as to build a comprehensive and accurate career portrait for the user, improve the processing efficiency of the portrait construction processing, ensure the accuracy of the obtained career portrait, and provide strong support for subsequent career planning.

[0117] In some optional implementations of this embodiment, step S205 includes the following steps:

[0118] The comprehensive behavior data is subjected to personality analysis processing based on a preset personality analysis model to generate the personality indicator characteristics corresponding to the user.

[0119] In this embodiment, in the above-mentioned target workplace experience space, the system collects a large amount of comprehensive behavior data by tracking and recording the behavior of prospective recruits. These data include but are not limited to: Task completion: such as the completion time, quality, accuracy of the task, etc. Interaction: such as the frequency and quality of communication with colleagues and superiors, teamwork, etc. Feedback and adjustment: such as user feedback on task difficulty and workplace environment, and self-adjustment based on feedback, etc.

[0120] Specifically, the above-mentioned personality analysis model can specifically adopt the MBTI model. By using the MBTI model to analyze the user's interaction, feedback, adjustment and other behaviors in the target workplace experience space, the user's personality characteristics, such as communication ability, autonomy, resilience, etc., can be inferred. These personality characteristics are then used as components of the personality index vector and as the corresponding user's personality index characteristics. Exemplarily, the generated personality index characteristics may include atmosphere attention direction (extraversion, introversion), cognitive style (sensing, intuition), judgment style (reason, emotion), lifestyle (judgment, understanding), a total of 8 vector dimensions.

[0121] The comprehensive behavior data is subjected to environmental analysis processing based on a preset environmental analysis strategy to generate the environmental indicator characteristics corresponding to the user.

[0122] In this embodiment, the target workplace experience space provides a variety of workplace environment templates, and the performance of users in different environments can reflect their adaptability and preferences for different environments. The corresponding environmental indicator vector can be extracted by analyzing the task completion status and feedback of users in different environments, and the environmental indicator vector can be quantified to obtain scores such as task completion efficiency and team interaction frequency, and used as environmental indicator features corresponding to the user.

[0123] The comprehensive behavior data is subjected to technical analysis based on a preset technical analysis strategy to generate the technical indicator features corresponding to the user.

[0124] In this embodiment, in the target workplace experience space, users need to complete various technology-related tasks, such as data analysis, project management, etc. By analyzing the user's performance in the task, their technical ability level can be evaluated, such as data processing ability, project management ability, etc. These technical abilities are then quantified to obtain scores such as task completion time and code quality scores, which are used as technical indicator features corresponding to the user.

[0125] This application performs personality analysis on the comprehensive behavior data based on a preset personality analysis model to generate the personality index characteristics corresponding to the user; and performs environmental analysis on the comprehensive behavior data based on a preset environmental analysis strategy to generate the environmental index characteristics corresponding to the user; and performs technical analysis on the comprehensive behavior data based on a preset technical analysis strategy to generate the technical index characteristics corresponding to the user. This application performs personality analysis, environmental analysis, and technical analysis on the comprehensive behavior data based on the personality analysis model, environmental analysis strategy, and technical analysis strategy, respectively, so as to quickly and accurately obtain the personality index characteristics, environmental index characteristics, and technical index characteristics of the user, thereby ensuring the improvement of the generation efficiency of the index characteristics and the accuracy of the generated index characteristics, which is conducive to the subsequent accurate calculation of the user's professional portrait based on the obtained personality index characteristics, environmental index characteristics, and technical index characteristics, thereby improving the accuracy of the generated professional portrait.

[0126] In some optional implementations, step S204 includes the following steps:

[0127] The comprehensive behavior data is cleaned to obtain corresponding first behavior data.

[0128] In this embodiment, a general data cleaning tool may be used to perform data cleaning on the comprehensive behavior data to remove invalid, redundant or abnormal data, thereby obtaining corresponding first behavior data.

[0129] The first behavior data is standardized to obtain corresponding second behavior data.

[0130] In this embodiment, the first behavior data may be standardized by using a tool with a standardization function, thereby obtaining corresponding second behavior data.

[0131] The second behavior data is used as the target comprehensive behavior data.

[0132] The present application performs data cleaning on the comprehensive behavior data to obtain the corresponding first behavior data; then performs standardization on the first behavior data to obtain the corresponding second behavior data; and subsequently uses the second behavior data as the target comprehensive behavior data. The present application performs data cleaning and standardization on the comprehensive behavior data, thereby achieving fast and accurate preprocessing of the comprehensive behavior data, and ensuring the accuracy, consistency, and comparability of the generated target comprehensive behavior data. This is conducive to the subsequent accurate generation of the user's professional portrait based on the obtained target comprehensive behavior data, thereby improving the accuracy of the produced professional portrait.

[0133] In some optional implementations, the determining of the corresponding target workplace experience space based on the profile information in step S202 includes the following steps:

[0134] Specified information corresponding to a specified information type is filtered out from the data information.

[0135] In this embodiment, the above-mentioned designated type information may specifically include the type of occupational interest and the type of educational background. Correspondingly, the corresponding occupational interest (such as marketing, software development, financial management, etc.) and educational background (such as academic qualifications, majors, etc.) may be extracted from the above-mentioned data information and used as the above-mentioned designated information.

[0136] Call the preset workplace experience space template library.

[0137] In this embodiment, the workplace experience space template library is a pre-built database containing a one-to-one correspondence between career interest information, educational background information and workplace experience space templates. The templates stored in the workplace experience space template can be virtual office environments, such as offices, conference rooms, project teams, etc., and each template contains different work scenes and tasks.

[0138] A designated workplace experience space template matching the designated information is selected from the workplace experience space template library.

[0139] In this embodiment, the specified information may be used to search for templates in the workplace experience space template library, thereby filtering out a specified workplace experience space template that matches the specified information.

[0140] The target workplace experience space is generated based on the designated workplace experience space template.

[0141] In this embodiment, the above-mentioned designated workplace experience space template can be directly used as the desired target workplace experience space. In addition, the system allows prospective relevant users to customize the preset workplace experience space, such as selecting their favorite office layout, color theme, etc. The customized experience space can increase the participation and immersion of relevant users, allowing them to experience the workplace environment more realistically.

[0142] The present application filters out the designated information corresponding to the designated information type from the data information; then calls a preset workplace experience space template library; then filters out the designated workplace experience space template that matches the designated information from the workplace experience space template library; and subsequently generates the target workplace experience space based on the designated workplace experience space template. The present application filters out the designated information corresponding to the designated information type from the data information, and then based on the use of a preset workplace experience space template library, it is possible to quickly and accurately filter out the designated workplace experience space template that matches the designated information and use it as the final target workplace experience space, effectively improving the determination efficiency and screening intelligence of the target workplace experience space, and ensuring the accuracy of the obtained target workplace experience space.

[0143] In some optional implementations of this embodiment, after step S207, the electronic device may further perform the following steps:

[0144] Obtain career planning related data corresponding to the user.

[0145] In this embodiment, the above-mentioned career planning related data may at least include the user's profile information, the generated user's career portrait and career planning suggestions.

[0146] The career planning related data is formatted and processed to obtain corresponding target career planning related data.

[0147] In this embodiment, the above-mentioned career planning related data can be converted into a format suitable for generating a career planning book, such as structured text, charts, etc., so as to obtain the corresponding target career planning related data.

[0148] Get a pre-made career plan template.

[0149] In this embodiment, a suitable career planning template is selected according to the needs and preferences of the user. The career planning template is customized according to the user's preferences and the data content and format of the target career planning related data, including adding personalized elements, adjusting the layout, etc.

[0150] The career planning document template is filled based on the target career planning related data to obtain a corresponding target career planning document.

[0151] In this embodiment, the target career planning related data can be filled into the corresponding position in the career planning book template to generate the corresponding target career planning book. The filled content can also be optimized in terms of grammar, logic and format to ensure the accuracy and readability of the information. In addition, the filled content can also be typeset according to the design requirements of the career planning book template, including font, font size, paragraph spacing, chart position, etc., to improve the accuracy and adaptability of the generated target career planning book.

[0152] The target career planning document is sent to the user.

[0153] In this embodiment, a suitable notification method can be selected according to the user's preference, such as email, text message, etc. And the above target career plan is sent to the user through the selected notification method.

[0154] The present application obtains the career planning related data corresponding to the user; then performs format conversion processing on the career planning related data to obtain the corresponding target career planning related data; then obtains a preset career planning book template; subsequently fills the career planning book template based on the target career planning related data to obtain the corresponding target career planning book; and finally sends the target career planning book to the user. The present application obtains the career planning related data corresponding to the user, and performs format conversion processing on the career planning related data to obtain the target career planning related data, and then fills the preset career planning book template based on the target planning related data, so that the corresponding target career planning book can be automatically and accurately constructed, thereby improving the generation efficiency and generation intelligence of the target career planning book, and ensuring the accuracy of the obtained target career planning book. In addition, the target career planning book will be intelligently sent to the user so that the user can easily access his or her own career planning book, thereby improving the user experience.

[0155] In some optional implementations of this embodiment, after the step of sending the target career plan to the user, the electronic device may further perform the following steps:

[0156] Determine whether a modification request for the target career plan returned by the user is received.

[0157] In this embodiment, after the target career plan is generated, the target career plan will be named and stored in a designated location for subsequent management and access. The user can log in to the system and modify the generated target career plan according to personal needs. The user can trigger a preset modification button in the system to trigger a corresponding modification request for the target career plan.

[0158] If so, receiving the modification data input by the user.

[0159] In this embodiment, the user can input the data that needs to be modified corresponding to the target career plan according to actual needs, which may include, for example, adjusting career development suggestions, adding personal goals, etc.

[0160] The target career planning document is modified accordingly based on the modification data to obtain a modified target career planning document.

[0161] In this embodiment, the system can perform matching modification processing on the target career plan according to the received modification data, thereby generating a modified target career plan that meets the user's needs.

[0162] The modified target career planning book is stored and processed.

[0163] In this embodiment, there is no specific limitation on the storage method of the modified target career plan, and it can be set according to actual storage needs, for example, blockchain storage, local database storage, cloud server storage, etc.

[0164] The present application determines whether a modification request for the target career plan returned by the user is received; if so, the modification data input by the user is received; then the target career plan is modified accordingly based on the modification data to obtain a modified target career plan; and the modified target career plan is subsequently stored and processed. The present application provides convenient viewing and modification functions for the career plan. When a modification request for the target career plan triggered by the user is received, the target career plan is automatically and intelligently modified according to the modification data input by the user, so that a comprehensive, personalized and user-friendly career plan can be generated for the user, thereby improving the accuracy and generation intelligence of the career plan and improving the user experience. In addition, the modified target career plan is also intelligently stored and processed, so that the data security of the modified target career plan can be guaranteed.

[0165] In some optional implementations, the user information obtained is subject to the user's consent and complies with relevant laws and policies.

[0166] In addition, the non-Company software tools or components that appear in the embodiments of the present application are merely examples and do not represent actual use.

[0167] It should be understood that the order of execution of the steps in the above embodiment does not necessarily mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiment of the present invention.

[0168] It should be emphasized that in order to further ensure the privacy and security of the above-mentioned career planning suggestions, the above-mentioned career planning suggestions can also be stored in a node of a blockchain.

[0169] The blockchain referred to in this application is a new application model of computer technologies such as distributed data storage, peer-to-peer transmission, consensus mechanism, encryption algorithm, etc. Blockchain is essentially a decentralized database, a string of data blocks generated by cryptographic methods. Each data block contains a batch of network transaction information, which is used to verify the validity of its information (anti-counterfeiting) and generate the next block. Blockchain can include the underlying blockchain platform, platform product service layer, and application service layer.

[0170] The embodiments of the present application can acquire and process relevant data based on artificial intelligence technology. Among them, artificial intelligence (AI) is the theory, method, technology and application system that uses digital computers or machines controlled by digital computers to simulate, extend and expand human intelligence, perceive the environment, acquire knowledge and use knowledge to obtain the best results.

[0171] AI basic technologies generally include sensors, dedicated AI chips, cloud computing, distributed storage, big data processing technology, operation / interaction systems, mechatronics, etc. AI software technologies mainly include computer vision technology, robotics technology, biometrics technology, speech processing technology, natural language processing technology, and machine learning / deep learning.

[0172] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through computer-readable instructions, and the computer-readable instructions can be stored in a computer-readable storage medium. When the program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, the aforementioned storage medium can be a non-volatile storage medium such as a disk, an optical disk, a read-only memory (ROM), or a random access memory (RAM).

[0173] It should be understood that, although the steps in the flowchart of the accompanying drawings are displayed in sequence as indicated by the arrows, these steps are not necessarily executed in sequence in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least a part of the steps in the flowchart of the accompanying drawings may include multiple sub-steps or multiple stages, and these sub-steps or stages are not necessarily executed at the same time, but can be executed at different times, and their execution order is not necessarily sequential, but can be executed in turn or alternately with other steps or at least a part of the sub-steps or stages of other steps.

[0174] Further references Figure 3 , as a response to the above Figure 2 The present application provides an embodiment of an information generating device, and the device embodiment is similar to Figure 2 Corresponding to the method embodiment shown, the device can be specifically applied to various electronic devices.

[0175] like Figure 3 As shown, the information generating device 300 described in this embodiment includes: a first acquisition module 301, a determination module 302, a collection module 303, a preprocessing module 304, an analysis module 305, a construction module 306 and a generation module 307. Among them:

[0176] The first acquisition module 301 is used to acquire user profile information; wherein the profile information at least includes basic information, career interests and career goals;

[0177] A determination module 302 is used to determine a corresponding target workplace experience space based on the data information, and determine a target space plot corresponding to the target workplace experience space;

[0178] The collection module 303 is used to collect the comprehensive behavior data of the user in the target workplace experience space when the user enters the target workplace experience space and experiences the target space plot;

[0179] A preprocessing module 304 is used to preprocess the comprehensive behavior data to obtain corresponding target comprehensive behavior data;

[0180] The analysis module 305 is used to analyze and process the target comprehensive behavior data based on preset analysis rules to generate personality index characteristics, environmental index characteristics and technical index characteristics corresponding to the user;

[0181] A construction module 306 is used to construct a portrait of the personality index feature, the environmental index feature and the technical index feature based on a preset portrait generation model to obtain a corresponding occupational portrait;

[0182] The generation module 307 is used to process the career portrait based on a preset planning tool to generate career planning suggestions corresponding to the user.

[0183] In this embodiment, the operations performed by the above modules or units correspond one-to-one to the steps of the information generating method in the aforementioned implementation mode, and are not described in detail here.

[0184] In some optional implementations of this embodiment, the construction module 306 includes:

[0185] The first acquisition submodule is used to obtain a preset career profile formula;

[0186] The second acquisition submodule is used to obtain preset model constants;

[0187] A solution submodule, used for substituting the personality index characteristics, the environmental index characteristics, the technical index characteristics and the model constants into the occupational portrait formula, and solving the occupational portrait formula through the portrait generation model to obtain a corresponding solution result;

[0188] The first generating submodule is used to generate the occupational portrait based on the solution result.

[0189] In some optional implementations of this embodiment, the analysis module 305 includes:

[0190] A first analysis submodule, configured to perform personality analysis on the comprehensive behavior data based on a preset personality analysis model to generate the personality indicator characteristics corresponding to the user;

[0191] A second analysis submodule, configured to perform environmental analysis processing on the comprehensive behavior data based on a preset environmental analysis strategy to generate the environmental indicator feature corresponding to the user;

[0192] The third analysis submodule is used to perform technical analysis on the comprehensive behavior data based on a preset technical analysis strategy to generate the technical indicator characteristics corresponding to the user.

[0193] In some optional implementations of this embodiment, the preprocessing module 304 includes:

[0194] A first processing submodule, configured to perform data cleaning processing on the comprehensive behavior data to obtain corresponding first behavior data;

[0195] A second processing submodule, configured to perform standardization processing on the first behavior data to obtain corresponding second behavior data;

[0196] A determination submodule is provided, which is used to use the second behavior data as the target comprehensive behavior data.

[0197] In some optional implementations of this embodiment, the determining module 302 includes:

[0198] A first screening submodule, used to screen out designated information corresponding to a designated information type from the data information;

[0199] The calling submodule is used to call the preset workplace experience space template library;

[0200] A second screening submodule, configured to screen out a designated workplace experience space template matching the designated information from the workplace experience space template library;

[0201] The second generating submodule is used to generate the target workplace experience space based on the designated workplace experience space template.

[0202] In some optional implementations of this embodiment, the information generating device further includes:

[0203] A second acquisition module is used to acquire career planning related data corresponding to the user;

[0204] A conversion module, used to perform format conversion processing on the career planning related data to obtain corresponding target career planning related data;

[0205] The third acquisition module is used to obtain a preset career planning template;

[0206] A filling module, used to fill the career planning template based on the target career planning related data to obtain a corresponding target career planning book;

[0207] A sending module is used to send the target career planning document to the user.

[0208] In some optional implementations of this embodiment, the information generating device further includes:

[0209] A judgment module, used to judge whether a modification request for the target career plan returned by the user is received;

[0210] A receiving module, configured to receive the modification data input by the user;

[0211] A modification module, used to modify the target career planning document accordingly based on the modification data to obtain a modified target career planning document;

[0212] The storage module is used to store the modified target career planning document.

[0213] To solve the above technical problems, the present application also provides a computer device. Figure 4 , Figure 4 This is a basic structural block diagram of the computer device in this embodiment.

[0214] The computer device 4 includes a memory 41, a processor 42, and a network interface 43 that are interconnected through a system bus. It should be noted that the figure only shows a computer device 4 with components 41-43, but it should be understood that it is not required to implement all the components shown, and more or fewer components can be implemented instead. Among them, those skilled in the art can understand that the computer device here is a device that can automatically perform numerical calculations and / or information processing according to pre-set or stored instructions, and its hardware includes but is not limited to microprocessors, application specific integrated circuits (Application Specific Integrated Circuit, ASIC), programmable gate arrays (Field-Programmable Gate Array, FPGA), digital processors (Digital Signal Processor, DSP), embedded devices, etc.

[0215] The computer device may be a computing device such as a desktop computer, a notebook, a PDA, a cloud server, etc. The computer device may interact with a user through a keyboard, a mouse, a remote controller, a touch pad, or a voice control device.

[0216] The memory 41 includes at least one type of readable storage medium, and the readable storage medium includes flash memory, hard disk, multimedia card, card-type memory (for example, SD or DX memory, etc.), random access memory (RAM), static random access memory (SRAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), programmable read-only memory (PROM), magnetic memory, disk, optical disk, etc. In some embodiments, the memory 41 can be an internal storage unit of the computer device 4, such as a hard disk or memory of the computer device 4. In other embodiments, the memory 41 can also be an external storage device of the computer device 4, such as a plug-in hard disk equipped on the computer device 4, a smart memory card (Smart Media Card, SMC), a secure digital (Secure Digital, SD) card, a flash card (FlashCard), etc. Of course, the memory 41 can also include both the internal storage unit of the computer device 4 and its external storage device. In this embodiment, the memory 41 is generally used to store the operating system and various application software installed on the computer device 4, such as computer-readable instructions of the information generation method, etc. In addition, the memory 41 can also be used to temporarily store various types of data that have been output or are to be output.

[0217] The processor 42 may be a central processing unit (CPU), a controller, a microcontroller, a microprocessor, or other data processing chip in some embodiments. The processor 42 is generally used to control the overall operation of the computer device 4. In this embodiment, the processor 42 is used to run computer-readable instructions stored in the memory 41 or process data, such as computer-readable instructions for running the information generation method.

[0218] The network interface 43 may include a wireless network interface or a wired network interface. The network interface 43 is generally used to establish a communication connection between the computer device 4 and other electronic devices.

[0219] The present application also provides another embodiment, namely, providing a computer-readable storage medium, wherein the computer-readable storage medium stores computer-readable instructions, and the computer-readable instructions can be executed by at least one processor to enable the at least one processor to perform the steps of the information generation method as described above.

[0220] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus a necessary general hardware platform, and of course by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present application, or the part that contributes to the prior art, can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk), and includes a number of instructions for a terminal device (which can be a mobile phone, computer, server, air conditioner, or network device, etc.) to execute the methods described in each embodiment of the present application.

[0221] Obviously, the embodiments described above are only some embodiments of the present application, rather than all embodiments. The preferred embodiments of the present application are given in the accompanying drawings, but they do not limit the patent scope of the present application. The present application can be implemented in many different forms. On the contrary, the purpose of providing these embodiments is to make the understanding of the disclosure of the present application more thorough and comprehensive. Although the present application is described in detail with reference to the aforementioned embodiments, for those skilled in the art, it is still possible to modify the technical solutions recorded in the aforementioned specific implementation methods, or to perform equivalent replacement of some of the technical features therein. Any equivalent structure made using the contents of the specification and drawings of this application, directly or indirectly used in other related technical fields, is similarly within the scope of patent protection of this application.

Claims

1. A method for generating information, characterized in that: The steps include: Obtaining user profile information; wherein the profile information at least includes basic information, career interests and career goals; Determine a corresponding target workplace experience space based on the profile information, and determine a target space plot corresponding to the target workplace experience space; In the process of the user entering the target workplace experience space and experiencing the target space according to the plot of the target space, collecting comprehensive behavior data of the user in the target workplace experience space; Preprocessing the comprehensive behavior data to obtain corresponding target comprehensive behavior data; Analyze and process the target comprehensive behavior data based on preset analysis rules to generate personality index characteristics, environmental index characteristics, and technical index characteristics corresponding to the user; Based on a preset portrait generation model, a portrait of the personality index feature, the environmental index feature, and the technical index feature is constructed to obtain a corresponding occupational portrait; The career profile is processed based on a preset planning tool to generate career planning suggestions corresponding to the user.

2. The information generation method according to claim 1, characterized in that: The step of performing portrait construction processing on the personality index characteristics, the environmental index characteristics and the technical index characteristics based on the preset portrait generation model to obtain the corresponding occupational portrait specifically includes: Get the preset career profile formula; Get the preset model constants; Substituting the personality index characteristics, the environmental index characteristics, the technical index characteristics and the model constants into the occupational portrait formula, and solving the occupational portrait formula through the portrait generation model to obtain a corresponding solution result; The occupational portrait is generated based on the solution result.

3. The information generation method according to claim 1, characterized in that: The step of analyzing and processing the target comprehensive behavior data based on preset analysis rules to generate personality index characteristics, environmental index characteristics, and technical index characteristics corresponding to the user specifically includes: Performing personality analysis on the comprehensive behavior data based on a preset personality analysis model to generate the personality indicator characteristics corresponding to the user; Performing environmental analysis on the comprehensive behavior data based on a preset environmental analysis strategy to generate the environmental indicator features corresponding to the user; The comprehensive behavior data is subjected to technical analysis based on a preset technical analysis strategy to generate the technical indicator features corresponding to the user.

4. The information generation method according to claim 1, characterized in that: The step of preprocessing the comprehensive behavior data to obtain corresponding target comprehensive behavior data specifically includes: Performing data cleaning processing on the comprehensive behavior data to obtain corresponding first behavior data; Performing standardization processing on the first behavior data to obtain corresponding second behavior data; The second behavior data is used as the target comprehensive behavior data.

5. The information generation method according to claim 1, characterized in that: The step of determining the corresponding target workplace experience space based on the data information specifically includes: Filtering out designated information corresponding to a designated information type from the data information; Call the preset workplace experience space template library; Filtering out a designated workplace experience space template matching the designated information from the workplace experience space template library; The target workplace experience space is generated based on the designated workplace experience space template.

6. The information generating method according to claim 1, characterized in that: After the step of processing the career profile based on the preset planning tool to generate a career planning suggestion corresponding to the user, the method further includes: Acquire career planning related data corresponding to the user; Performing format conversion processing on the career planning related data to obtain corresponding target career planning related data; Get a preset career planning template; Filling the career planning template based on the target career planning related data to obtain a corresponding target career planning document; The target career planning document is sent to the user.

7. The information generating method according to claim 6, characterized in that: After the step of sending the target career plan to the user, the method further includes: Determining whether a modification request for the target career plan returned by the user is received; If so, receiving modification data input by the user; Modify the target career plan accordingly based on the modification data to obtain a modified target career plan; The modified target career planning book is stored and processed.

8. An information generating device, characterized in that: include: The first acquisition module is used to acquire the user's profile information; wherein the profile information at least includes basic information, career interests and career goals; A determination module, used to determine a corresponding target workplace experience space based on the data information, and determine a target space plot corresponding to the target workplace experience space; A collection module, configured to collect comprehensive behavior data of the user in the target workplace experience space when the user enters the target workplace experience space and experiences the target space according to the plot of the target space; A preprocessing module, used for preprocessing the comprehensive behavior data to obtain corresponding target comprehensive behavior data; An analysis module, used to analyze and process the target comprehensive behavior data based on preset analysis rules to generate personality index characteristics, environmental index characteristics and technical index characteristics corresponding to the user; A construction module, used to construct a portrait of the personality index feature, the environmental index feature and the technical index feature based on a preset portrait generation model to obtain a corresponding occupational portrait; A generation module is used to process the career portrait based on a preset planning tool to generate career planning suggestions corresponding to the user.

9. A computer device, characterized in that: The method comprises a memory and a processor, wherein the memory stores computer-readable instructions, and the processor implements the steps of the information generating method according to any one of claims 1 to 7 when executing the computer-readable instructions.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer-readable instructions, and when the computer-readable instructions are executed by a processor, the steps of the information generating method according to any one of claims 1 to 7 are implemented.

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