Real-time evaluation method and device for health state of user and storage medium

Abstract

The invention relates to the field of data processing, and discloses a real-time evaluation method and device for the health state of a user and a storage medium. The method comprises the following steps: detecting session content of a webpage session interface in real time; extracting sensitive content corresponding to the session content, wherein the sensitive content comprises sensitive copywriting, sensitive pictures, sensitive words and filtering websites; and according to the sensitive content, analyzing to obtain a user health state value, and outputting prompt information according to the user health state value. In the embodiment of the invention, the session content of the webpage session interface is detected in real time, and sensitive content is extracted for analysis instead of being comprehensively monitored, so that the privacy of the user is protected to the greatest extent. By extracting the sensitive content, the network social behaviors possibly influencing the health state of the user can be accurately captured, and a means for effectively monitoring the network behaviors of children is provided for parents. And prompt information can be output in real time according to the user health state value obtained through analysis.

Description

Technical Field

[0001] The present invention relates to the field of data processing, and in particular to a real-time evaluation method, device and storage medium for user health status. Background Art

[0002] In the digital age, the popularity of social media and instant messaging applications has brought convenience to communication, but it has also caused parents to worry about their children's online social behavior. Existing monitoring software is difficult to effectively obtain web chat data, and there is a risk of privacy infringement. A new technical solution is needed to solve the above technical problems. For example, it can provide parents with a safe and legal way to monitor their children's online behavior while protecting privacy and avoid family conflicts. Summary of the invention

[0003] The main purpose of the present invention is to solve the technical problem that existing monitoring software is difficult to effectively obtain web chat data and there is a risk of privacy infringement.

[0004] A first aspect of the present invention provides a method for real-time evaluation of a user's health status, the method comprising: Real-time detection of the conversation content of the webpage conversation interface; Extracting sensitive content corresponding to the conversation content, wherein the sensitive content includes sensitive text, sensitive pictures, sensitive words, and filtered URLs; According to the sensitive content, a user health status value is analyzed and obtained, and prompt information is output according to the user health status value.

[0005] Optionally, in a first implementation manner of the first aspect of the present invention, the step of extracting sensitive content corresponding to the conversation content includes: extracting key content from the conversation content; According to the key content, the sensitive content is matched in a preset sensitive content library.

[0006] Optionally, in a second implementation manner of the first aspect of the present invention, the step of extracting sensitive content corresponding to the conversation content includes: The pre-trained ChatGPT model is called to extract key content from the conversation content.

[0007] Optionally, in a third implementation of the first aspect of the present invention, before the step of detecting the conversation content of the webpage conversation interface in real time, the method further includes: When a plug-in extension request is detected, in response to the plug-in extension request, a target plug-in is selected in a preset plug-in library as the ChatGPT model.

[0008] Optionally, in a fourth implementation manner of the first aspect of the present invention, after performing a standardization operation on the sensitive content to be processed according to a preset sensitive content library to obtain the standard of the sensitive content, the method further includes: Acquire device operation data, and determine the residence time and access frequency corresponding to the sensitive content according to the acquired device operation data; The user health status value is analyzed and obtained according to the sensitive content, the stay duration and the access frequency.

[0009] Optionally, in a fifth implementation of the first aspect of the present invention, the step of analyzing and obtaining the user health status value according to the sensitive content, the stay duration, and the access frequency includes: Obtaining preset user information, including age, gender, and hobbies; The user health status value is analyzed and obtained according to the user information, the sensitive content, the stay duration and the access frequency.

[0010] Optionally, in a sixth implementation of the first aspect of the present invention, the step of analyzing and obtaining a user health status value according to the sensitive content, the stay duration, and the access frequency includes: Generate a basic score and weight based on the user information, including age, gender, and hobbies; The user health status value is calculated based on the basic score and the weight.

[0011] Optionally, in a seventh implementation manner of the first aspect of the present invention, the step of detecting the conversation content of the webpage conversation interface in real time includes: When it is detected that the preset APP is started, the conversation content of the webpage conversation interface is detected in real time, and the preset APP is a pre-marked sensitive APP.

[0012] A second aspect of the present invention provides a real-time assessment device for a user's health status, comprising: a memory and at least one processor, wherein instructions are stored in the memory, and the memory and the at least one processor are interconnected via lines; the at least one processor calls the instructions in the memory so that the real-time assessment device for the user's health status executes the above-mentioned real-time assessment method for the user's health status.

[0013] A third aspect of the present invention provides a computer-readable storage medium, in which instructions are stored, which, when executed on a computer, enable the computer to execute the above-mentioned method for real-time assessment of user health status.

[0014] In an embodiment of the present invention, the conversation content of the webpage conversation interface is detected in real time; the sensitive content corresponding to the conversation content is extracted, and the sensitive content includes sensitive text, sensitive pictures, sensitive words, and filtered websites; according to the sensitive content, the user health status value is analyzed and obtained, and prompt information is output according to the user health status value. The conversation content of the webpage conversation interface is detected in real time, focusing on extracting sensitive content for analysis rather than comprehensively monitoring user behavior, thereby protecting the user's privacy to the greatest extent. By extracting sensitive content (including sensitive text, sensitive pictures, sensitive words, filtered websites, etc.), it is possible to accurately capture online social behaviors that may affect the user's health status, providing parents with a means to effectively monitor their children's online behavior. According to the user health status value obtained by analysis, prompt information can be output instantly. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 It is a schematic diagram of a first embodiment of a method for real-time evaluation of a user's health status in an embodiment of the present invention; Figure 2 It is a schematic diagram of a specific embodiment of step 102 of the method for real-time assessment of user health status in an embodiment of the present invention; Figure 3 This is a schematic diagram of a specific embodiment of step 103 of the method for real-time assessment of user health status in an embodiment of the present invention; Figure 4 This is a schematic diagram of a specific embodiment of step 1032 of the method for real-time assessment of user health status in an embodiment of the present invention; Figure 5 The figure is a schematic diagram of an embodiment of a device for real-time evaluation of a user's health status in an embodiment of the present invention. DETAILED DESCRIPTION

[0016] The embodiments of the present invention provide a method, a device and a storage medium for real-time evaluation of a user's health status.

[0017] The embodiments disclosed in the present invention will be described in more detail below with reference to the accompanying drawings. Although certain embodiments disclosed in the present invention are shown in the accompanying drawings, it should be understood that the present invention can be implemented in various forms and should not be construed as being limited to the embodiments described herein, which are instead provided for a more thorough and complete understanding of the present invention. It should be understood that the drawings and embodiments disclosed in the present invention are only for exemplary purposes and are not intended to limit the scope of protection disclosed in the present invention.

[0018] In the description of the embodiments disclosed in the present invention, the term "including" and similar terms should be understood as open inclusion, that is, "including but not limited to". The term "based on" should be understood as "based at least in part on". The term "one embodiment" or "the embodiment" should be understood as "at least one embodiment". The terms "first", "second", etc. may refer to different or the same objects. Other explicit and implicit definitions may also be included below.

[0019] The professional terms involved in the real-time assessment method of user health status include but are not limited to: User health status: refers to the comprehensive assessment results of the user's psychological state, behavioral habits or potential risks reflected by his or her online behavior (such as browsing content, communicating information, etc.) within a specific period of time. The assessment results are intended to help parents, guardians or relevant institutions understand the user's online health status so that timely intervention measures can be taken.

[0020] Web conversation interface: refers to the interactive interface of users on web browsers, including chat windows, social media pages, web forums, etc. These interfaces are direct channels for users to generate and receive network information.

[0021] Sensitive content: refers to content that may have a negative impact on users (especially minors). Such content is considered an important indicator when assessing the health status of users.

[0022] ChatGPT model: ChatGPT is a natural language processing model based on artificial intelligence technology that can understand and generate human language. In this claim, the ChatGPT model is used to extract key content from conversation content and assist in identifying sensitive information.

[0023] Extensions: Refers to components or modules that provide additional functionality to software or applications. In this context, extensions allow users to select different functional components (such as different natural language processing models) as needed to extend the functionality of the real-time evaluation method.

[0024] Dwell time: refers to the length of time a user stays on a web page or session interface related to sensitive content. This metric helps assess the user's attention to sensitive content and its potential impact.

[0025] Access frequency: refers to the number of times a user accesses a web page or session interface containing sensitive content. The frequency of access reflects the user's interest in or exposure to such content.

[0026] Preset APPs: refers to applications that are marked in advance as requiring special attention. These applications usually contain sensitive content that users may access or network social functions with potential risks. By monitoring these preset APPs, users' network health status can be more effectively assessed.

[0027] Standardization operation: refers to the process of uniformly handling sensitive content to ensure the consistency and comparability of evaluation results. Standardization operation may include content cleaning, format conversion, keyword mapping and other steps.

[0028] Basic score and weight: When evaluating the user's health status, different basic scores and weights are assigned according to different characteristics of the user (such as age, gender, interests and hobbies). The scores and weights are used to calculate the final user health status value to reflect the degree of influence of different characteristics on the user's health status.

[0029] For ease of understanding, the specific process of the embodiment of the present invention is described below. Figure 1 , an embodiment of a method for real-time evaluation of a user's health status in an embodiment of the present invention includes: 101. Real-time detection of the conversation content of the webpage conversation interface; Specifically, when the real-time assessment device for the user's health status is started, the preset sensitive content library, user information (including age, gender, interests and hobbies, etc.), preset APP list and other configuration information are loaded from the memory.

[0030] The monitoring or interception mechanism in the real-time evaluation device of the user's health status can be used to capture the session content of the web page session interface in real time.

[0031] For example, when a real-time assessment device for a user's health status (such as a smartphone, software application on a computer, etc.) is started, the necessary configuration information is automatically loaded from the local storage or remote server, including a preset sensitive content library (updated regularly to reflect the latest network trends and risks), user information (such as age, gender, interests and hobbies, etc., which can be obtained through user registration or subsequent authorized access), and a preset APP list (containing applications known to contain sensitive content).

[0032] Utilize built-in monitoring or interception mechanisms (such as network packet capture, API hooks, screen content reading, etc.) to capture all user activities on the web session interface in real time, including but not limited to chat records, browsing history, image viewing, etc.

[0033] The captured data is stored encrypted and analyzed immediately to ensure user privacy and data security.

[0034] Optionally, step 101 also includes the following specific implementation steps: 1011. When it is detected that the preset APP is started, the conversation content of the webpage conversation interface is detected in real time, and the preset APP is a pre-marked sensitive APP.

[0035] In step 1011, by performing real-time detection only on pre-marked sensitive apps, the monitoring scope is narrowed, and unnecessary computing resources and time consumption are reduced. The targeted monitoring method enables the real-time evaluation device of the user's health status to respond and evaluate the user's network behavior more quickly, thereby improving the evaluation efficiency.

[0036] 102. Extract sensitive content corresponding to the conversation content, where the sensitive content includes sensitive text, sensitive pictures, sensitive words, and filtered URLs; Specifically, the captured conversation content is parsed to extract multimedia information such as text and pictures.

[0037] Match the extracted key content with the preset sensitive content library to identify sensitive text, sensitive images, sensitive words, filtered URLs, etc.

[0038] For example, the captured conversation content is first parsed into different multimedia types (such as text, pictures, videos, etc.). For text content, natural language processing (NLP) technology is used for analysis; for pictures and videos, image recognition and video analysis technology are used.

[0039] The extracted text, pictures and other key contents are sent to the preset sensitive content library for matching. The sensitive content library contains multiple sub-libraries, corresponding to different types of sensitive information.

[0040] The matching algorithm can use efficient string search, pattern recognition or deep learning technology to improve the accuracy and efficiency of recognition.

[0041] For images and videos, in addition to directly matching known sensitive images in the library, machine learning models can be used to identify potentially objectionable content.

[0042] Optional, see Figure 2 , Figure 2 FIG. 1 is a schematic diagram of a specific embodiment of step 102 of the method for real-time evaluation of user health status in an embodiment of the present invention. Step 102 also includes the following specific implementation methods: 1021. Extract key content from the conversation content; 1022. Match the sensitive content in a preset sensitive content library according to the key content.

[0043] In steps 1021-1022, by real-time detection of the content of the webpage session interface, sensitive information that the user may be exposed to can be captured immediately. This ensures that the real-time evaluation device of the user's health status can respond quickly to the user's behavior, and timely evaluate and feedback the health risks that the user may face. By extracting sensitive content such as sensitive copy, sensitive pictures, sensitive words, and filtering URLs, the user's network activity content is fully covered. Combined with the preset sensitive content library for precise matching, the accuracy and efficiency of recognition are improved.

[0044] Optionally, in step 1021, the following specific implementations are also included: 10211. Call the pre-trained ChatGPT model to extract key content from the conversation content.

[0045] In step 10211, by calling the pre-trained ChatGPT model to extract key content in the conversation content, the powerful capabilities of ChatGPT in natural language processing can be fully utilized, thereby improving the accuracy and efficiency of sensitive content extraction.

[0046] Optionally, in step 1021, the following specific implementations are also included: 102111. When a plug-in extension request is detected, in response to the plug-in extension request, a target plug-in is selected in a preset plug-in library as the ChatGPT model.

[0047] In step 102111, through the plug-in extension mechanism, different plug-ins can be selected and integrated as needed to support the operation of the ChatGPT model and the extraction of sensitive content. This makes the real-time assessment device for user health status more flexible and can easily cope with changes in different scenarios and needs. The plug-in extension mechanism simplifies the process of deployment and maintenance of real-time assessment devices for user health status. When the ChatGPT model needs to be updated or replaced, only the new target plug-in needs to be selected in the preset plug-in library, without the need for large-scale modification or redeployment of the entire real-time assessment device for user health status.

[0048] 103. Analyze and obtain a user health status value based on the sensitive content, and output a prompt message based on the user health status value.

[0049] Specifically, a preset algorithm is called to analyze and obtain the user health status value according to the sensitive content, and prompt information is output according to the user health status value.

[0050] For example, a preset algorithm model is called, which comprehensively considers the type, quantity, frequency of sensitive content and the user's personal information (such as age, gender, interests, etc.). The model can use weighted scoring methods, machine learning classification or regression algorithms to derive a quantified user health status value.

[0051] The size of the user health status value reflects the user's current network health status.

[0052] According to the calculated user health status value, corresponding prompt information is automatically generated. Prompt information includes but is not limited to warnings, suggestions, educational content or links that guide users to take certain actions.

[0053] The prompt information is displayed to the user or guardian through the device's user interface (such as pop-up windows, notification bar, in-app messages, etc.) and possible remote notification methods (such as SMS and email).

[0054] For high-risk situations, trigger emergency response mechanisms, such as automatically blocking access to certain websites, sending emergency alerts to parents or guardians, etc.

[0055] In a specific scenario, assume that user A is using a browser that integrates a real-time user health status assessment method. The browser can detect web page session content in real time and extract sensitive content from it.

[0056] Over a period of time, the browser detects that the session content of user A contains the following sensitive content: Sensitive words: appeared 3 times; Sensitive URLs: Visited 1 time; Sensitive images: Viewed 1 time; At the same time, the real-time assessment device for user health status obtains basic information about user A: Age: 12 years old Gender: Male; Hobbies: games, technology; Sensitive content weight distribution: Sensitive words: Each time they appear, a certain negative score (such as -5 points) will be assigned, for a total of -15 points.

[0057] Sensitive URLs: Each visit will be assigned a high negative score (such as -20 points).

[0058] Sensitive images: A certain negative score (such as -10 points) is assigned after each viewing.

[0059] The calculations could be adjusted slightly to assume that users are more susceptible to bad information, but this factor is not taken into account in this example.

[0060] Add up the scores of all sensitive content: -15 points (sensitive words) + -20 points (sensitive URLs) + -10 points (sensitive images) = -45 points.

[0061] Assuming the basic score is 70 points, the user's health status value is 80-45=25 points.

[0062] This score directly reflects the network health status of user A in the current time period. The lower the score, the greater the risk the user may face.

[0063] According to the calculated user health status value (25), the real-time evaluation device of the user health status can generate corresponding prompt information, such as: "Warning! You have recently browsed multiple web pages containing bad information. Please stay vigilant to avoid being deceived and exposed to bad content." Optional, see Figure 3 , Figure 3 FIG. 1 is a schematic diagram of a specific embodiment of step 103 of the method for real-time evaluation of user health status in an embodiment of the present invention. Step 103 also includes the following specific implementation methods: 1031. Obtain device operation data, and determine the residence time and access frequency corresponding to the sensitive content according to the device operation data; 1032. Analyze and obtain a user health status value based on the sensitive content, the dwelling duration, and the access frequency.

[0064] In steps 1031-1032, by considering the user's age, gender, interests and hobbies and other personalized information, the user's reaction to sensitive content and potential impact in different situations can be more accurately evaluated. Personalized evaluation makes the health status value and prompt information output by the system closer to the user's actual situation, improving the pertinence and effectiveness of the evaluation.

[0065] Optional, see Figure 4 , Figure 4 FIG. 1 is a schematic diagram of a specific embodiment of step 1032 of the method for real-time evaluation of user health status in an embodiment of the present invention. Step 1032 also includes the following specific implementation methods: 10321. Obtain preset user information, where the user information includes age, gender, and hobbies; 10322. Analyze and obtain a user health status value based on the user information, the sensitive content, the duration of stay and the access frequency.

[0066] In steps 10321-10322, the introduction of user information makes the evaluation process more tailored to the user's actual situation. Users of different ages, genders, and interests may have different reactions and potential health risks to the same or different sensitive content. By considering these factors, the system can generate more personalized health status values ​​and provide more accurate health guidance. User information provides an additional reference dimension for the evaluation process. Combining data such as sensitive content, length of stay, and frequency of visits can more comprehensively analyze users' network behavior patterns and potential health risks, thereby improving the accuracy of the evaluation results.

[0067] Optionally, step 10322 also includes the following specific implementations: 103221. Generate a basic score and weight based on the user information, which includes age, gender, and hobbies; 103222. Calculate the user health status value according to the basic score and the weight; 103223. Obtain preset user information, which includes age, gender, and hobbies; 103224. Analyze and obtain a user health status value based on the user information, the sensitive content, the duration of stay and the access frequency.

[0068] In a specific scenario, suppose there is a real-time evaluation system for user health status called "Health Guardian", running on an educational website, bound to student terminals (real-time evaluation of user health status), which can receive health status values ​​fed back by student terminals to prevent them from accessing bad content. The following is an example: User ID: 001; Name: Xiao Ming; Age: 15 years old; Gender: Male; Hobbies: programming, games; In the web page session, it was detected that Li Ming visited a web page containing sensitive words (such as "violent games") and sensitive pictures (such as bloody pictures), and he stayed on the web page for a long time (for example, 30 minutes) and visited it frequently (for example, 5 times in a week).

[0069] The extracted sensitive content includes: sensitive words such as "violent games" and sensitive pictures with bloody scenes; duration: 30 minutes; access frequency: 5 times within a week; Analysis process: According to the user's age (15 years old), the basic score is set to 80 points (assuming that young users have a good initial status, it can be set based on the user's basic information).

[0070] Gender and hobbies have little direct impact on health status assessment in this scenario, but they can be used as reference factors for adjusting weights. For example, gender may have a slight impact on the tendency to access violent content, and "games" in hobbies may be related to accessing violent game content, so the relevant weights can be adjusted appropriately.

[0071] Sensitive content (including sensitive words and images): weight 0.5 (because the content directly affects health status) Duration of stay: Weight 0.3 (a longer stay may indicate a deeper concern or influence).

[0072] Visit frequency: Weight 0.2 (high frequency of visits may indicate that users have a high interest in or are continuously influenced by such content).

[0073] Calculate the user's health status value: Sensitive content score (assuming the full score is 100): Due to the presence of sensitive words and images, the score is 50 (indicating poor).

[0074] Length of stay score (assuming full score is 100): 30 minutes converts to a score of 60 points (assuming long stays have lower scores).

[0075] Visit frequency score (assuming the full score is 100): 5 visits in a week translates to a score of 40 (high-frequency visits have lower scores).

[0076] Calculate the final score based on the weights: [User health status value = (sensitive content score\times 0.5) + (stay time score\times0.3) + (visit frequency score\times 0.2)]; [User health status value = (50 \times 0.5) + (60 \times 0.3) + (40 \times 0.2) = 25 + 18 + 8 = 51].

[0077] In steps 103221-103224, the basic scores and weights are set based on the user's specific attributes, so that the evaluation process is closer to the user's personalized characteristics. Different users may have different reactions and potential health risks to the same sensitive content due to their age, gender, interests and hobbies. By individually adjusting the basic scores and weights, the evaluation results can more accurately reflect the user's actual situation.

[0078] In an embodiment of the present invention, the conversation content of the webpage conversation interface is detected in real time; the sensitive content corresponding to the conversation content is extracted, and the sensitive content includes sensitive text, sensitive pictures, sensitive words, and filtered websites; according to the sensitive content, the user health status value is analyzed and obtained, and prompt information is output according to the user health status value. The conversation content of the webpage conversation interface is detected in real time, focusing on extracting sensitive content for analysis rather than comprehensively monitoring user behavior, thereby protecting the user's privacy to the greatest extent. By extracting sensitive content (including sensitive text, sensitive pictures, sensitive words, filtered websites, etc.), it is possible to accurately capture online social behaviors that may affect the user's health status, providing parents with a means to effectively monitor their children's online behavior. According to the user health status value obtained by analysis, prompt information can be output instantly.

[0079] Figure 5 : This is a structural diagram of a real-time evaluation device for user health status provided by an embodiment of the present invention. The real-time evaluation device 500 for user health status may have relatively large differences due to different configurations or performances, and may include one or more processors (central processing units, CPU) 510 (for example, one or more processors) and a memory 520, and one or more storage media 530 (for example, one or more mass storage devices) storing application programs 533 or data 532. Among them, the memory 520 and the storage medium 530 can be short-term storage or permanent storage. The program stored in the storage medium 530 may include one or more modules (not shown in the figure), and each module may include a series of instruction operations in the real-time evaluation device 500 for user health status. Furthermore, the processor 510 may be configured to communicate with the storage medium 530 to execute a series of instruction operations in the storage medium 530 on the real-time evaluation device 500 for user health status.

[0080] The real-time assessment device 500 based on the user's health status may also include one or more power supplies 540, one or more wired or wireless network interfaces 550, one or more input and output interfaces 560, and / or one or more operating systems 531, such as Windows Serve, Mac OS X, Unix, Linux, Free BSD, etc. It will be appreciated by those skilled in the art that Figure 5 The structure of the device for real-time assessment of the user's health status shown does not constitute a limitation on the device for real-time assessment based on the user's health status, and may include more or less components than shown in the figure, or combine certain components, or arrange the components differently.

[0081] The present invention also provides a computer-readable storage medium, which may be a non-volatile computer-readable storage medium or a volatile computer-readable storage medium. Instructions are stored in the computer-readable storage medium. When the instructions are executed on a computer, the computer executes the steps of the real-time assessment method of the user's health status.

[0082] In the context of the present disclosure, a machine-readable medium may be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, device, or equipment. A machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or equipment, or any suitable combination of the foregoing. A more specific example of a machine-readable storage medium may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

[0083] In addition, although each operation is described in a specific order, this should be understood as requiring such operation to be performed in the specific order shown or in a sequential order, or requiring that all illustrated operations should be performed to obtain desired results. Under certain circumstances, multitasking and parallel processing may be advantageous. Similarly, although some specific implementation details are included in the above discussion, these should not be interpreted as limiting the scope of the present disclosure. Some features described in the context of a separate embodiment can also be implemented in a single implementation in combination. On the contrary, the various features described in the context of a single implementation can also be implemented in multiple implementations individually or in any suitable sub-combination mode.

[0084] Although the subject matter has been described in language specific to structural features and / or methodological logical actions, it should be understood that the subject matter defined in the appended claims is not necessarily limited to the specific features or actions described above. On the contrary, the specific features and actions described above are merely example forms of implementing the claims.

Claims

1. A real-time assessment method for user health status, It is characterized in that The real-time evaluation method of the user's health status includes: Real-time detection of the conversation content of the webpage conversation interface; Extracting sensitive content corresponding to the conversation content, wherein the sensitive content includes sensitive text, sensitive pictures, sensitive words, and filtered URLs; According to the sensitive content, a user health status value is analyzed and obtained, and prompt information is output according to the user health status value.

2. The real-time evaluation method for user health status according to claim 1, It is characterized in that The step of extracting the sensitive content corresponding to the conversation content comprises: extracting key content from the conversation content; According to the key content, the sensitive content is matched in a preset sensitive content library.

3. The real-time evaluation method for user health status according to claim 2, It is characterized in that The step of extracting the sensitive content corresponding to the conversation content comprises: The pre-trained ChatGPT model is called to extract key content from the conversation content.

4. The real-time evaluation method for user health status according to claim 3, It is characterized in that Before the step of detecting the conversation content of the webpage conversation interface in real time, the method further includes: When a plug-in extension request is detected, in response to the plug-in extension request, a target plug-in is selected in a preset plug-in library as the ChatGPT model.

5. The real-time evaluation method for user health status according to claim 1, It is characterized in that The step of analyzing and obtaining a user health status value according to the sensitive content, and outputting prompt information according to the user health status value comprises: Acquire device operation data, and determine the residence time and access frequency corresponding to the sensitive content according to the acquired device operation data; The user health status value is analyzed and obtained according to the sensitive content, the stay duration and the access frequency.

6. The real-time evaluation method for user health status according to claim 5, It is characterized in that The step of analyzing and obtaining the user health status value according to the sensitive content, the stay duration and the access frequency comprises: Obtaining preset user information, including age, gender, and hobbies; The user health status value is analyzed and obtained according to the user information, the sensitive content, the stay duration and the access frequency.

7. The real-time evaluation method for user health status according to claim 6, It is characterized in that The step of analyzing and obtaining the user health status value according to the sensitive content, the stay duration and the access frequency comprises: Generate a basic score and weight based on the user information, including age, gender, and hobbies; The user health status value is calculated based on the basic score and the weight.

8. The real-time evaluation method for user health status according to claim 1, It is characterized in that The step of real-time detection of the conversation content of the webpage conversation interface comprises: When it is detected that the preset APP is started, the conversation content of the webpage conversation interface is detected in real time, and the preset APP is a pre-marked sensitive APP.

9. A real-time assessment device for user health status, It is characterized in that The real-time assessment device for the user's health status comprises: a memory and at least one processor, the memory stores instructions, and the memory and the at least one processor are interconnected via a line; The at least one processor calls the instructions in the memory to enable the real-time assessment device for the user's health status to execute the real-time assessment method for the user's health status as described in any one of claims 1-8.

10. A computer-readable storage medium having a computer program stored thereon, It is characterized in that When the computer program is executed by a processor, the real-time evaluation method for the user's health status as described in any one of claims 1 to 8 is implemented.

Images