AI intelligent terminal information management and push method

Abstract

The invention discloses an AI intelligent terminal information management and push method, relates to the technical field of information management and push, and provides personalized information push and evaluation by dividing popular science learning challenges into two stages. In a first preset period, a target time period and a pushing quantity are determined according to historical consulting data of a user, and an information consulting condition in the first preset period is collected, so that personal characteristics of the user are obtained through analysis, and meanwhile, the popular science mastering degree of the user is evaluated according to effective consulting information coverage. According to the method, personalized pushing is realized by accurately capturing the user behavior characteristics, the science popularization information consulting efficiency is improved, the learning systematicness and continuity are guaranteed, and the user experience is improved. And pertinence and interestingness of science popularization learning of teenagers

Description

Technical Field

[0001] This application relates to the field of information management and push technology, specifically to methods for information management and push on AI smart terminals. Background Technology

[0002] In the digital age of information overload, users are constantly bombarded with massive amounts of data. Disorder, overload, and inefficient acquisition of information have become common problems. Intelligent management and push of information is the core solution to address this challenge. Its value lies in the deep optimization of multiple dimensions such as user experience, social efficiency, and technological development. Therefore, this application proposes an AI-powered intelligent terminal information management and push method.

[0003] Existing technology, such as the message push processing method disclosed in patent application CN111931110B, involves an access server, upon receiving a message push request from a service provider, querying an information management server for the target user terminals corresponding to the target user group attributes in the message push request. The access server then retrieves the push settings information sent by the target user terminals, which is pre-stored in the information management server. Finally, it matches the push settings information of each target user terminal with the message attribute information to determine the final target user terminal that matches the message attributes. Since the push settings information is set and sent by the user according to their own needs, the message content that matches the push settings information is the message content that the user is truly interested in.

[0004] Existing technologies, such as the cloud server information management method and system disclosed in patent application CN113271328A, determine the push service tag information of the business data to be pushed and the preset content push location information under the preset content push object. Then, they calculate the relative correlation elements between the push service tag and each push model, and construct a push service area with the push service tag as the content push object by determining the target relative correlation elements. The location points of the push model are mapped to the push service area as the push target. By determining the push status at the push target and the push information to be output at the push model, the push result with the push service tag as the push object is determined by outputting the push information. Thus, the push service can be performed based on the push service tag of the business data to be pushed, thereby improving the push service and push experience at the push service tag location.

[0005] The above solution has the following technical problems: 1. The current technology mainly associates message attributes with the attributes of the target audience to push messages, but it does not continuously monitor and analyze the viewing of pushed messages. Analyzing users' message viewing behavior can continuously optimize subsequent message pushes. The current technology's neglect of this aspect leads to the lack of perfection in message push.

[0006] 2. Current technology mainly involves building a push service area and then pushing business data through push business tags. However, the current technology does not analyze the push time and frequency of business data. The efficiency and effect of users processing business data are different when pushing business data during busy periods versus when users are less busy. Therefore, the current technology's neglect of this aspect may lead to the business data not achieving the desired processing effect. Summary of the Invention

[0007] The purpose of this application is to provide an AI-powered intelligent terminal information management and push method, which solves the problems existing in the background technology.

[0008] To solve the above-mentioned technical problems, this application adopts the following technical solution: This application provides an AI smart terminal information management and push method, including: Step 1, pushing information to the target user according to the preset information push data within a first preset period, and collecting the target user's viewing status of each pushed information within the first preset period.

[0009] Step 2: Based on the target user's viewing behavior of each push notification within the first preset period, the personal characteristic information of the target user is obtained. At the same time, the target user's understanding of the first phase of popular science is also analyzed. Then, the target user's personal characteristic information and understanding of the first phase of popular science are combined to push information for the second preset period, and the viewing behavior of each push notification by the target user within the second preset period is collected.

[0010] Step 3: After the information push is completed in the second preset period, determine whether to conduct a science popularization content test on the target users based on the target users' viewing of each pushed information within the second preset period, and then determine whether the target users have completed this science popularization learning.

[0011] The beneficial effects of this application are as follows: 1. The AI-powered intelligent terminal information management and push method provided in this application implements personalized information push and evaluation by dividing the science popularization learning challenge into two stages. Within the first preset period, the target time period and the number of pushes are determined based on the user's historical browsing data. Information browsing data within the first preset period is collected, and user personal characteristics are analyzed. Simultaneously, the user's level of science popularization understanding is evaluated based on the coverage of effective browsing information. The number of pushes and the proportion of information styles are dynamically adjusted accordingly. Finally, a test is conducted based on the user's preferred style and format and self-selected test type. Those who meet the standards proceed to the next stage of science popularization learning. This application achieves personalized push by accurately capturing user behavioral characteristics, improving the efficiency of science popularization information browsing, ensuring the systematic and continuous nature of learning, and enhancing the relevance and interest of science popularization learning for teenagers.

[0012] 2. This application achieves precise delivery of popular science information through multi-dimensional data collection and analysis. Within the first preset period, based on the target users' historical browsing data, it identifies high-frequency usage time periods and information demand, and pushes basic popular science content in conjunction with terminal environment awareness. Simultaneously, by analyzing the proportion of users browsing information types, styles, and formats, it dynamically adjusts the push strategy for the second period. This closed-loop mechanism, where user behavior feedback leads to optimized push strategies, avoids the inefficiency of traditional push methods, allowing teenagers to access popular science content at times and in formats that interest them, reducing information filtering costs, and significantly improving learning focus and knowledge acquisition efficiency.

[0013] 3. This application assesses the user's knowledge level to ensure a gradual learning process. It also compares the types of information effectively accessed with the stage's science goals to determine whether to proceed to the next learning stage. If the user has not covered all the information types in basic science, they will continue to solidify their foundation. After completing the goals, advanced content will be pushed to them. This phased approach aligns with the cognitive development of teenagers, ensuring the integrity of the knowledge system while flexibly adjusting the pace according to individual differences, allowing each user to steadily improve their scientific literacy at an appropriate level of difficulty.

[0014] 4. This application deeply integrates the testing process with user preferences. Before the test, data from the second cycle is analyzed to identify the information style and format preferred by users. Personalized test content is generated based on the user's chosen test type, thereby reducing teenagers' resistance to testing. The test results are then used to determine the information push content for the next stage. This mechanism not only tests the level of knowledge mastery but also optimizes subsequent push directions through feedback. This application, through engaging tests and clear progression paths, stimulates teenagers' learning motivation and enhances the fun and enthusiasm of user learning. Attached Figure Description

[0015] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0016] Figure 1 This is a flowchart illustrating the steps involved in implementing the method described in this application. Detailed Implementation

[0017] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0018] Reference Figure 1 As shown, this application provides an AI smart terminal information management and push method, including the following modules / steps: Step 1: Push information to the target user according to the preset information push data within the first preset period, and collect the target user's viewing status of each pushed information within the first preset period.

[0019] It should be noted that the specific length of the first preset period is set by the relevant staff. It can be a week, half a month, or a month. No specific restrictions are imposed here.

[0020] In a specific example, the process of pushing information to target users according to preset information push data within the first preset period is as follows: the users participating in the science popularization learning challenge are recorded as target users. First, the historical information browsing data of the target users is obtained from the terminal. The historical information browsing data includes the time periods when the target users use the smart terminal and the average number of information browsed in each time period, which are respectively recorded as the target time periods of the first preset period and the target push quantity corresponding to each target time period.

[0021] It should be noted that the target users are aged 8-16.

[0022] Then, retrieve the basic science information from the data center of the current science learning challenge, and push the basic science information to the terminal devices of the target users according to the corresponding target push quantity in each target time period of the first preset cycle.

[0023] It should be noted that the content of the science popularization learning challenge includes natural sciences, humanities, history, and social life.

[0024] In a specific example, the collection of target users' viewing status of each push message within a first preset period includes the number of push messages in each target time period, the viewing duration of each viewed message, the information type, information style, and information format of each viewed message.

[0025] It should be noted that the information types include natural sciences, humanities, history, and social life; the information styles include engaging storytelling, rigorous popular science, interactive Q&A, and case analysis; and the information formats include text, images, audio, and video.

[0026] Step 2: Based on the target user's viewing behavior of each push notification within the first preset period, the personal characteristic information of the target user is obtained. At the same time, the target user's understanding of the first phase of popular science is also analyzed. Then, the target user's personal characteristic information and understanding of the first phase of popular science are combined to push information for the second preset period, and the viewing behavior of each push notification by the target user within the second preset period is collected.

[0027] It should be noted that the first preset cycle is the first science popularization stage, and similarly, the second preset cycle is the second science popularization stage. The setting method of the second preset cycle is the same as that of the first preset cycle, so it will not be described again.

[0028] In a specific example, the personal characteristic information of the target user is obtained by analyzing the target user's viewing of each push message within a first preset period. The specific process is as follows: Based on the target user's viewing of each push message within the first preset period, the information style and format of each message viewed by the target user in each target time period, as well as the information style and format of each push message, are obtained. Then, the number of messages viewed and the number of push messages of each style in each target time period are counted. Similarly, the number of messages viewed and the number of push messages of each format in each target time period are counted. The number of messages viewed and the number of push messages of each style in each target time period are divided by the number of push messages of the corresponding message to obtain the viewing ratio of each style of information in each target time period. Similarly, the number of messages viewed and the number of push messages of each format in each target time period are divided by the number of push messages of the corresponding message to obtain the viewing ratio of each format of information in each target time period.

[0029] Then, based on the target user's viewing of each push message within the first preset period, the number of push messages and the number of messages viewed in each target time period are obtained. The number of messages viewed in each target time period is divided by the number of push messages in the corresponding period to obtain the information viewing ratio in each target time period.

[0030] In a specific example, the simultaneous analysis of the target user's understanding of the first phase of popular science is carried out as follows: based on the target user's viewing of each pushed information within the first preset period, the types of information viewed and the viewing duration of each target time period are obtained, and thus the target user's viewed information and viewing duration within the first preset period are obtained.

[0031] The system compares the viewing time of each piece of information viewed by the target user with the set information viewing time threshold. If the viewing time of a piece of information is less than the set information viewing time threshold, the viewed information is updated as invalid. If the viewing time of a piece of information is greater than or equal to the set information viewing time threshold, the viewed information is updated as valid. Based on this, the system re-acquires each piece of valid information viewed by the target user within the first preset period.

[0032] It should be noted that the information viewing time threshold is set by the relevant staff based on the specific information content, and no specific restrictions are imposed here.

[0033] The information types of each valid search result are compared with the types of basic science information. If the information types of each valid search result include all types of basic science information, then the target user will be pushed information in the second stage of science popularization. Otherwise, the target user will still be pushed information in the first stage of science popularization.

[0034] In a specific example, the second preset period of information push is further combined with the target user's personal characteristics and their level of understanding of the first stage of popular science. The specific process is as follows: Based on the target user's personal characteristics, the information viewing ratio of the target user in each target time period is obtained. When the target user's information viewing ratio in a certain target time period is less than one-half, the number of information pushes in the second preset period for that target time period is reduced according to a preset ratio. When the target user's information viewing ratio in a certain target time period is greater than or equal to one-half, the number of information pushes in the second preset period for that target time period is increased according to a preset ratio.

[0035] Simultaneously, based on the target user's personal characteristic information, the proportion of the target user's viewing of information of various styles and the proportion of viewing of information of various forms in each target time period are obtained. When the target user's viewing proportion of information of a certain style in a certain target time period is greater than one-half, the push proportion of information of that style in the second preset period is increased according to the preset proportion. When the target user's viewing proportion of information of a certain style in a certain target time period is less than or equal to one-half, the push proportion of information of that style in the second preset period is decreased according to the preset proportion.

[0036] It should be noted that the preset ratios are all set by relevant staff. For example, when the information viewing ratio of a target user in a certain target time period is three-quarters, the number of information pushes in the second preset period for that target time period is increased by three times; or, for example, when the target user's viewing ratio for a certain style of information in a certain target time period is three-quarters, the calculation formula is used: The proportion of push notifications for this style of information within the target time period in the second preset period is obtained. The above example is only for illustrative purposes and is not the only limitation.

[0037] Step 3: After the information push is completed in the second preset period, determine whether to conduct a science popularization content test on the target users based on the target users' viewing of each pushed information within the second preset period, and then determine whether the target users have completed this science popularization learning.

[0038] It should be noted that the content of the target user's viewing of each push message in the second preset period is the same as that in the target user's viewing of each push message in the first preset period.

[0039] In a specific example, the process of determining whether to conduct a science popularization content test on the target user based on the target user's viewing of each push message within the second preset period is as follows: Based on the analysis of the target user's viewing of each push message within the second preset period, the types of information viewed and the viewing duration of each target time period of the target user are obtained, thereby obtaining the target user's viewed information and viewing duration within the second preset period.

[0040] Based on the analysis of the target user's viewed information and viewing duration within the second preset period, the effective viewed information of the target user within the second preset period is obtained.

[0041] It should be noted that the effective information viewed by the target user in the second preset period is obtained by analyzing the information viewed and the viewing time of the target user in the second preset period. The analysis method is the same as that for the effective information viewed in the first preset period.

[0042] The information types of each valid search query are compared with the types of advanced science popularization information. If the information types of each valid search query include all types of intermediate science popularization information, it is determined that science popularization content testing will be conducted on the target users; otherwise, it is determined that science popularization content testing will not be conducted on the target users.

[0043] In a specific example, the testing of popular science content proceeds as follows: Based on the analysis of the target users' viewing of each push notification within the second preset period, the number of times the target users viewed each style of information and each form of information, as well as the total number of information viewed, are obtained. The number of times the target users viewed each style of information and each form of information within the second preset period are compared with the total number of information viewed to obtain the viewing ratio of each style of information and each form of information. The information style and form with the highest viewing ratio are recorded as the target user's test information style and test information form.

[0044] At the same time, target users can choose the type of science popularization test themselves, which includes knowledge challenge test and scenario simulation test.

[0045] The science popularization test is conducted on the target users based on the type of test, style, and format of the test information.

[0046] In a specific example, the process of determining whether the target user has completed the current science popularization learning is as follows: the target user's test score is obtained based on the science popularization test, and the target user's test score is compared with a set test score threshold. When the target user's test score is greater than or equal to the set test score threshold, it is determined that the target user has completed the current science popularization learning and can be pushed the next type of science popularization information. Otherwise, it is determined that the target user has not completed the current science popularization learning and cannot be recommended the next type of science popularization information.

[0047] The test score threshold is 70% of the total test score.

[0048] In a specific instance, the recommendation process for the next type of popular science information is the same as the recommendation process for the current popular science information.

[0049] The AI-powered intelligent terminal information management and push method provided in this application implements personalized information push and evaluation by dividing the science popularization learning challenge into two stages. Within the first preset period, the target time period and the number of pushes are determined based on the user's historical browsing data. Information browsing data within the first preset period is collected, and user personal characteristics are analyzed. Simultaneously, the user's level of science popularization understanding is evaluated based on the coverage of effective browsing information. The number of pushes and the proportion of information styles are dynamically adjusted accordingly. Finally, a test is conducted based on the user's preferred style and format and self-selected test type. Those who pass the test proceed to the next stage of science popularization learning. This application achieves personalized push by accurately capturing user behavioral characteristics, improving the efficiency of science popularization information browsing, ensuring the systematic and continuous nature of learning, and enhancing the relevance and interest of science popularization learning for teenagers.

[0050] The above content is merely an example and illustration of the concept of this application. Those skilled in the art can make various modifications or additions to the specific embodiments described or use similar methods to replace them, as long as they do not deviate from the inventive concept or exceed the scope defined in this application, they should all fall within the protection scope of this application.

Claims

1. An AI-powered intelligent terminal information management and push method, characterized in that, include: Step 1: Push information to target users according to preset information push data within the first preset period, and collect the target users' viewing status of each pushed information within the first preset period. Step 2: Based on the target user's viewing behavior of each push notification within the first preset period, the personal characteristic information of the target user is obtained. At the same time, the target user's understanding of the first phase of popular science is also analyzed. Then, the target user's personal characteristic information and understanding of the first phase of popular science are combined to push information for the second preset period, and the viewing behavior of the target user of each push notification within the second preset period is collected. Step 3: After the information push is completed in the second preset period, determine whether to conduct a science popularization content test on the target users based on the target users' viewing of each pushed information within the second preset period, and then determine whether the target users have completed this science popularization learning.

2. The AI ​​intelligent terminal information management and push method according to claim 1, characterized in that, The process of pushing information to the target user according to preset information push data within the first preset period is as follows: Users participating in the science learning challenge are recorded as target users. First, the historical information browsing data of the target users is obtained from the terminal. The historical information browsing data includes the target users' smart terminal usage time periods and the average number of information browsing in each time period, which are respectively recorded as the target time periods of the first preset period and the target push quantity corresponding to each target time period. Then, retrieve the basic science information from the data center of the current science learning challenge, and push the basic science information to the terminal devices of the target users according to the corresponding target push quantity in each target time period of the first preset cycle.

3. The AI ​​intelligent terminal information management and push method according to claim 2, characterized in that, The data collection includes the target user's viewing status of each push notification within the first preset period, including the number of push notifications in each target time period, the viewing duration of each viewed notification, the information type, information style, and information format of each viewed notification.

4. The AI ​​intelligent terminal information management and push method according to claim 3, characterized in that, The process of analyzing the target user's viewing behavior of each push notification within a first preset period to obtain the target user's personal characteristic information is as follows: Based on the target user's viewing of each push message within the first preset period, the information style and format of each viewed message and each push message are obtained in each target time period. Then, the number of viewed messages and the number of push messages of each style in each target time period are calculated. Similarly, the number of viewed messages and the number of push messages of each format in each target time period are calculated. The number of viewed messages of each style in each target time period is divided by the number of push messages of the corresponding message to obtain the viewing ratio of each style of information in each target time period. Similarly, the number of viewed messages of each format in each target time period is divided by the number of push messages of the corresponding message to obtain the viewing ratio of each format of information in each target time period. Then, based on the target user's viewing of each push message within the first preset period, the number of push messages and the number of messages viewed in each target time period are obtained. The number of messages viewed in each target time period is divided by the number of push messages in the corresponding period to obtain the information viewing ratio in each target time period.

5. The AI ​​intelligent terminal information management and push method according to claim 4, characterized in that, The simultaneous analysis yields the target user's level of understanding of the first phase of science popularization. The specific process is as follows: Based on the target user's viewing of each push message within the first preset period, obtain the types of information viewed and the viewing duration of each target time period, and thereby obtain the target user's viewed information and viewing duration within the first preset period. The system compares the viewing time of each piece of information viewed by the target user with the set information viewing time threshold. If the viewing time of a piece of information is less than the set information viewing time threshold, the viewed information is updated as invalid viewing information. If the viewing time of a piece of information is greater than or equal to the set information viewing time threshold, the viewed information is updated as valid viewing information. Based on this, the system re-acquires each piece of valid viewing information of the target user within the first preset period. The information types of each valid search result are compared with the types of basic science information. If the information types of each valid search result include all types of basic science information, then the target user will be pushed information in the second stage of science popularization. Otherwise, the target user will still be pushed information in the first stage of science popularization.

6. The AI ​​intelligent terminal information management and push method according to claim 5, characterized in that, The second preset period of information push is then conducted by comprehensively considering the target user's personal characteristics and their level of understanding of the first phase of science popularization. The specific process is as follows: Based on the target user's personal characteristics, obtain the information viewing ratio of the target user in each target time period. When the information viewing ratio of the target user in a certain target time period is less than one-half, reduce the number of information pushes in the second preset period for that target time period according to the preset ratio. When the information viewing ratio of the target user in a certain target time period is greater than or equal to one-half, increase the number of information pushes in the second preset period for that target time period according to the preset ratio. Simultaneously, based on the target user's personal characteristic information, the proportion of the target user's viewing of information of various styles and the proportion of viewing of information of various forms in each target time period are obtained. When the target user's viewing proportion of information of a certain style in a certain target time period is greater than one-half, the push proportion of information of that style in the second preset period is increased according to the preset proportion. When the target user's viewing proportion of information of a certain style in a certain target time period is less than or equal to one-half, the push proportion of information of that style in the second preset period is decreased according to the preset proportion.

7. The AI ​​intelligent terminal information management and push method according to claim 6, characterized in that, The process of determining whether to conduct science popularization content testing on target users based on their viewing behavior of each push notification within the second preset period is as follows: Based on the analysis of the target user's viewing of each push message within the second preset period, the types of information viewed and the viewing duration of each target time period are obtained, and the information viewed and the viewing duration of each target user within the second preset period are obtained accordingly. Based on the analysis of the target user’s viewed information and viewing duration within the second preset period, we obtain the target user’s valid viewed information within the second preset period. The information types of each valid search query are compared with the types of advanced science popularization information. If the information types of each valid search query include all types of intermediate science popularization information, it is determined that science popularization content testing will be conducted on the target users; otherwise, it is determined that science popularization content testing will not be conducted on the target users.

8. The AI ​​intelligent terminal information management and push method according to claim 7, characterized in that, The science popularization content test process is as follows: Based on the analysis of the target user's viewing of each push message within the second preset period, the number of times the target user viewed each style of information and each form of information, as well as the number of messages viewed, are obtained within the second preset period. The number of times the target user viewed each style of information and each form of information within the second preset period are compared with the number of messages viewed to obtain the viewing ratio of each style of information and each form of information. The information style and information form with the highest viewing ratio are recorded as the target user's test information style and test information form. At the same time, target users can choose the type of science popularization test themselves, which includes knowledge challenge test and scenario simulation test; The science popularization test is conducted on the target users based on the type of test, style, and format of the test information.

9. The AI ​​intelligent terminal information management and push method according to claim 8, characterized in that, The process of determining whether the target user has completed the science popularization learning is as follows: The test scores of target users are obtained through science popularization tests. The test scores of target users are compared with the set test score thresholds. When the test scores of target users are greater than or equal to the set test score thresholds, it is determined that the target users have completed the current science popularization learning and can be pushed the next type of science popularization information. Otherwise, it is determined that the target users have not completed the current science popularization learning and cannot be recommended the next type of science popularization information.

10. The AI ​​intelligent terminal information management and push method according to claim 9, characterized in that, The recommendation process for the next type of science popularization information is the same as the current recommendation process for science popularization information.

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