CN118714523B - Information interaction method and system based on 5G message - Google Patents
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Abstract
本发明公开了一种基于5G消息的信息交互方法及系统，涉及移动通信技术领域，包括，利用设备内置的传感器数据分析设备的使用模式，通过用户情境识别模型输出用户所处的情境标签；基于情境标签，自动调整消息展示形式与交互方式；根据用户设备能力和网络状况，对消息内容进行多模态编排；对编排后的多模态消息内容进行深度学习算法审核，并依据用户偏好个性化排序审核通过的消息，输出审核通过且排序完成的消息队列；通过5G网络发送消息队列至接收者，接收端再次执行情境分析，输出为根据接收者情境优化后的消息展示，完成交互过程。本发明不仅显著提升了5G消息服务的智能化水平和用户体验，也为未来信息交互技术的发展开辟了新的方向。
The present invention discloses a method and system for information interaction based on 5G messages, which relates to the field of mobile communication technology, including: using the sensor data built into the device to analyze the usage mode of the device, and outputting the context label of the user through the user context recognition model; based on the context label, automatically adjusting the message display form and interaction mode; multi-modal arrangement of the message content according to the user device capability and network status; deep learning algorithm review of the arranged multi-modal message content, and personalized sorting of the reviewed and approved messages according to user preferences, and outputting the message queue that has passed the review and completed the sorting; sending the message queue to the receiver through the 5G network, and the receiving end performing context analysis again, and outputting the message display optimized according to the receiver's context, completing the interaction process. The present invention not only significantly improves the intelligence level and user experience of 5G message services, but also opens up a new direction for the development of future information interaction technology.
Description
Technical Field
The invention relates to the technical field of mobile communication, in particular to an information interaction method and system based on 5G information.
Background
Under the background of rapid development of information technology, commercial deployment of a fifth generation mobile communication technology (5G) has the characteristics of ultrahigh speed, low delay and high connection density, revolutionary transformation is brought to the field of information interaction, however, how to efficiently and intelligently utilize the advantages of the 5G technology, and the intelligent level of information interaction is improved, so that the method and the device become key problems to be solved urgently.
Despite the great development of 5G messaging services in terms of transmission speed and capacity, challenges remain: the singulation of information display and interaction can not be fully adapted to various situations of users, so that the experience quality is reduced; the content arrangement and adaptation method is relatively solidified, so that the performance difference and network fluctuation of the user equipment are difficult to dynamically cope with, and the optimal display effect is influenced; the information auditing and personalized sequencing technology is lagged, the automatic auditing efficiency is low, large-scale data are difficult to process, the personalized sequencing is simply dependent on a user preference model, and accurate matching driven by deep learning is lacking.
Disclosure of Invention
The present invention has been made in view of the above-described problems occurring in the prior art.
Therefore, the invention provides an information interaction method, an information interaction device, computer equipment and a storage medium based on 5G information, which solve the problems of insufficient suitability of information interaction situation and slow response of personalized requirements in a 5G environment.
In order to solve the technical problems, the invention provides the following technical scheme:
In a first aspect, an embodiment of the present invention provides an information interaction method based on a 5G message, which includes outputting, by using a user context recognition model, a context label where a user is located by using a usage mode of a sensor data analysis device built in the device;
Automatically adjusting the message display form and the interaction mode based on the situation label;
according to the capability of the user equipment and the network condition, the message content is arranged in a multi-mode manner;
Performing deep learning algorithm auditing on the content of the arranged multi-mode message, and individually ordering the audited messages according to the user preference, and outputting a message queue which passes the auditing and is ordered;
and sending the message queue to a receiver through a 5G network, and executing the situation analysis again by the receiver, outputting the message to display the optimized message according to the situation of the receiver, thereby completing the interaction process.
As a preferable scheme of the information interaction method based on 5G message in the invention, the method comprises the following steps: the use mode of the user equipment comprises screen on-off time, application program use frequency and charging state.
As a preferable scheme of the information interaction method based on 5G message in the invention, the method comprises the following steps: the specific operation steps of outputting the situation label of the user through the user situation recognition model are as follows:
Cleaning the collected original data, removing abnormal values, performing time sequence smoothing to reduce noise interference, and converting various data into a uniform format;
integrating the preprocessed data into feature vectors;
Loading a user situation recognition model which is trained through a large number of tag data sets, inputting feature vectors into the model, and outputting the prediction probability of each situation category;
and selecting the situation label with the highest probability as the current situation of the user according to the probability distribution output by the model.
As a preferable scheme of the information interaction method based on 5G message in the invention, the method comprises the following steps: based on the situation label, the message display form and the interaction mode are automatically adjusted, and the specific operation steps are as follows:
Constructing a situation response strategy library, including user situations in driving, meeting and home;
For the user context in driving, a policy repository contains a specific set of rules, including,
Priority adjustment: urgent messages have a higher priority than non-urgent messages;
screen brightness automatic adjustment: the screen brightness during night driving is reduced, so that the driving safety is influenced by anti-dazzle;
and (3) interface simplification: the interface layout is simplified, the complex operation is removed, and key function buttons for answering and refusing call and controlling voice messages are reserved;
automatically triggering corresponding strategies in a situation response strategy library according to the situation label system with the highest probability;
immediately switching the user interface to a very simple mode, folding an unnecessary character input area, and amplifying key buttons;
The system automatically starts a text-to-speech function, sets a default message receiving mode as speech playing, and configures a speech recognition module for standby so as to prepare for receiving a speech instruction of a user;
According to a preset specific rule set, the system automatically screens and distinguishes the received message as urgent and non-urgent, the non-urgent text message is automatically converted into voice broadcasting, and the urgent message draws the attention of a user through a special prompt tone and gives a short text abstract preview;
based on the real-time geographic position of the user, the system uses the geofence technology to outline a certain range around the user, and takes the area as a boundary to screen related information;
Extracting merchant offers, activity information and traffic condition updating contents related to geographic positions from a database, and scoring the relevance of each content by combining historical preferences and behavior modes of a user through a collaborative filtering algorithm;
Sorting the contents according to the score, and selecting the most relevant information to form a personalized recommendation list;
text-to-speech conversion of titles and summaries of recommended content;
and monitoring a voice command of the user, and executing corresponding operation by the system according to the command.
As a preferable scheme of the information interaction method based on 5G message in the invention, the method comprises the following steps: according to the capability of the user equipment and the network condition, the message content is arranged in a multi-mode manner, and the specific operation steps are as follows:
inquiring user equipment information through an API, and monitoring the current network connection speed and stability;
When the equipment supports AR and the network condition is good, a 3D model is added to provide high-definition image and video experience;
when the equipment resources are limited, reducing the use of images and videos;
According to the network bandwidth level, adopting different resolutions and compression standards;
According to the importance of the information and the instant requirement of the user, layering and arranging the text, voice, image, video and AR content, preferentially displaying key information in a text and voice mode, and providing immersive experience by taking the enhanced content as auxiliary information;
An intuitive interaction entrance is designed for each modal content, so that a user can conveniently operate in different environments;
In the process of playing the message content, continuously monitoring the load of a CPU (Central processing Unit), a GPU (graphics processing Unit) and the network flow by a background;
When performance bottlenecks and network fluctuations are detected, content quality is automatically reduced until the original settings are restored after environmental conditions are improved.
As a preferable scheme of the information interaction method based on 5G message in the invention, the method comprises the following steps: performing deep learning algorithm auditing on the content of the arranged multi-mode message, and individually ordering and auditing passing messages according to user preferences, and outputting an auditing passing and ordering completed message queue, wherein the specific operation steps are as follows:
constructing a deep learning auditing model, splitting the multi-mode message content into a text segment, an image frame and a video segment, and sending the text segment, the image frame and the video segment into the auditing model for analysis;
Identifying sensitive information in text, images, videos and AR content, setting a sensitivity threshold for each type of content, allowing the content below the threshold to pass through directly, and allowing the content above the threshold to enter manual review and direct rejection;
for the content which contains sensitive information but does not form violations, the system automatically adds a warning label containing the sensitive information and prompts a user to confirm whether to continue to send or not;
Based on historical browsing, praying and sharing behavior data of the user, establishing a user preference model by utilizing collaborative filtering;
Generating a personalized sequencing list by adopting a multi-objective optimization algorithm;
according to the personalized sequencing result, the message content with the auditing state and the sensitive information label is organized into a message queue, and the message queue is in butt joint with a message sending service through a RESTful API interface to prepare for distribution to a target user group.
As a preferable scheme of the information interaction method based on 5G message in the invention, the method comprises the following steps: the method comprises the steps of sending a message queue to a receiver through a 5G network, executing context analysis again by a receiving end, outputting the message to display the message after the optimization according to the context of the receiver, and completing an interaction process, wherein the specific operation steps are as follows:
dynamically selecting an optimal path according to the position of a receiver and the network condition;
Pushing the message queue to a 5G message application of a receiver through an MQTT protocol;
The receiving end application monitors the state of the user equipment in real time, and analyzes the message receiving mode of the user tendency under the specific situation by combining the historical use habit;
adopting a logistic regression model, rapidly judging the most suitable display mode according to the collected information, and converting the multimedia content;
The message display interface layout is adaptively adjusted for different devices and scenes.
In a second aspect, the present invention provides an information interaction system based on 5G messages, comprising,
Context awareness and data collection module: analyzing the use mode of the equipment by utilizing sensor data built in the equipment, and outputting a situation label of the user through a user situation recognition model;
The context adaptive interaction design module: automatically adjusting the message display form and the interaction mode based on the situation label;
a multi-modal content optimization and orchestration module: according to the capability of the user equipment and the network condition, the message content is arranged in a multi-mode manner;
An intelligent content auditing and personalized sequencing module: performing deep learning algorithm auditing on the content of the arranged multi-mode message, and individually ordering the audited messages according to the user preference, and outputting a message queue which passes the auditing and is ordered;
5G network transmission and receiving end adaptation module: and sending the message queue to a receiver through a 5G network, and executing the situation analysis again by the receiver, outputting the message to display the optimized message according to the situation of the receiver, thereby completing the interaction process.
In a third aspect, embodiments of the present invention provide a computer apparatus comprising a memory and a processor, the memory storing a computer program, wherein: the computer program, when executed by a processor, implements any of the steps of the 5G message based information interaction method according to the first aspect of the invention.
In a fourth aspect, embodiments of the present invention provide a computer-readable storage medium having a computer program stored thereon, wherein: the computer program, when executed by a processor, implements any of the steps of the 5G message based information interaction method according to the first aspect of the invention.
The invention has the beneficial effects that: the use mode of the equipment is analyzed by utilizing sensor data built in the equipment, accurate situation label generation is realized through a situation recognition model, the relativity and timeliness of information pushing are improved, a foundation is laid for personalized interaction, the problems of weak situation awareness and low matching degree of the traditional pushing are solved, and user experience is enhanced; according to the situation label, the interface and the interaction mode are automatically optimized, and efficient communication is realized; according to the user equipment and network conditions, dynamically arranging multi-mode message contents, ensuring smooth information transmission, adapting to different equipment capabilities and improving the reliability and efficiency of interaction; the deep learning is utilized to audit the content and order the content according to the user preference, so that the information security is enhanced, the content individuation is realized, the information overload is reduced, the user experience is optimized, the user viscosity is enhanced, and the effective transmission of the information is promoted.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings required for the description of the embodiments will be briefly described below, it being obvious that the drawings in the following description are only some embodiments of the present invention, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a flowchart of an information interaction method based on a 5G message in embodiment 1.
FIG. 2 is a sensitivity threshold determination chart in example 1.
Detailed Description
In order that the above-recited objects, features and advantages of the present invention will become more readily apparent, a more particular description of the invention will be rendered by reference to specific embodiments thereof which are illustrated in the appended drawings.
In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention, but the present invention may be practiced in other ways other than those described herein, and persons skilled in the art will readily appreciate that the present invention is not limited to the specific embodiments disclosed below.
Further, reference herein to "one embodiment" or "an embodiment" means that a particular feature, structure, or characteristic can be included in at least one implementation of the invention. The appearances of the phrase "in one embodiment" in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments.
Embodiment 1, referring to fig. 1 and 2, is a first embodiment of the present invention, and this embodiment provides an information interaction method based on a 5G message, which includes the following steps:
S1, analyzing the use mode of the user equipment by using sensor data built in the equipment, wherein the use mode comprises screen on-off time, application program use frequency and charging state.
Furthermore, the accurate longitude and latitude coordinates are obtained through the GPS module, and meanwhile, the position accuracy in an indoor environment or in an environment with poor signals is enhanced by combining a base station positioning technology (such as A-GPS), and the frequency is set to be updated once per minute so as to balance the accuracy and the energy consumption;
the motion state (such as stillness, walking, running and driving) of the equipment is judged through the sensors such as an accelerometer, a gyroscope and the like, and the recognition accuracy is improved by utilizing a motion pattern recognition algorithm;
the most recently used list of applications is analyzed, high frequency application categories (e.g., social, news, health) are identified, and the distribution of active times within the application reflects the user's immediate points of interest.
S2, outputting a situation label where a user is located through a user situation recognition model, wherein the specific operation steps are as follows:
Cleaning the collected original data, removing abnormal values (such as geographical position information with obvious errors), and performing time sequence smoothing to reduce noise interference;
converting various data into a unified format, such as converting geographic positions into standardized geographic codes, unifying time stamps into UTC standard time, and encoding motion states into predefined categories;
integrating the preprocessed data into feature vectors, wherein each feature corresponds to a data type, such as geographic position features, time features and the like;
loading a user context recognition model (including geographic location, time, motion state, application use and corresponding context labels) that has been trained with a large number of marker datasets;
inputting the feature vector into a model, wherein the model adopts a multi-layer neural network structure, and comprises an embedded layer, a hidden layer (using a ReLU activation function) and an output layer (using a Softmax function for probability distribution), and outputting the prediction probability of each situation category;
and selecting the situation label with the highest probability as the current situation of the user according to the probability distribution output by the model.
S3, based on the situation label, automatically adjusting a message display form and an interaction mode, wherein the specific operation steps are as follows:
Constructing a situation response strategy library, including user situations in driving, meeting and home;
For the user context in driving, a policy repository contains a specific set of rules, including,
Priority adjustment: urgent messages have a higher priority than non-urgent messages;
screen brightness automatic adjustment: the screen brightness during night driving is reduced, so that the driving safety is influenced by anti-dazzle;
and (3) interface simplification: the interface layout is simplified, the complex operation is removed, and key function buttons for answering and refusing call and controlling voice messages are reserved;
automatically triggering corresponding strategies in a situation response strategy library according to the situation label system with the highest probability;
immediately switching the user interface to a very simple mode, folding the unnecessary text input area, and amplifying key buttons (such as answering/rejecting calls and voice message control) to reduce the sight line transfer time;
The system automatically starts a text-to-speech function, sets a default message receiving mode as speech playing, and configures a speech recognition module for standby so as to prepare for receiving a speech instruction of a user;
According to a preset specific rule set, the system automatically screens and distinguishes the received message as urgent and non-urgent, the non-urgent text message is automatically converted into voice broadcasting, and the urgent message draws the attention of a user through a special prompt tone and gives a short text abstract preview;
based on the real-time geographic position of the user, the system uses the geofence technology to outline a certain range around the user, and takes the area as a boundary to screen related information;
Extracting merchant offers, activity information and traffic condition updating contents related to geographic positions from a database, and scoring the relevance of each content by combining historical preferences and behavior modes of a user through a collaborative filtering algorithm;
Sorting the contents according to the score, selecting the most relevant information to form a personalized recommendation list, wherein the list comprises a short title, a voice abstract and quick navigation options;
text-to-speech conversion is carried out on titles and abstracts of recommended contents, so that a user can acquire important information through hearing in the driving process, and meanwhile, the eyes and hands are kept focused on driving tasks;
And monitoring voice instructions of the user, such as 'neglect', 'later reminding' or 'more details', and performing corresponding operations by the system according to the instructions, such as skipping current information, setting reminding or voice broadcasting of detailed information.
S4, according to the capability of the user equipment and the network condition, the message content is arranged in a multi-mode, and the specific operation steps are as follows:
Inquiring user equipment information through an API (application program interface), including but not limited to screen size, resolution, processor model, GPU (graphics processing Unit) capability, whether AR (augmented reality) and other functions are supported, monitoring current network connection speed and stability, evaluating real-time bandwidth by using HTTP SPEED +mobility or similar algorithms, and classifying the real-time bandwidth into three grades of low, medium and high;
When the equipment supports AR and the network condition is good, a 3D model is added, and for high-resolution large-screen equipment, high-definition images and video experience are provided on the premise of ensuring the content quality;
when the equipment resources are limited, the method focuses on optimizing text and voice contents, reducing the use of images and videos and ensuring the smooth basic functions;
According to the network bandwidth level, adopting different resolutions and compression standards, for example, when the network condition is bad, automatically switching to H.264 coding, reducing the resolution to 480p, and increasing the compression ratio; when the network is good, HEVC is adopted to maintain 1080p or higher resolution, so that the image quality is ensured, and delay is reduced;
According to the importance of the information and the instant requirement of the user, layering and arranging text, voice, images, video and AR content, preferentially displaying key information in a text and voice form, and providing immersive experience by taking enhanced content (such as video and AR) as auxiliary information;
An intuitive interaction entrance, such as touch, voice instruction or gesture control, is designed for each modal content, so that a user can conveniently operate in different environments;
in the process of playing the message content, the background continuously monitors the load of the CPU, the load of the GPU and the network flow, so that smooth user experience is ensured without jamming;
When performance bottlenecks and network fluctuations are detected, content quality is automatically reduced, e.g., video resolution is reduced, AR rendering is suspended, until the original settings are restored after environmental conditions are improved.
S5, performing deep learning algorithm auditing on the arranged multi-mode message content, and individually ordering and auditing passing messages according to user preferences, and outputting an auditing passing and ordering completed message queue, wherein the specific operation steps are as follows:
constructing a deep learning auditing model, splitting the multi-mode message content into a text segment, an image frame and a video segment, and sending the text segment, the image frame and the video segment into the auditing model for analysis;
Identifying sensitive information in text, images, videos and AR content, setting a sensitivity threshold for each type of content, allowing the content below the threshold to pass through directly, and allowing the content above the threshold to enter manual review and direct rejection;
For contents which contain sensitive information but do not form violations, such as personal medical record screenshot uploaded by a user, the system automatically adds a warning label containing the sensitive information and prompts the user to confirm whether to continue to send;
Based on historical browsing, praying and sharing behavior data of the user, establishing a user preference model by utilizing collaborative filtering;
Adopting a multi-objective optimization algorithm (such as weighted linear combination or Pareto front exploration), comprehensively considering the factors such as novelty, popularity, correlation with user interests and the like of the content, and generating a personalized ranking list;
according to the personalized sequencing result, the message content with the auditing state and the sensitive information label is organized into a message queue, and the message queue is in butt joint with a message sending service through a RESTful API interface to prepare for distribution to a target user group.
Identifying sensitive image elements using a target detection technique;
identifying bad contents such as improper behaviors through space-time characteristic analysis;
the AR elements are converted into 3D models or key frames, and an image recognition technology is applied for examination.
Further, the sensitivity threshold α is specifically divided as follows:
When alpha is more than or equal to 0 and less than or equal to 0.6, the security area does not detect sensitive information in the content, and the security area directly passes the auditing without special treatment;
when alpha is more than or equal to 0.6 and less than or equal to 0.8, the warning area contains slightly sensitive information or potential risks in the content, more detailed examination is needed for texts, images and videos, and the comprehensive influence is analyzed for AR content;
When alpha is more than or equal to 0.8 and less than or equal to 0.9, reviewing the area, wherein the content contains more obvious sensitive information, text, images, video and AR content, and performing manual review to determine whether the modification can be issued or required;
when alpha is more than or equal to 0.9 and less than or equal to 1.0, the refused area definitely contains serious violations or highly sensitive information, and the release is refused directly.
S6, sending a message queue to a receiver through a 5G network, and executing context analysis again by the receiver, outputting the context analysis to display the message optimized according to the context of the receiver, so as to complete the interaction process, wherein the specific operation steps are as follows:
according to the position of the receiver and the network condition, dynamically selecting an optimal path, reducing the loss and delay of the data packet, and improving the transmission efficiency;
Pushing the message queue to a 5G message application of a receiver through an MQTT protocol;
The receiving end application monitors the state of the user equipment in real time, including but not limited to geographic position, equipment type, screen size, network connection condition and activity mode (such as walking, driving and static), and analyzes the message receiving mode (text, voice, image or video) of the user tendency under specific situations by combining the historical use habit;
Adopting a logistic regression model, rapidly judging the most suitable display mode according to the collected information, and converting the multimedia content, for example, when detecting that a user is driving, automatically selecting a voice broadcast as a preferred display form by the model;
The message presentation interface layout is adaptively adjusted for different devices and scenarios, ensuring user friendliness, e.g., preferential display of core message summaries on small screen devices.
The embodiment also provides an information interaction system based on the 5G message, which comprises a context awareness and data collection module: analyzing the use mode of the equipment by utilizing sensor data built in the equipment, and outputting a situation label of the user through a user situation recognition model;
The context adaptive interaction design module: automatically adjusting the message display form and the interaction mode based on the situation label;
a multi-modal content optimization and orchestration module: according to the capability of the user equipment and the network condition, the message content is arranged in a multi-mode manner;
An intelligent content auditing and personalized sequencing module: performing deep learning algorithm auditing on the content of the arranged multi-mode message, and individually ordering the audited messages according to the user preference, and outputting a message queue which passes the auditing and is ordered;
5G network transmission and receiving end adaptation module: and sending the message queue to a receiver through a 5G network, and executing the situation analysis again by the receiver, outputting the message to display the optimized message according to the situation of the receiver, thereby completing the interaction process.
The embodiment also provides a computer device, which is applicable to the situation of the information interaction method based on the 5G message, and comprises the following steps: a memory and a processor; the memory is configured to store computer executable instructions, and the processor is configured to execute the computer executable instructions to implement the information interaction method based on 5G messages as set forth in the above embodiment.
The computer device may be a terminal comprising a processor, a memory, a communication interface, a display screen and input means connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The communication interface of the computer device is used for carrying out wired or wireless communication with an external terminal, and the wireless mode can be realized through WIFI, an operator network, NFC (near field communication) or other technologies. The display screen of the computer equipment can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer equipment can be a touch layer covered on the display screen, can also be keys, a track ball or a touch pad arranged on the shell of the computer equipment, and can also be an external keyboard, a touch pad or a mouse and the like.
The present embodiment also provides a storage medium having stored thereon a computer program which, when executed by a processor, implements the method for implementing 5G message based information interaction as proposed in the above embodiments; the storage medium may be implemented by any type or combination of volatile or nonvolatile Memory devices, such as static random access Memory (Static Random Access Memory, SRAM), electrically erasable Programmable Read-Only Memory (ELECTRICALLY ERASABLE PROGRAMMABLE READ-Only Memory, EEPROM), erasable Programmable Read-Only Memory (Erasable Programmable Read Only Memory, EPROM), programmable Read-Only Memory (PROM), read-Only Memory (ROM), magnetic Memory, flash Memory, magnetic disk, or optical disk.
In summary, by utilizing the use mode of the sensor data analysis equipment built in the equipment and utilizing the situation recognition model, the invention realizes accurate situation label generation, improves the relativity and timeliness of information pushing, lays a foundation for personalized interaction, solves the problems of weak situation perception and low matching degree of the traditional pushing, and enhances the user experience; according to the situation label, the interface and the interaction mode are automatically optimized, and efficient communication is realized; according to the user equipment and network conditions, dynamically arranging multi-mode message contents, ensuring smooth information transmission, adapting to different equipment capabilities and improving the reliability and efficiency of interaction; the deep learning is utilized to audit the content and order the content according to the user preference, so that the information security is enhanced, the content individuation is realized, the information overload is reduced, the user experience is optimized, the user viscosity is enhanced, and the effective transmission of the information is promoted.
Example 2
Referring to table 1, experimental simulation data of the information interaction method based on the 5G message is given for the second embodiment of the present invention, in order to further verify the advancement of the present invention.
Firstly, representative user equipment is selected through experiments, wherein the representative user equipment comprises a high-performance smart mobile phone, a middle-end tablet computer and a basic function mobile phone, so that interactive performance under different equipment capabilities is evaluated.
In addition, the experiment also considers the network conditions of different geographic positions of city centers, suburbs, mobile vehicles and the like, and peak time periods and off-peak time periods so as to fully investigate the adaptability of the system.
A training set containing 10,000 pieces of marking data is constructed, the training set covers user behavior modes under various situations and is used for training a user situation recognition model, the model adopts an LSTM neural network structure, and 92% accuracy is realized through cross verification. The specific table is shown below:
table 1, 5G information interaction method performance evaluation experiment record table
From the comparative analysis of the experimental data, it can be seen that the embodiments fully demonstrate the innovativeness and advantages of the 5G message-based information interaction method. Firstly, the accuracy of the situation label is high, for example, in the test object 001, the system accurately identifies the situation of 'mobile shopping' through the comprehensive analysis of the real-time geographic position (city center) and the application activity record (shopping application), and then the situation label is automatically adjusted to be in the display form of voice and short text abstract, so that the convenience of the user in walking is greatly improved, the user satisfaction degree score reaches 4.7, and the validity of personalized adjustment is proved.
Second, the suitability for different devices and network environments is verified. For example, under the conditions of a basic function mobile phone and a mobile network, the test object 003 intelligently selects a pure voice broadcast, so that the requirement on equipment resources is reduced, and although the personalized ranking score is relatively low (6.9), the user satisfaction score indicates that the mode can still meet the basic requirement (3.9 points) under a specific situation.
Furthermore, the personalized ranking algorithm significantly improves the user experience. Under the high-performance mobile phone and stable home network environment, the test object 004 combines the historical preference of the user, the system provides the immersive experience of high-definition video+AR elements for the relevant 'home office' situation of work, the personalized ranking score is 9.2, the user satisfaction score is 4.9 points at the highest, and the successful application of the deep learning auditing and personalized ranking algorithm is proved.
In summary, the embodiment not only verifies the feasibility of the invention content in practical application, but also shows the remarkable advantages of adapting to the capability of user equipment, optimizing content display and improving the interaction efficiency of users, compared with the prior art, the method remarkably enhances the intelligentization and individuation level of the 5G message service and improves the user experience, thereby effectively proving the creativity and novelty of the invention.
It should be noted that the above embodiments are only for illustrating the technical solution of the present invention and not for limiting the same, and although the present invention has been described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that the technical solution of the present invention may be modified or substituted without departing from the spirit and scope of the technical solution of the present invention, which is intended to be covered in the scope of the claims of the present invention.
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| CN116980840A (en) * | 2023-04-19 | 2023-10-31 | 深圳德德电气科技有限公司 | Interactive communication management system and method based on 5G communication |
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