Intelligent message management system based on 5G

Abstract

The invention relates to the technical field of mobile communication, and discloses a 5G-based intelligent message management system, which comprises a message receiving module, a message analysis module, a message management module, a user interface module and a 5G network interface module, the message receiving module comprises a 5G communication unit and a multi-source adaptation unit; the message analysis module comprises a feature extraction unit, an analysis model unit and a classification decision unit; the message management module comprises a management strategy unit and an execution unit; the user interface module comprises a visualization unit and an interaction unit; the 5G network interface module comprises a protocol conversion unit and a network optimization unit; and the message analysis module and the message management module are arranged, so that an intelligent analysis model can be constructed by combining four types of features and adopting a multi-layer perceptron in combination with an attention mechanism, and the message classification accuracy is effectively improved.

Description

Technical Field

[0001] This invention relates to the field of mobile communication technology, and more specifically to a 5G-based intelligent message management system. Background Technology

[0002] With the development of mobile communication technology, 5G technology has become the mainstream of the new generation of communication technology. 5G technology has the characteristics of high speed, low latency, and high capacity, bringing more innovative applications to the field of mobile communication. In terms of message management, users receive a large number of SMS messages, emails, social media messages, etc. every day. These messages contain useful information and useless spam. Users need to spend a lot of time filtering and managing messages, which reduces communication efficiency. Therefore, it is necessary to study an intelligent message management system based on 5G technology to improve the efficiency of user message processing.

[0003] However, traditional 5G intelligent message management has not optimized message transmission for the characteristics of 5G networks, resulting in the underutilization of the advantages of 5G networks, high message sending and receiving latency and insufficient stability. Most messages are classified based on simple rules and cannot be accurately judged based on multi-dimensional features. Message management relies on manual operation by users and lacks automated strategies based on analysis results, which increases the cognitive and operational burden on users. Summary of the Invention

[0004] In order to overcome the above-mentioned defects of the prior art, the present invention provides a 5G-based intelligent message management system to solve the problems existing in the background art.

[0005] The present invention provides the following technical solution: a 5G-based intelligent message management system, comprising a message receiving module, a message analysis module, a message management module, a user interface module, and a 5G network interface module; The message receiving module is used to receive messages sent and received by users through the 5G network and transmit them to the message analysis module; the message receiving module includes a 5G communication unit and a multi-source adaptation unit; The message analysis module is used to receive data from the message receiving module, perform intelligent analysis on the received messages, identify the message type, importance, and urgency of the messages, classify the messages according to the analysis results, and transmit the classification results to the message management module; the message analysis module includes a feature extraction unit, an analysis model unit, and a classification decision unit; The message management module is used to receive the classification results of the message analysis module and to intelligently manage the user's messages. The message management module includes a management strategy unit and an execution unit. The user interface module is used to display the operation interface of the message management module, through which users can view and manage messages; the user interface module includes a visualization unit and an interaction unit; The 5G network interface module is used to enable communication between each module and the 5G network, and is connected to the message receiving module, message analysis module, message management module and user interface module respectively; the 5G network interface module includes a protocol conversion unit and a network optimization unit.

[0006] Preferably, the 5G communication unit is used to establish a wireless connection with a 5G base station; the multi-source adaptation unit is used to interface with different types of message sources; the feature extraction unit is used to extract feature parameters of the message; and the analysis model unit uses a multilayer perceptron based on the feature parameters. An intelligent analysis model is constructed by combining attention mechanisms to output the message type label of the message. Importance level and the degree of urgency The classification decision unit uses the message type labels output by the analysis model unit. Importance level and the degree of urgency The messages are divided according to the preset classification rules to obtain the message classification results.

[0007] Preferably, the feature parameters include message source features. Content keyword characteristics Time characteristics and user behavior characteristics The message source characteristics Identification information indicating the message sender, including contact ID, application account, and IP address; the content keyword features. By performing natural language processing on the message text content, key semantic information is extracted; the time features... The time difference between the message sending time and the current time; the user behavior characteristics This indicates the user's interaction preference for a certain type of message, determined based on their historical operation records, which include marked important messages, ignored messages, and the frequency of quick message replies. The message types include work messages, social messages, and notification messages; the importance levels include four levels: extremely high, high, medium, and low; the urgency levels include four levels: immediate, short-term, routine, and non-urgent. The classification results include categories such as urgent and important, spam, work to-do, social chat, and notifications.

[0008] Preferably, the management strategy unit has intelligent management strategies and corresponding to different classification results; the execution unit is used to call the intelligent management strategies in the management strategy unit to perform corresponding intelligent management operations on different messages; the visualization unit is used to generate a graphical operation interface; the interaction unit is used to respond to the user's touch operation, voice command and gesture operation, and transmit the user's command to the message management module to adjust the intelligent management strategy and execute custom management operations. The graphical user interface includes a message category display area, a message details preview area, and a management operation area. The message category display area is used to display message lists of different categories. The message details preview area is used to display the complete content of the message, sender information, and timestamp when the message list is clicked. The management operation area is used to provide quick operations.

[0009] Preferably, the protocol conversion unit is used to convert the internal communication protocols of each module into a communication protocol adapted to the 5G network, wherein the internal communication protocol is based on... The application layer protocol, the 5G network communication protocol includes... , as well as ; The network optimization unit allocates dedicated slice resources for message transmission based on 5G network network slicing technology, ensuring that the transmission latency of messages is less than or equal to [a certain value] in different network environments. Packet loss rate less than or equal to Simultaneously, when network congestion occurs, priority is given to ensuring data transmission between the message management module and the management server, as well as the reception of critical messages by the message receiving module.

[0010] Preferably, the time difference between the message sending time and the current time is expressed as: ;in, This indicates the time difference between the message's sending time and the current time. Indicates the current time. Indicates the time the message was sent; The specific steps of performing natural language processing on the message text content to extract key semantic information are as follows: The message text is standardized, including removing punctuation and stop words, then performing word segmentation and tagging parts of speech. use Extract keywords and obtain their weights; the weights are expressed by the formula: ;in, Indicates the first The weight of each word Indicates the first The word frequency of each word Indicates the first Inverse document frequency of each word; ;in, Indicates the first The number of times each word appears in the current message. Indicates the total number of words in the message; ;in, This represents the total number of documents in the corpus. Indicates containing the first The number of documents per word; Introduce a domain dictionary and perform semantic mapping with any of the BERT models.

[0011] Preferably, the intelligent analysis model mainly includes an input layer, a hidden layer, a loss function, and an output layer; The loss function selected is the cross-entropy loss function, which minimizes the difference between the predicted value and the true value; The input layer is used to input feature parameters, the hidden layer contains two layers, and the output layer is used to output results; Using a multilayer perceptron An intelligent analysis model is constructed by combining attention mechanisms to output the message type label of the message. Importance level and the degree of urgency The specific process is as follows: The feature parameters are converted into vectors of uniform dimension and then concatenated to obtain the concatenated vector. ; A multi-head self-attention mechanism is used to obtain the correlation weights between features; Weighted features The input is a multilayer perceptron, the hidden layers perform calculations layer by layer, and then the output is output through the output layer.

[0012] Preferably, the step of using a multi-head self-attention mechanism to obtain the correlation weights between features specifically involves: The query vector, key vector, and value vector are obtained through linear transformation; the formula is as follows: ; ; ;in, , as well as These are the corresponding trainable weight matrices; The attention score is calculated using the following formula: ;in, This represents the scaling factor, used to prevent gradient vanishing; Represents the transpose of a matrix; Perform multi-head attention concatenation; concatenate the multi-head outputs and obtain weighted features through linear transformation. ; The hidden layer is calculated layer by layer as follows: The formula for calculating the first hidden layer is as follows: ;in, This represents the weights of the first hidden layer. Indicates the bias of the first hidden layer; This represents the output of the first hidden layer; The formula for calculating the second hidden layer is as follows: ;in, This indicates the weights of the second hidden layer. Indicates the bias of the second hidden layer; This represents the output of the second hidden layer; The output layer outputs probability distributions for message type, importance, and urgency, and takes the message type, importance, and urgency corresponding to the maximum probability.

[0013] Preferably, the step of dividing messages according to preset classification rules specifically involves: If importance level And the level of urgency Then the messages will be categorized as urgent and important. If importance level If the sender is a marketing account, the message will be classified as spam. If message type tag And the level of importance and Then the messages will be categorized as work to be done; If message type tag And the level of importance And the level of urgency Then the messages will be categorized as social chat. If message type tag And the level of importance and Then the message will be classified as a notification.

[0014] The technical effects and advantages of this invention are as follows: This invention, by incorporating a message analysis module and a message management module, facilitates the accurate determination of message type, importance, and urgency through multi-dimensional feature extraction combined with information such as message source, content, time, and user behavior. It combines four types of features and employs a multilayer perceptron. By combining attention mechanisms to build an intelligent analysis model, the accuracy of message classification is effectively improved. An automated management strategy library is also built to execute personalized management operations based on the classification results, reducing user operation costs and effectively improving message management efficiency. At the same time, a 5G network interface module is introduced to effectively ensure efficient communication between each module and the 5G network, making full use of the characteristics of the 5G network to improve the stability and immediacy of message transmission. Attached Figure Description

[0015] Figure 1 This is a structural diagram of the 5G-based intelligent message management system of the present invention. Detailed Implementation

[0016] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings. In addition, the forms of the various structures described in the following embodiments are merely illustrative. The 5G-based intelligent message management system involved in the present invention is not limited to the structures described in the following embodiments. All other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0017] like Figure 1 As shown, the present invention provides a 5G-based intelligent message management system, including a message receiving module, a message analysis module, a message management module, a user interface module, and a 5G network interface module; The message receiving module is used to receive messages sent and received by users through the 5G network and transmit them to the message analysis module; the messages include, but are not limited to, SMS, email and social media messages; the message receiving module includes a 5G communication unit and a multi-source adaptation unit. The message analysis module is used to receive data from the message receiving module, perform intelligent analysis on the received messages, identify the message type, importance, and urgency of the messages, classify the messages according to the analysis results, and transmit the classification results to the message management module; the message analysis module includes a feature extraction unit, an analysis model unit, and a classification decision unit; The message management module is used to receive the classification results of the message analysis module and intelligently manage the user's messages. The intelligent management includes, but is not limited to, automatically archiving important messages, reminding users to reply to urgent messages, and automatically deleting spam messages. The message management module includes a management strategy unit and an execution unit. The user interface module is used to display the operation interface of the message management module, through which users can view and manage messages; the user interface module includes a visualization unit and an interaction unit; The 5G network interface module is used to enable communication between each module and the 5G network, and is connected to the message receiving module, message analysis module, message management module and user interface module respectively; the 5G network interface module includes a protocol conversion unit and a network optimization unit.

[0018] In this embodiment, it should be specifically noted that the 5G communication unit is used to establish a wireless connection with the 5G base station, supporting millimeter-wave frequency bands and... Frequency band signal transmission and reception; The multi-source adaptation unit is used to connect to different types of message sources, including but not limited to native mobile terminal applications, third-party social applications, and enterprise-level communication platforms, in order to receive and perform preliminary parsing of SMS, email, and social media messages.

[0019] In this embodiment, it should be specifically noted that the feature extraction unit is used to extract feature parameters of the message, and the feature parameters include message source features. Content keyword characteristics Time characteristics and user behavior characteristics The message source characteristics Identification information indicating the message sender, including but not limited to contact ID, application account, and IP address; the content keyword features. By performing natural language processing on the message text content, key semantic information is extracted; the time features... The time difference between the message sending time and the current time; the user behavior characteristics This indicates the user's interaction preference for a certain type of message, determined based on their historical operation records. These historical operation records include, but are not limited to, marked important messages, ignored messages, and the frequency of quick message replies. The analysis model unit uses a multilayer perceptron based on the feature parameters. An intelligent analysis model is constructed by combining attention mechanisms to output the message type label of the message. Importance level and the degree of urgency The message types include, but are not limited to, work messages, social messages, and notification messages; the importance levels include four levels: extremely high, high, medium, and low; the urgency levels include four levels: immediate, short-term, routine, and non-urgent. The classification decision unit is based on the message type labels output by the analysis model unit. Importance level and the degree of urgency The messages are divided according to preset classification rules to obtain the message classification results; the classification results include urgent and important messages, spam messages, work to-do messages, social chat messages, and notifications.

[0020] In this embodiment, it should be specifically noted that the management strategy unit has intelligent management strategies and corresponds to different classification results, specifically: If the classification result is "urgent and important", a strong reminder window will pop up and continue for the preset duration. It displays the message title and key content, and can also trigger phone vibration and top status bar flashing, and mark the notification as a high priority notification. If the classification result is spam, then the system will be invoked. Delete a message and store the message ID, sender, and deletion time in the local database. With user authorization, the sender can be temporarily blocked for 24 hours. If the category result is "Work To-Do", the message will be automatically archived into the user's preset work to-do file, and a to-do item will be created. The trigger time for the reminder of the to-do item will be... ;in, Indicates the current time. Indicates the delay duration. ,in, This indicates the historical average time it takes for a user to process similar messages. This represents the minimum preset delay time of the system; in this embodiment, it is selected as... ; If the classification result is social chat, the message will be automatically archived to the user's preset social chat file and grouped according to the conversation partner. At the same time, the message content will be displayed in the message list and a preset quick reply template will be provided. If the classification result is a notification message, the message will be stored according to the notification type, and key information will be automatically identified and highlighted. The key information includes, but is not limited to, the deadline and operation link; a reminder can also be given before the deadline.

[0021] The execution unit is used to invoke the intelligent management strategy in the management strategy unit to perform corresponding intelligent management operations on different messages.

[0022] In this embodiment, it should be specifically noted that the visualization unit is used to generate a graphical user interface, which includes a message category display area, a message details preview area, and a management operation area. The message category display area is used to display message lists of different categories, the message details preview area is used to display the complete content of the message, sender information, and timestamp when the message list is clicked, and the management operation area is used to provide quick operations. The interaction unit is used to respond to the user's touch operation, voice command and gesture operation, and transmit the user's command to the message management module to adjust the intelligent management strategy and execute customized management operations.

[0023] In this embodiment, it should be specifically noted that the protocol conversion unit is used to convert the internal communication protocols of each module into a communication protocol adapted to the 5G network. The internal communication protocol is based on... The application layer protocol, the 5G network communication protocol includes... , as well as ; The network optimization unit allocates dedicated slice resources for message transmission based on 5G network network slicing technology, ensuring that the transmission latency of messages is less than or equal to [a certain value] in different network environments. Packet loss rate less than or equal to Meanwhile, when network congestion occurs, priority is given to ensuring the transmission of policy update data between the message management module and the management server, as well as the reception of critical messages by the message receiving module.

[0024] In this embodiment, it should be specifically noted that the time difference between the message sending time and the current time is expressed as follows: ;in, This indicates the time difference between the message's sending time and the current time. Indicates the current time. Indicates the time the message was sent; The specific steps of performing natural language processing on the message text content to extract key semantic information are as follows: The message text is standardized by removing punctuation and stop words, then segmented into words and labeled with parts of speech. A bidirectional longest matching algorithm can be used to segment the text into word sequences for word segmentation, and a word tagger can be used to mark the parts of speech and filter out nouns, gerunds and other content words. use Extract keywords and obtain their weights; the weights are expressed by the formula: ;in, Indicates the first The weight of each word Indicates the first The word frequency of each word Indicates the first Inverse document frequency of each word; ;in, Indicates the first The number of times each word appears in the current message. Indicates the total number of words in the message; ;in, This represents the total number of documents in the corpus. Indicates containing the first The number of documents containing a word; the higher the word's weight, the more important the word. Introduce domain dictionaries or BERT models for semantic mapping to form more standardized terminology.

[0025] In this embodiment, it should be specifically noted that the intelligent analysis model mainly includes an input layer, a hidden layer, a loss function, and an output layer; The loss function selected is the cross-entropy loss function, which minimizes the difference between the predicted value and the true value; The input layer is used to input feature parameters, the hidden layer contains two layers, and the output layer is used to output results; Using a multilayer perceptron An intelligent analysis model is constructed by combining attention mechanisms to output the message type label of the message. Importance level and the degree of urgency The specific process is as follows: The feature parameters are converted into vectors of uniform dimension and then concatenated to obtain the concatenated vector. ; A multi-head self-attention mechanism is used to obtain the correlation weights between features; Weighted features The input is a multilayer perceptron, the hidden layers perform calculations layer by layer, and then the output is output through the output layer.

[0026] In this embodiment, it should be specifically explained that the multi-head self-attention mechanism for obtaining the correlation weights between features is specifically as follows: The query vector, key vector, and value vector are obtained through linear transformation; the formula is as follows: ; ; ;in, , as well as These are the corresponding trainable weight matrices; The attention score is calculated using the following formula: ;in, This represents the scaling factor, used to prevent gradient vanishing; Represents the transpose of a matrix; Perform multi-head attention concatenation; concatenate the multi-head outputs and obtain weighted features through linear transformation. ; The hidden layer is calculated layer by layer as follows: The formula for calculating the first hidden layer is as follows: ;in, This represents the weights of the first hidden layer. Indicates the bias of the first hidden layer; This represents the output of the first hidden layer; The formula for calculating the second hidden layer is as follows: ;in, This indicates the weights of the second hidden layer. Indicates the bias of the second hidden layer; This represents the output of the second hidden layer; The output layer outputs probability distributions for message type, importance, and urgency, and takes the message type, importance, and urgency corresponding to the maximum probability.

[0027] In this embodiment, it should be specifically explained that the process of dividing messages according to preset classification rules specifically involves: If importance level And the level of urgency Then the messages will be categorized as urgent and important. If importance level If the sender is a marketing account, the message will be classified as spam. If message type tag And the level of importance and Then the messages will be categorized as work to be done; If message type tag And the level of importance And the level of urgency Then the messages will be categorized as social chat. If message type tag And the level of importance and Then the message will be classified as a notification.

[0028] In conclusion, the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

[0029] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A 5G-based intelligent message management system, characterized in that: It includes a message receiving module, a message analysis module, a message management module, a user interface module, and a 5G network interface module; The message receiving module is used to receive messages sent and received by users through the 5G network and transmit them to the message analysis module; the message receiving module includes a 5G communication unit and a multi-source adaptation unit; The message analysis module is used to receive data from the message receiving module, perform intelligent analysis on the received messages, identify the message type, importance and urgency of the messages, classify the messages according to the analysis results, and transmit the classification results to the message management module. The message analysis module includes a feature extraction unit, an analysis model unit, and a classification decision unit; The message management module is used to receive the classification results of the message analysis module and to intelligently manage the user's messages. The message management module includes a management strategy unit and an execution unit. The user interface module is used to display the operation interface of the message management module, through which users can view and manage messages; the user interface module includes a visualization unit and an interaction unit; The 5G network interface module is used to enable communication between each module and the 5G network, and is connected to the message receiving module, message analysis module, message management module and user interface module respectively; the 5G network interface module includes a protocol conversion unit and a network optimization unit.

2. The 5G-based intelligent message management system according to claim 1, characterized in that: The 5G communication unit is used to establish a wireless connection with a 5G base station; the multi-source adaptation unit is used to interface with different types of message sources; the feature extraction unit is used to extract feature parameters of the message; and the analysis model unit uses a multilayer perceptron based on the feature parameters. An intelligent analysis model is constructed by combining attention mechanisms to output the message type label of the message. Importance level and the degree of urgency The classification decision unit uses the message type labels output by the analysis model unit. Importance level and the degree of urgency The messages are divided according to the preset classification rules to obtain the message classification results.

3. The 5G-based intelligent message management system according to claim 2, characterized in that: The feature parameters include message source features. Content keyword characteristics Time characteristics and user behavior characteristics The message source characteristics Identification information indicating the message sender, including contact ID, application account, and IP address; the content keyword features. By performing natural language processing on the message text content, key semantic information is extracted; the time features... The time difference between the message sending time and the current time; the user behavior characteristics This indicates the user's interaction preference for a certain type of message, determined based on their historical operation records, which include marked important messages, ignored messages, and the frequency of quick message replies. The message types include work messages, social messages, and notification messages; the importance levels include four levels: very high, high, medium, and low. The urgency levels include four levels: immediate, short-term, routine, and non-urgent. The classification results include categories such as urgent and important, spam, work to-do, social chat, and notifications.

4. The 5G-based intelligent message management system according to claim 3, characterized in that: The management strategy unit has intelligent management strategies and corresponding to different classification results. The execution unit is used to call the intelligent management strategies in the management strategy unit to perform corresponding intelligent management operations on different messages. The visualization unit is used to generate a graphical operation interface. The interaction unit is used to respond to the user's touch operation, voice command and gesture operation, and transmit the user's command to the message management module to adjust the intelligent management strategy and execute custom management operations. The graphical user interface includes a message category display area, a message details preview area, and a management operation area. The message category display area is used to display message lists of different categories. The message details preview area is used to display the complete content of the message, sender information, and timestamp when the message list is clicked. The management operation area is used to provide quick operations.

5. The 5G-based intelligent message management system according to claim 4, characterized in that: The protocol conversion unit is used to convert the internal communication protocols of each module into a communication protocol adapted to 5G networks. The internal communication protocol is based on... The application layer protocol, the 5G network communication protocol includes... , as well as ; The network optimization unit allocates dedicated slice resources for message transmission based on 5G network network slicing technology, ensuring that the transmission latency of messages is less than or equal to [a certain value] in different network environments. Packet loss rate less than or equal to Simultaneously, when network congestion occurs, priority is given to ensuring data transmission between the message management module and the management server, as well as the reception of critical messages by the message receiving module.

6. The 5G-based intelligent message management system according to claim 5, characterized in that: The time difference between the message sending time and the current time is expressed as: ;in, This indicates the time difference between the message's sending time and the current time. Indicates the current time. Indicates the time the message was sent; The specific steps of performing natural language processing on the message text content to extract key semantic information are as follows: The message text is standardized, including removing punctuation and stop words, then performing word segmentation and tagging parts of speech. use Extract keywords and obtain their weights; the weights are expressed by the formula: ;in, Indicates the first The weight of each word Indicates the first The word frequency of each word Indicates the first Inverse document frequency of each word; ;in, Indicates the first The number of times each word appears in the current message. Indicates the total number of words in the message; ;in, This represents the total number of documents in the corpus. Indicates containing the first The number of documents per word; Introduce a domain dictionary and perform semantic mapping with any of the BERT models.

7. A 5G-based intelligent message management system according to claim 6, characterized in that: The intelligent analysis model mainly includes an input layer, a hidden layer, a loss function, and an output layer; The loss function selected is the cross-entropy loss function, which minimizes the difference between the predicted value and the true value; The input layer is used to input feature parameters, the hidden layer contains two layers, and the output layer is used to output results; Using a multilayer perceptron An intelligent analysis model is constructed by combining attention mechanisms to output the message type label of the message. Importance level and the degree of urgency The specific process is as follows: The feature parameters are converted into vectors of uniform dimension and then concatenated to obtain the concatenated vector. ; A multi-head self-attention mechanism is used to obtain the correlation weights between features; Weighted features The input is a multilayer perceptron, the hidden layers perform calculations layer by layer, and then the output is output through the output layer.

8. A 5G-based intelligent message management system according to claim 7, characterized in that: The specific steps for obtaining the correlation weights between features using a multi-head self-attention mechanism are as follows: The query vector, key vector, and value vector are obtained through linear transformation; the formula is as follows: ; ; ;in, , as well as These are the corresponding trainable weight matrices; The attention score is calculated using the following formula: ;in, This represents the scaling factor, used to prevent gradient vanishing; Represents the transpose of a matrix; Perform multi-head attention concatenation; concatenate the multi-head outputs and obtain weighted features through linear transformation. ; The hidden layer is calculated layer by layer as follows: The formula for calculating the first hidden layer is as follows: ;in, This represents the weights of the first hidden layer. Indicates the bias of the first hidden layer; This represents the output of the first hidden layer; The formula for calculating the second hidden layer is as follows: ;in, This indicates the weights of the second hidden layer. Indicates the bias of the second hidden layer; This represents the output of the second hidden layer; The output layer outputs probability distributions for message type, importance, and urgency, and takes the message type, importance, and urgency corresponding to the maximum probability.

9. A 5G-based intelligent message management system according to claim 8, characterized in that: The specific steps of classifying messages according to preset classification rules are as follows: If importance level And the level of urgency Then the messages will be categorized as urgent and important. If importance level If the sender is a marketing account, the message will be classified as spam. If message type tag And the level of importance and Then the messages will be categorized as work to be done; If message type tag And the level of importance And the level of urgency Then the messages will be categorized as social chat. If message type tag And the level of importance and Then the message will be classified as a notification.

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