Short message processing method and short message processing terminal

Abstract

The invention discloses a short message processing method and a short message processing terminal, and belongs to the technical field of short message processing. The method comprises the following steps: acquiring received short message data, and preprocessing the received short message data to obtain preprocessed short message data; based on the preprocessed short message data, extracting short message text features to obtain received short message text features; the scene where the user is located is judged in real time through mobile terminal sensor data and user schedule information; linkage of other application programs is carried out based on the judged result of the scene where the user is located; the method comprises the following steps: obtaining a short message text emotion index through a received short message text feature, and triggering a linkage operation with other application programs based on the short message text emotion index. According to the method, the short message receiving and processing mode is intelligently adjusted through dynamic scene perception and cross-application cooperation, and then the short message processing strategy is intelligently adapted according to the scene where the user is located, so that the problem of lack of dynamic adaption to the real-time scene of the user at present is effectively solved.

Description

Technical Field

[0001] The present invention relates to the technical field of short message processing, and in particular to a short message processing method and a short message processing terminal. Background Art

[0002] With the rapid development of mobile communication technology, SMS, as a basic means of communication, continues to play an irreplaceable role in daily life, commercial services, and emergency notifications. However, the types of SMS messages users receive are becoming increasingly diverse (such as marketing advertisements, verification codes, social messages, emergency notifications, etc.), and traditional SMS processing methods are no longer able to meet the needs of personalization, scenario-based, and intelligent processing.

[0003] Existing SMS management systems typically prioritize and block spam messages through keyword filtering, rule engines, or simple machine learning-based classification. For example, some systems use pre-set rule libraries to label messages containing specific keywords (such as "verification code" and "promotion") or use naive Bayesian algorithms to identify spam messages.

[0004] However, in the process of implementing the technical solutions of the invention in the embodiments of the present application, the present application found that the above technology has at least the following technical problems: In the existing technology, the existing system is unable to adjust the SMS processing method based on the user's current environment, resulting in the user being subject to irrelevant interference or missing key information in different scenarios, and there is a problem of lack of dynamic adaptation to the user's real-time scenario. Summary of the Invention

[0005] The embodiments of the present application solve the problems of user interference or information omission caused by the lack of dynamic scene adaptation capability in the prior art by providing a text message processing method and a text message processing terminal, and achieve the technical effect of intelligently adjusting the text message reception and processing method according to the user's scene and text message emotion index.

[0006] The embodiment of the present application provides a method for processing a text message, comprising the following steps: obtaining received text message data, preprocessing the received text message data, and obtaining preprocessed text message data; Extracting SMS text features based on the pre-processed SMS data to obtain received SMS text features; Determine the user's current scene in real time through mobile terminal sensor data and user schedule information. The mobile terminal sensors include acceleration sensors, biometric sensors, and light sensors. Based on the determined user scenario, other applications are linked; The sentiment index of the SMS text is obtained through the features of the received SMS text, and based on the sentiment index of the SMS text, linkage operations with other applications are triggered.

[0007] Furthermore, based on the pre-processed SMS data, SMS text features are extracted to obtain received SMS text features, including the following steps: A word segmentation tool based on statistical models that performs word segmentation processing on SMS text features to obtain individual words; Use machine learning to perform part-of-speech tagging on each word to obtain the part of speech of each word; Through the dictionary data structure, traverse each word, record the number of times each word appears, and obtain the word frequency statistics.

[0008] Furthermore, the user's scene is determined in real time through mobile terminal sensor data, user schedule information, and application status information, including the following steps: The mobile terminal sensor determines whether the user is in a driving scene. If the user is in a driving scene, the received SMS data is broadcasted through voice. If the user is not in a driving scene, the SMS data is received normally through the mobile terminal; The mobile terminal sensor determines whether the user is in a resting state. If the user is in a resting state, the mobile terminal receives SMS data in silence. If the user is not in a resting state, the mobile terminal receives SMS data normally. By obtaining the user schedule information of the mobile terminal, it is determined whether the user is in a working scene. If the user is in a working scene, the SMS data is received silently through the mobile terminal. If the user is not in a working scene, the SMS data is received normally through the mobile terminal.

[0009] Furthermore, based on the determined user scenario, other applications are linked, including the following steps: When the user is not driving, resting, or working, the mobile terminal will not be linked to other applications. When the user is in a driving scene, a rest scene, a rest scene, or a work scene, the mobile terminal will be linked to other applications.

[0010] Furthermore, obtaining the sentiment index of the received text message based on the text features of the received text message includes the following steps: Based on the received SMS text features, obtain the SMS sender's influence index, sentiment index, and urgency index; Obtain the weights of the keyword importance index, sentiment tendency index, and urgency index to the text sentiment index of the SMS through the information stored in the database; Get the text sentiment index of the SMS text using the SMS sentiment index formula; The formula for the text sentiment index is: ; Where P is the sentiment index of the text message, K(S) is the influence index of the text message sender, S(S) is the sentiment tendency index, and U(S) is the urgency index. is the weight factor of K(S) to P, is the weight factor of S (S) on P, is the weight factor of U(S) to P.

[0011] Furthermore, obtaining the SMS sender influence index includes the following steps: Get the SMS sender's SMS sending time, the number of URL links in the SMS content, and the average character brightness in the SMS content; Based on the information stored in the database, a nonlinear adjustment coefficient of a maximum allowable SMS sending time and an SMS sender influence index is obtained; Obtain the SMS sender influence index through the SMS sender influence index formula; The SMS sender influence index formula is: ; Where, It takes time to send SMS. The maximum allowed SMS sending time. The number of URL links in the SMS content. is the average brightness of characters in the text message content, is the nonlinear adjustment coefficient of the SMS sender influence index, and e is a natural constant.

[0012] Furthermore, the steps for obtaining the sentiment tendency index are as follows: Obtain the time interval between consecutive SMS messages of the same type received by the user's mobile terminal, the activity period of the user's mobile terminal screen, the screen brightness of the user's mobile terminal, and the sound pressure level of the environment in which the user's mobile terminal is located; Based on the information stored in the database, a nonlinear adjustment coefficient of the maximum screen brightness and the emotional tendency index of the user's mobile terminal is obtained; Obtain the sentiment tendency index through the sentiment tendency index formula; The sentiment index formula is: ; Where, The time interval for the user's mobile terminal to continuously receive the same type of text messages. The activity cycle of the user's mobile terminal screen, The screen brightness of the user's mobile terminal, is the ambient sound pressure level of the user's mobile terminal environment, The maximum screen brightness of the user's mobile terminal, is the nonlinear adjustment coefficient of the sentiment tendency index, and e is a natural constant.

[0013] Furthermore, the steps for obtaining the urgency index are: Obtain the current remaining battery power of the user's mobile terminal, the number of historical repetitions of the same type of text messages on the user's mobile terminal, the total number of historical text messages on the user's mobile terminal, the sender's sending frequency, the sender's geographic location vector, and the recipient's geographic location vector; Based on the information stored in the database, the critical power threshold of the user's mobile terminal, the nonlinear adjustment coefficient of the urgency index, and the maximum sending frequency of the sender are obtained; The urgency index is obtained through the urgency index formula; The urgency index is: ; Where, The current remaining power of the user's mobile terminal, The number of times the same type of SMS messages are repeated in the user's mobile terminal. The total number of historical SMS messages on the user's mobile terminal. is the sending frequency of the sender, is the maximum sending frequency of the sender, is the geographic location vector of the sender, is the geographic location vector of the recipient, The critical power threshold of the user's mobile terminal, is the nonlinear adjustment coefficient of the urgency index.

[0014] Furthermore, based on the sentiment index of the SMS text, triggering linkage operations with other applications includes the following steps: Based on the obtained SMS text sentiment index, if the SMS text sentiment index is less than the sentiment index threshold set in the database, no linkage operation is performed; If the sentiment index of the text message is not less than the sentiment index threshold set in the database, the corresponding linkage operation will be performed when the SMS sender influence index, sentiment index and urgency index meet the following conditions. If the following conditions are not met, the linkage operation will not be performed: When the sentiment index is greater than the preset positive sentiment threshold and the urgency index is lower than the preset emergency threshold, a linkage operation with a social application is triggered, and a reply template is automatically generated and pushed to the SMS interface; When the urgency index is greater than the preset emergency threshold and the SMS sender's influence index exceeds the preset trust threshold, a linkage operation with a security application is triggered to encrypt and back up the SMS content to the cloud and activate the real-time location sharing function; When the sentiment index is lower than the preset negative sentiment threshold and the sender influence index is lower than the preset interception threshold, a linkage operation with the filtering application is triggered to mark the SMS as spam and synchronize it to the user's blocking list database; When the urgency index and the sentiment index exceed the preset composite threshold at the same time, a multi-application collaborative operation is triggered: the voice assistant is called to broadcast the text message content, and an urgent to-do reminder is inserted into the calendar management application.

[0015] The embodiment of the present application provides a short message processing terminal for implementing the short message processing method, characterized by comprising: a short message receiving module, a text extraction module, a scene determination module, and a program linkage module; The SMS receiving module is used to obtain received SMS data, pre-process the received SMS data, and obtain pre-processed SMS data; The text extraction module is used to extract SMS text features based on the pre-processed SMS data to obtain received SMS text features; The scene determination module is used to determine the scene the user is in in real time based on mobile terminal sensor data and user schedule information. The mobile terminal sensors include acceleration sensors, biometric sensors, and light sensors. The program linkage module is used to link other applications based on the determined user scenario; The sentiment index of the SMS text is obtained through the features of the received SMS text, and based on the sentiment index of the SMS text, linkage operations with other applications are triggered.

[0016] One or more technical solutions provided in the embodiments of this application have at least the following technical effects or advantages: 1. Through dynamic scene perception and cross-application collaboration, the SMS reception and processing methods are intelligently adjusted, thereby achieving the technical effect of intelligently adapting the SMS processing strategy according to the user's scene and SMS sentiment index, effectively solving the problems of user interference or information omission caused by the lack of dynamic scene adaptation capabilities in existing technologies.

[0017] 2. By preprocessing SMS data and extracting multi-dimensional text features, we can accurately identify SMS content and emotional tendencies, thereby accurately calculating the SMS sentiment index and improving the intelligent level of SMS processing.

[0018] 3. By determining the user's current situation in real time and combining the SMS sentiment index to trigger application linkage, personalized and intelligent SMS processing services can be achieved, thereby improving the user experience, reducing unnecessary interference, and ensuring that important information is not missed. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 A flowchart of a method for processing text messages provided in an embodiment of the present application; Figure 2 This is a structural diagram of a short message processing terminal provided in an embodiment of the present application. DETAILED DESCRIPTION

[0020] The embodiments of the present application solve the problems of user interference or information omission caused by the lack of dynamic scene adaptation capability in the prior art by providing a text message processing method and a text message processing terminal. Through dynamic scene perception and cross-application collaboration, the text message reception and processing methods are intelligently adjusted, thereby achieving the technical effect of intelligently adapting the text message processing strategy according to the user's scene and the text message emotion index.

[0021] In order to better understand the above technical solution, the above technical solution will be described in detail below with reference to the accompanying drawings and specific implementation methods.

[0022] like Figure 1 , which is a flow chart of a method for processing text messages provided in an embodiment of the present application, and which is applied to a text message processing terminal, the method comprises the following steps: obtaining received text message data, preprocessing the received text message data, and obtaining preprocessed text message data; Extracting SMS text features based on the pre-processed SMS data to obtain received SMS text features; Determine the user's current scene in real time through mobile terminal sensor data and user schedule information. The mobile terminal sensors include acceleration sensors, biometric sensors, and light sensors. Based on the determined user scenario, other applications are linked; The sentiment index of the SMS text is obtained through the features of the received SMS text, and based on the sentiment index of the SMS text, linkage operations with other applications are triggered.

[0023] In this embodiment, intelligent SMS processing is achieved through preprocessing, feature extraction, contextual awareness, and sentiment analysis. Preprocessing ensures data quality, feature extraction provides the foundation for subsequent analysis, contextual awareness adjusts SMS reception based on user status, and sentiment analysis triggers application interaction. This multi-dimensional processing approach, combined with natural language processing (NLP) and machine learning algorithms, accurately identifies SMS content, improves user experience, and ensures timely processing of important information.

[0024] Furthermore, based on the pre-processed SMS data, SMS text features are extracted to obtain received SMS text features, including the following steps: A word segmentation tool based on statistical models that performs word segmentation processing on SMS text features to obtain individual words; Use machine learning to perform part-of-speech tagging on each word to obtain the part of speech of each word; Through the dictionary data structure, traverse each word, record the number of times each word appears, and obtain the word frequency statistics.

[0025] In this example, when extracting SMS text features, a statistical model word segmentation tool combined with machine learning is used for part-of-speech tagging, and word frequencies are recorded using a dictionary. This method efficiently processes SMS text and provides accurate data for sentiment analysis and urgency assessment. Word segmentation and part-of-speech tagging are key steps in natural language processing and directly impact the accuracy of text semantic understanding.

[0026] Furthermore, the user's scene is determined in real time through mobile terminal sensor data, user schedule information, and application status information, including the following steps: The mobile terminal sensor determines whether the user is in a driving scene. If the user is in a driving scene, the received SMS data is broadcasted through voice. If the user is not in a driving scene, the SMS data is received normally through the mobile terminal; The mobile terminal sensor determines whether the user is in a resting state. If the user is in a resting state, the mobile terminal receives SMS data in silence. If the user is not in a resting state, the mobile terminal receives SMS data normally. By obtaining the user schedule information of the mobile terminal, it is determined whether the user is in a working scene. If the user is in a working scene, the SMS data is received silently through the mobile terminal. If the user is not in a working scene, the SMS data is received normally through the mobile terminal.

[0027] In this embodiment, mobile sensor data and user schedule information are used to determine the user's context in real time, enabling personalized SMS processing. Automatically switching to voice notifications during driving, silent reception during rest, and silent notifications during work. This approach provides services tailored to the user's real-time state, enhancing the user experience.

[0028] Furthermore, based on the determined user scenario, other applications are linked, including the following steps: When the user is not driving, resting, or working, the mobile terminal will not be linked to other applications. When the user is in a driving scene, a rest scene, a rest scene, or a work scene, the mobile terminal will be linked to other applications.

[0029] In this embodiment, applications are linked based on user scenario results to deliver intelligent services. Driving scenarios can initiate navigation, rest scenarios can adjust music playback, and work scenarios can highlight important information. This linkage mechanism combines SMS processing with other application functions to provide comprehensive and convenient services.

[0030] Furthermore, obtaining the sentiment index of the received text message based on the text features of the received text message includes the following steps: Based on the received SMS text features, obtain the SMS sender's influence index, sentiment index, and urgency index; Obtain the weights of the keyword importance index, sentiment tendency index, and urgency index to the text sentiment index of the SMS through the information stored in the database; Get the text sentiment index of the SMS text using the SMS sentiment index formula; The formula for the text sentiment index is: ; Where P is the sentiment index of the text message, K(S) is the influence index of the text message sender, S(S) is the sentiment tendency index, and U(S) is the urgency index. is the weight factor of K(S) to P, is the weight factor of S (S) on P, is the weight factor of U(S) to P.

[0031] In this embodiment, a sentiment index is calculated based on SMS text features to accurately assess the importance and urgency of SMS messages. The sentiment index combines the sender's influence, emotional inclination, and urgency to provide users with precise analysis, helping them quickly identify important information and avoid missing key content.

[0032] Furthermore, obtaining the SMS sender influence index includes the following steps: Get the SMS sender's SMS sending time, the number of URL links in the SMS content, and the average character brightness in the SMS content; Based on the information stored in the database, the maximum allowed SMS sending time and the nonlinear adjustment coefficient of the SMS sender influence index are obtained; Obtain the SMS sender influence index through the SMS sender influence index formula; The SMS sender influence index formula is: ; Where, It takes time to send SMS. The maximum allowed SMS sending time. The number of URL links in the SMS content. is the average brightness of characters in the text message content, is the nonlinear adjustment coefficient of the SMS sender influence index, and e is a natural constant.

[0033] In this example, the influence index of the text message sender is obtained to evaluate the sender's behavioral characteristics and the characteristics of the text message content. By combining parameters such as sending time, number of links, and character brightness with a nonlinear adjustment coefficient, the sender's influence is accurately calculated. This allows the importance of the text message to be assessed from the sender's perspective, providing a reference for calculating the sentiment index.

[0034] Furthermore, the steps for obtaining the sentiment tendency index are as follows: Obtain the time interval between consecutive SMS messages of the same type received by the user's mobile terminal, the activity period of the user's mobile terminal screen, the screen brightness of the user's mobile terminal, and the ambient sound pressure level of the environment in which the user's mobile terminal is located; Based on the information stored in the database, the maximum screen brightness of the user's mobile terminal and the nonlinear adjustment coefficient of the emotional tendency index are obtained; Obtain the sentiment tendency index through the sentiment tendency index formula; The sentiment index formula is: ; Where, The time interval for the user's mobile terminal to continuously receive the same type of text messages. The activity cycle of the user's mobile terminal screen, The screen brightness of the user's mobile terminal, is the ambient sound pressure level of the user's mobile terminal environment, The maximum screen brightness of the user's mobile terminal, is the nonlinear adjustment coefficient of the sentiment tendency index.

[0035] In this embodiment, the sentiment index is derived by assessing the sentiment of text messages based on user behavior and environmental conditions. By combining parameters such as the reception interval, screen activity period, screen brightness, and ambient sound pressure level with a nonlinear adjustment coefficient, the sentiment index is accurately calculated. This allows users to assess the sentiment of text messages from a user's perspective and provides a reference for calculating the sentiment index.

[0036] Furthermore, the steps for obtaining the urgency index are: Obtain the current remaining battery power of the user's mobile terminal, the number of historical repetitions of the same type of text messages on the user's mobile terminal, the total number of historical text messages on the user's mobile terminal, the sender's sending frequency, the sender's geographic location vector, and the recipient's geographic location vector; Based on the information stored in the database, the critical power threshold of the user's mobile terminal, the nonlinear adjustment coefficient of the urgency index, and the maximum sending frequency of the sender are obtained; The urgency index is obtained through the urgency index formula; The urgency index is: ; Where, The current remaining power of the user's mobile terminal, The number of times the same type of SMS messages are repeated in the user's mobile terminal. The total number of historical SMS messages on the user's mobile terminal. is the sending frequency of the sender, is the maximum sending frequency of the sender, is the geographic location vector of the sender, is the geographic location vector of the recipient, The critical power threshold of the user's mobile terminal, is the nonlinear adjustment coefficient of the urgency index.

[0037] In this embodiment, the urgency of a text message is assessed based on the user's device status and the sender's behavioral characteristics. For example, if the user's current battery life is low and the same type of text message has been sent many times in the past, the system may consider the text message to be more urgent, thereby increasing the urgency index.

[0038] Furthermore, based on the sentiment index of the SMS text, triggering linkage operations with other applications includes the following steps: Based on the obtained SMS text sentiment index, if the SMS text sentiment index is less than the sentiment index threshold set in the database, no linkage operation is performed; If the sentiment index of the text message is not less than the sentiment index threshold set in the database, the corresponding linkage operation will be performed when the SMS sender influence index, sentiment index and urgency index meet the following conditions. If the following conditions are not met, the linkage operation will not be performed: When the sentiment index is greater than the preset positive sentiment threshold and the urgency index is lower than the preset emergency threshold, a linkage operation with a social application is triggered, and a reply template is automatically generated and pushed to the SMS interface; When the urgency index is greater than the preset emergency threshold and the SMS sender's influence index exceeds the preset trust threshold, a linkage operation with a security application is triggered to encrypt and back up the SMS content to the cloud and activate the real-time location sharing function; When the sentiment index is lower than the preset negative sentiment threshold and the sender influence index is lower than the preset interception threshold, a linkage operation with the filtering application is triggered to mark the SMS as spam and synchronize it to the user's blocking list database; When the urgency index and the sentiment index exceed the preset composite threshold at the same time, a multi-application collaborative operation is triggered: the voice assistant is called to broadcast the text message content, and an urgent to-do reminder is inserted into the calendar management application.

[0039] The preset positive emotion threshold, the preset emergency threshold, the preset trust threshold, the preset negative emotion threshold, the preset interception threshold and the preset composite threshold are all obtained from the database.

[0040] In this embodiment, application linkage is triggered based on the SMS sentiment index, enabling intelligent services. When the sentiment index is high, related applications, such as navigation, music, or calendar, are automatically launched, providing personalized services. Application behavior is automatically adjusted based on the SMS content and sentiment, enhancing the user experience.

[0041] like Figure 2 , which is a structural diagram of a text message processing terminal provided in an embodiment of the present application, and is used to implement the text message processing method described above, and is characterized in that it includes: a text message receiving module, a text extraction module, a scene determination module, and a program linkage module; The SMS receiving module is used to obtain received SMS data, pre-process the received SMS data, and obtain pre-processed SMS data; The text extraction module is used to extract SMS text features based on the pre-processed SMS data to obtain received SMS text features; The scene determination module is used to determine the scene the user is in in real time based on mobile terminal sensor data and user schedule information. The mobile terminal sensors include acceleration sensors, biometric sensors, and light sensors. The program linkage module is used to link other applications based on the determined user scenario; The sentiment index of the SMS text is obtained through the features of the received SMS text, and based on the sentiment index of the SMS text, linkage operations with other applications are triggered.

[0042] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Thus, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0043] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowcharts and / or block diagrams, as well as combinations of processes and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowcharts and / or block diagrams. Figure 1a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0044] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0045] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0046] Although the preferred embodiments of the present invention have been described, those skilled in the art may make additional changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0047] Obviously, those skilled in the art may make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if such changes and modifications fall within the scope of the claims and their equivalents, the present invention is intended to include such changes and modifications.

Claims

1. A method for processing short messages, characterized in that: The following steps are involved: Acquire received SMS data, pre-process the received SMS data, and obtain pre-processed SMS data; Extracting SMS text features based on the pre-processed SMS data to obtain received SMS text features; Determine the user's current scene in real time through mobile terminal sensor data and user schedule information. The mobile terminal sensors include acceleration sensors, biometric sensors, and light sensors. Based on the determined user scenario, other applications are linked; The sentiment index of the SMS text is obtained through the features of the received SMS text, and based on the sentiment index of the SMS text, linkage operations with other applications are triggered.

2. A method for processing short messages as claimed in claim 1, characterized in that: Extracting SMS text features based on the preprocessed SMS data to obtain received SMS text features includes the following steps: A word segmentation tool based on statistical models that performs word segmentation processing on SMS text features to obtain individual words; Use machine learning to perform part-of-speech tagging on each word to obtain the part of speech of each word; Through the dictionary data structure, traverse each word, record the number of times each word appears, and obtain the word frequency statistics.

3. A method for processing short messages as claimed in claim 1, characterized in that: Using mobile sensor data, user schedule information, and application status information, the user's current scenario is determined in real time. This includes the following steps: The mobile terminal sensor determines whether the user is in a driving scene. If the user is in a driving scene, the received SMS data is broadcasted through voice. If the user is not in a driving scene, the SMS data is received normally through the mobile terminal; The mobile terminal sensor determines whether the user is in a resting state. If the user is in a resting state, the mobile terminal receives SMS data in silence. If the user is not in a resting state, the mobile terminal receives SMS data normally. By obtaining the user schedule information of the mobile terminal, it is determined whether the user is in a working scene. If the user is in a working scene, the SMS data is received silently through the mobile terminal. If the user is not in a working scene, the SMS data is received normally through the mobile terminal.

4. A method for processing short messages as claimed in claim 1, characterized in that: Based on the determined user scenario, other applications are linked, including the following steps: When the user is not driving, resting, or working, the mobile terminal will not be linked to other applications. When the user is in a driving scene, a rest scene, a rest scene, or a work scene, the mobile terminal will be linked to other applications.

5. A method for processing short messages as claimed in claim 1, characterized in that: Obtaining the sentiment index of a received SMS text using the features of the received SMS text includes the following steps: Based on the received SMS text features, obtain the SMS sender's influence index, sentiment index, and urgency index; Obtain the weights of the keyword importance index, sentiment tendency index, and urgency index to the text sentiment index of the SMS through the information stored in the database; Get the text sentiment index of the SMS text using the SMS sentiment index formula; The formula for the text sentiment index is: ； Where P is the sentiment index of the text message, K(S) is the influence index of the text message sender, S(S) is the sentiment tendency index, and U(S) is the urgency index. is the weight factor of K(S) to P, is the weight factor of S (S) on P, is the weight factor of U(S) to P.

6. A method for processing short messages as claimed in claim 5, characterized in that: Obtaining the SMS sender influence index includes the following steps: Get the SMS sender's SMS sending time, the number of URL links in the SMS content, and the average character brightness in the SMS content; Based on the information stored in the database, a nonlinear adjustment coefficient of a maximum allowable SMS sending time and an SMS sender influence index is obtained; Obtain the SMS sender influence index through the SMS sender influence index formula; The SMS sender influence index formula is: ； Where, It takes time to send SMS. The maximum allowed SMS sending time. The number of URL links in the SMS content. is the average brightness of characters in the text message content, is the nonlinear adjustment coefficient of the SMS sender influence index, and e is a natural constant.

7. A method for processing short messages as claimed in claim 5, characterized in that: The steps to obtain the sentiment tendency index are: Obtain the time interval between consecutive SMS messages of the same type received by the user's mobile terminal, the activity period of the user's mobile terminal screen, the screen brightness of the user's mobile terminal, and the ambient sound pressure level of the environment in which the user's mobile terminal is located; Based on the information stored in the database, a nonlinear adjustment coefficient of the maximum screen brightness and the emotional tendency index of the user's mobile terminal is obtained; Obtain the sentiment tendency index through the sentiment tendency index formula; The sentiment index formula is: ； Where, The time interval for the user's mobile terminal to continuously receive the same type of text messages. The activity cycle of the user's mobile terminal screen, The screen brightness of the user's mobile terminal, is the ambient sound pressure level of the user's mobile terminal environment, The maximum screen brightness of the user's mobile terminal, is the nonlinear adjustment coefficient of the sentiment tendency index, and e is a natural constant.

8. A method for processing short messages as claimed in claim 5, characterized in that: The steps to obtain the urgency index are: Obtain the current remaining battery power of the user's mobile terminal, the number of historical repetitions of the same type of text messages on the user's mobile terminal, the total number of historical text messages on the user's mobile terminal, the sender's sending frequency, the sender's geographic location vector, and the recipient's geographic location vector; Based on the information stored in the database, the critical power threshold of the user's mobile terminal, the nonlinear adjustment coefficient of the urgency index, and the maximum sending frequency of the sender are obtained; The urgency index is obtained through the urgency index formula; The urgency index is: ； Where, The current remaining power of the user's mobile terminal, The number of times the same type of SMS messages are repeated in the user's mobile terminal. The total number of historical SMS messages on the user's mobile terminal. is the sending frequency of the sender, is the maximum sending frequency of the sender, is the geographic location vector of the sender, is the geographic location vector of the recipient, The critical power threshold of the user's mobile terminal, is the nonlinear adjustment coefficient of the urgency index.

9. A method for processing short messages as claimed in claim 1, characterized in that: Triggering linkage operations with other applications based on the sentiment index of SMS texts includes the following steps: Based on the obtained SMS text sentiment index, if the SMS text sentiment index is less than the sentiment index threshold set in the database, no linkage operation is performed; If the sentiment index of the text message is not less than the sentiment index threshold set in the database, the corresponding linkage operation will be performed when the SMS sender influence index, sentiment index and urgency index meet the following conditions. If the following conditions are not met, the linkage operation will not be performed: When the sentiment index is greater than the preset positive sentiment threshold and the urgency index is lower than the preset emergency threshold, a linkage operation with a social application is triggered, and a reply template is automatically generated and pushed to the SMS interface; When the urgency index is greater than the preset emergency threshold and the SMS sender's influence index exceeds the preset trust threshold, a linkage operation with a security application is triggered to encrypt and back up the SMS content to the cloud and activate the real-time location sharing function; When the sentiment index is lower than the preset negative sentiment threshold and the sender influence index is lower than the preset interception threshold, a linkage operation with the filtering application is triggered to mark the SMS as spam and synchronize it to the user's blocking list database; When the urgency index and the sentiment index exceed the preset composite threshold at the same time, a multi-application collaborative operation is triggered: the voice assistant is called to broadcast the text message content, and an urgent to-do reminder is inserted into the calendar management application.

10. A short message processing terminal, used to implement the short message processing method according to any one of claims 1 to 9, characterized in that: include: SMS receiving module, text extraction module, scene determination module, and program linkage module; The SMS receiving module is used to obtain received SMS data, pre-process the received SMS data, and obtain pre-processed SMS data; The text extraction module is used to extract SMS text features based on the pre-processed SMS data to obtain received SMS text features; The scene determination module is used to determine the scene the user is in in real time based on mobile terminal sensor data and user schedule information. The mobile terminal sensors include acceleration sensors, biometric sensors, and light sensors. The program linkage module is used to link other applications based on the determined user scenario; The sentiment index of the SMS text is obtained through the features of the received SMS text, and based on the sentiment index of the SMS text, linkage operations with other applications are triggered.

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