Short message real-time processing method and device

Abstract

The invention provides a short message real-time processing method and electronic equipment, and the method comprises the steps: receiving a short message sending request containing the content of a short message to be sent, initiating a real-time classification request of the content of the short message, enabling a classification module to carry out the text matching of the content of the short message and a classified short message, obtaining a text matching degree, and transmitting the text matching degree to a server; and determining the short message type of the short message content based on the text matching degree, and feeding back the short message type to the supervision platform, so that the supervision platform processes the short message sending request according to the short message type, and therefore, real-time processing of the short message can be performed without depending on a large number of labeled samples, and the cold start problem is solved. And the dynamic change of the short message content is adapted based on the text matching logic, so that the manual frequent sample updating is not needed, the real-time identification requirement is met, the dependence on the sample labeling accuracy is reduced, the classification consistency is improved through the direct matching of the classified short messages, and the classification precision requirement is met.

Description

Technical Field

[0001] This application relates to the field of data processing, and more particularly to a method and apparatus for real-time processing of text messages. Background Technology

[0002] With the development of mobile communication technology, industry SMS has become an important channel for communication between enterprises and users, covering various scenarios such as business promotion and notification reminders. According to regulatory requirements, industry SMS messages need to be reported according to categories, but in practice, a large number of SMS messages do not conform to the reported categories, posing a challenge to regulatory work.

[0003] Current SMS type identification methods largely rely on traditional machine learning algorithms, training models through labeled samples to achieve classification. However, this approach has significant drawbacks, such as a high dependence on the accuracy of sample labeling; labeling bias or incomplete labeling leads to insufficient classification accuracy. Furthermore, when SMS content changes dynamically, the model requires manual updates and retraining, making it difficult to adapt to real-time identification needs. Additionally, the initial deployment of the system lacks labeled samples, resulting in a cold start problem, while manual labeling is costly and time-consuming. These issues prevent existing technologies from efficiently and accurately meeting the requirements of real-time SMS processing. Therefore, a more efficient and accurate real-time SMS processing method is urgently needed. Summary of the Invention

[0004] This application provides a method and apparatus for real-time SMS processing, which can improve the accuracy and efficiency of SMS type identification while performing real-time SMS processing.

[0005] To achieve the above objectives, the embodiments of this application adopt the following technical solutions: In a first aspect, embodiments of this application provide a real-time SMS processing method, the method comprising: receiving an SMS sending request, the SMS sending request containing SMS content to be sent; initiating a real-time classification request for the SMS content, so that a classification module performs text matching between the SMS content and classified SMS messages to obtain a text matching degree; determining the SMS type of the SMS content based on the text matching degree; and feeding back the SMS type to a monitoring platform, so that the monitoring platform processes the SMS sending request according to the SMS type.

[0006] In another possible implementation, determining the SMS type of the SMS content based on the text matching degree includes: if the text matching degree is greater than or equal to a preset threshold, determining a first SMS type of the SMS content based on the SMS type corresponding to the classified SMS; if the text matching degree is less than the preset threshold, performing type recognition on the SMS content based on a large model to obtain a second SMS type of the SMS content.

[0007] In another possible implementation, determining the SMS type of the SMS content based on the SMS type corresponding to the classified SMS includes: sorting the classified SMS according to the text matching degree to obtain a list of classified SMS; taking the classified SMS in the list of classified SMS at a preset position as the target classified SMS; counting the number of SMS types of the target classified SMS, and taking the SMS types with a number of SMS types greater than a threshold as the first SMS type of the SMS content.

[0008] In another possible implementation, initiating a real-time classification request for the SMS content, so that the classification module can perform text matching between the SMS content and the already classified SMS messages to obtain a text matching degree, includes: initiating a real-time classification request for the SMS content, so that the classification module can extract a first text feature of the SMS content; performing text matching based on the first text feature and a plurality of pre-extracted second text features of the already classified SMS messages to obtain each matching feature item; and calculating the average value based on the number of the already classified SMS messages and each matching feature item to obtain the text matching degree.

[0009] In another possible implementation, the method further includes: labeling the SMS content based on a second SMS type to obtain labeled SMS messages; writing the labeled SMS messages into an SMS library storing the categorized SMS messages, so that when other SMS sending requests are received, the SMS types of other SMS messages included in the other SMS sending requests are determined based on the labeled SMS messages and the categorized SMS messages stored in the SMS library.

[0010] In another possible implementation, the method further includes: obtaining SMS samples from an SMS gateway; performing type identification on the SMS samples using a large model to obtain the SMS type of the SMS samples; and labeling the SMS samples based on the SMS type of the SMS samples to obtain the classified SMS.

[0011] In another possible implementation, the method includes: determining whether the SMS information of the SMS content matches the reporting category of the SMS content; if not, imposing sending restrictions on the sender corresponding to the SMS sending request.

[0012] Secondly, embodiments of this application provide a real-time SMS processing apparatus, comprising: a request acquisition module for receiving an SMS sending request, the SMS sending request containing SMS content to be sent; a text matching module for initiating a real-time classification request for the SMS content, so that the classification module performs text matching between the SMS content and classified SMS messages to obtain a text matching degree; a type determination module for determining the SMS type of the SMS content based on the text matching degree; and an SMS type feedback module for feeding back the SMS type to a monitoring platform, so that the monitoring platform processes the SMS sending request according to the SMS type.

[0013] Thirdly, embodiments of this application provide a computer-readable storage medium storing a computer program for executing the real-time SMS processing method provided in the first aspect above.

[0014] Fourthly, embodiments of this application also provide an electronic device, including: one or more processors; and a memory configured to store one or more programs; wherein, when the one or more programs are executed by the one or more processors, the one or more processors implement the real-time processing method for SMS messages as described in any one of the first aspects above.

[0015] Fifthly, embodiments of this application provide a computer program product that, when instructions in the computer program product are executed by a processor, performs the real-time SMS processing method provided in the first aspect above. Attached Figure Description

[0016] Figure 1 This is a flowchart illustrating a real-time SMS processing method provided in an embodiment of this application.

[0017] Figure 2 This is a flowchart for determining SMS type, provided as an embodiment of this application.

[0018] Figure 3 This is a schematic diagram of a real-time SMS processing device provided in an embodiment of this application.

[0019] Figure 4 This is a schematic diagram of an electronic device provided in an embodiment of this application. Detailed Implementation

[0020] The technical solutions of the embodiments of this application will now be described with reference to the accompanying drawings. To facilitate a clear description of the technical solutions of the embodiments of this application, the use of terms such as "first," "second," etc., in the embodiments of this application is for illustrative purposes and to distinguish the objects being described. There is no particular order between them, nor does it indicate a specific limitation on the number of devices in the embodiments of this application, and they do not constitute any limitation on the embodiments of this application.

[0021] To address the challenges of cold-start sample annotation, classification accuracy dependence on sample quality, and model update lag in real-time SMS processing, this application provides a real-time SMS processing method. This method receives an SMS sending request containing the content to be sent, initiates a real-time classification request for the SMS content, and enables the classification module to perform text matching between the SMS content and already classified SMS messages to obtain a text matching score. Based on the text matching score, the SMS type is determined, and the SMS type is fed back to the monitoring platform. The monitoring platform then processes the SMS sending request according to the SMS type. This method allows for real-time SMS processing without relying on a large number of labeled samples, solving the cold-start problem. Furthermore, it adapts to dynamic changes in SMS content based on text matching logic, eliminating the need for frequent manual sample updates, meeting real-time recognition requirements, reducing reliance on the accuracy of sample annotation, and improving classification consistency through direct matching of already classified SMS messages, thus meeting classification accuracy requirements.

[0022] Figure 1 A flowchart illustrating a real-time SMS processing method provided in this application embodiment is shown below. Figure 1 As shown, the method includes steps 101 to 104.

[0023] Step 101: Receive SMS sending request.

[0024] The real-time SMS processing method provided in this embodiment can be applied to an SMS gateway. The SMS gateway connects SMS senders and receivers, handling SMS forwarding, processing, and regulatory integration. In practical applications, the SMS gateway can send SMS requests containing SMS content via interfaces such as Hypertext Transfer Protocol (HTTP). For example, when the SMS gateway receives an SMS sending request from an organization or user, it will immediately activate the real-time SMS processing method described in this embodiment to ensure timely and accurate determination and feedback of the SMS type, thereby effectively supporting the regulatory platform's standardization and management of the SMS sending behavior of organizations or users.

[0025] In practical applications, there are scenarios where it is necessary to verify whether the SMS type of the content sent by the SMS sender is consistent with the reported type (e.g., commercial SMS, notification SMS, public service SMS, etc.). In this scenario, after receiving an SMS sending request, the SMS gateway will determine the SMS type of the SMS content and feed the SMS type back to the regulatory platform. This allows the regulatory platform to check in real time whether the SMS sending complies with the standard (i.e., whether the SMS type is consistent with the reported type), so as to quickly identify abnormal SMS (such as SMS that disguises commercial promotion as notification) and ensure that the SMS service complies with the standard.

[0026] For example, an SMS sending request includes the content of an SMS message to be sent. The SMS content may be in the form of at least one of the following: text, numbers, or symbols. After receiving the SMS sending request, the SMS gateway extracts the SMS content to prepare for subsequent classification processing.

[0027] Step 102: Initiate a real-time classification request for the SMS content so that the classification module can perform text matching between the SMS content and the already classified SMS messages to obtain the text matching score.

[0028] For example, a real-time classification request refers to a request generated and sent immediately by the SMS gateway after receiving the SMS content. This request aims to trigger the classification module to perform real-time classification processing on the SMS content. The classification module can be configured with the K-Nearest Neighbors (KKN) algorithm to determine the SMS type of the SMS content. In addition, other models with classification functions can also be configured in the classification module, which are not limited in this embodiment.

[0029] Classified SMS messages refer to SMS messages whose types have been pre-identified using a large model. To improve matching efficiency, SMS samples can be further labeled based on their types. The SMS samples cover a variety of possible SMS types, such as commercial promotions, notifications, and public service announcements.

[0030] In some examples, SMS samples are obtained, and the SMS samples are type-identified using a large model to obtain the SMS type of the SMS samples. Based on the SMS type of the SMS samples, the SMS samples are labeled to obtain the classified SMS.

[0031] The large-scale model can be pre-trained and optimized to improve the accuracy and efficiency of type recognition. During training, the large-scale model continuously learns the feature patterns in SMS samples, enabling it to classify new SMS content more accurately. For example, during type recognition, the large-scale model identifies and labels SMS samples according to prescribed classification criteria (such as three main categories: commercial promotion, notification reminders, and public service announcements, plus 11 subcategories within commercial promotion). For example, the large-scale model analyzes the text content of SMS samples using deep learning algorithms, extracts key features, and compares them with preset classification criteria to determine the specific type of each SMS sample. Furthermore, after obtaining classified SMS messages, the classification module can store them in a dedicated database for quick retrieval during subsequent text matching.

[0032] After initiating a real-time classification request for SMS content, the classification module extracts the first text features of the SMS content. These features may include keywords, phrases, sentence structure, etc., used to represent the core information of the SMS content. Simultaneously, the classification module extracts the second text features from pre-stored classified SMS messages.

[0033] Next, the classification module performs text matching based on the first and second text features to obtain each matching feature item. The matching feature items reflect the degree of similarity between the SMS content and the already classified SMS messages.

[0034] The categorized SMS messages serve as a baseline dataset for text matching, providing a reference for determining the type of newly received SMS messages. In practical applications, the categorized SMS message database is continuously updated and expanded to adapt to the ever-changing content and types of SMS messages, ensuring the accuracy and timeliness of text matching.

[0035] It should be noted that the above-mentioned process of obtaining SMS samples, identifying the SMS sample type through a large model, and labeling the SMS sample based on the SMS sample type can be regarded as the cold start process of the classification model. The real-time SMS processing method provided in this embodiment does not need to rely on a large number of labeled samples to train the classification model. It directly uses a large model to generate SMS samples, solves the sample labeling problem in the cold start process, and reduces the initial deployment cost and cycle of the model.

[0036] Text matching score can be a quantitative indicator that measures the similarity between SMS content and categorized SMS messages. The numerical range of text matching score can be set according to actual needs, for example, between 0 and 1. The closer the value is to 1, the higher the similarity, and the closer the value is to 0, the lower the similarity. Another example is between 0% and 100%, where the closer the value is to 100%, the higher the similarity, and the closer the value is to 0%, the lower the similarity.

[0037] During text matching in the classification module, a real-time classification request for the SMS content is initiated, enabling the classification module to extract the first text features of the SMS content. Based on the first text features and pre-extracted second text features from multiple classified SMS messages, text matching is performed to obtain each matching feature item. The average of the number of classified SMS messages and each matching feature item is calculated to obtain the text matching degree. This process, through precise feature extraction and matching algorithms, ensures the accuracy and reliability of the text matching degree, providing a basis for subsequent SMS classification.

[0038] The text features can be features that represent the semantics of the text, such as word frequency features, word vector features, and grammatical structure features. For example, the process of the classification module extracting the first text feature may include: counting the word frequency of each word in the text message content, for example, "promotion" appears 3 times in the text message and "notification" appears 1 time, and then organizing the word frequency of each word into a fixed-length vector according to the order of the preset word set. For example, if the preset word set contains "promotion", "notification", and "event", and the word frequencies of the three in a certain text message are 3, 1, and 2 respectively, the corresponding word frequency feature is [3, 1, 2].

[0039] Alternatively, the process of extracting the first text features by the classification module may include: using a pre-trained word vector model (such as Word2Vec, GloVe, etc.) to convert each word into a fixed-dimensional vector, thereby obtaining word vector features. Alternatively, grammatical analysis tools may be used to extract grammatical structure information of the SMS content, such as sentence components and dependency relations, as grammatical structure features.

[0040] After obtaining the first and second text features, the classification module can measure the text similarity between texts by calculating indicators such as cosine similarity and Euclidean distance between the first and second text features, and use the text similarity as the text matching degree.

[0041] Step 103: Determine the SMS type of the SMS content based on the text matching degree. In some examples, if the text matching degree is greater than or equal to a preset threshold, the first SMS type of the SMS content is determined based on the SMS types corresponding to the already classified SMS messages.

[0042] Figure 2 A flowchart for determining SMS type is provided as an embodiment of this application, such as... Figure 2 As shown, the above method for determining the first SMS type of SMS content based on the SMS type corresponding to the classified SMS includes steps 201 to 203.

[0043] Step 201: Sort the categorized SMS messages according to the text matching degree to obtain a list of categorized SMS messages.

[0044] In some examples, multiple categorized text messages are sorted based on their text match scores to obtain a categorized text message list. The categorized text message at the top of the list has the highest text match score, followed by the next categorized text messages with decreasing text match scores.

[0045] Step 202: Select the classified SMS messages that are in a preset position in the classified SMS list as the target classified SMS messages.

[0046] For example, the preset position can be selected according to actual needs, and this embodiment does not limit it. For example, the top n classified SMS messages in the classified SMS list are selected as target classified SMS messages. When n is 1, the first classified SMS message in the classified SMS list is selected as the target classified SMS message. Since this classified SMS message has the highest text matching degree with the SMS content, the accuracy of SMS type determination can be ensured to the greatest extent. When n is greater than 1, the text matching degree of multiple classified SMS messages with SMS content can be considered. For example, the SMS type with the highest frequency among multiple target classified SMS messages can be selected as the first SMS type of the SMS content, thereby further improving the reliability of SMS type determination.

[0047] Step 203: Count the number of SMS types in the target categorized SMS messages, and take the SMS types with a number of SMS types greater than the threshold as the first SMS type of the SMS content.

[0048] For example, when determining the SMS type of the SMS content based on the number of SMS types in the target categorized SMS messages, the SMS type that appears most frequently among the SMS types in the target categorized SMS messages can be used as the first SMS type of the SMS content.

[0049] For example, suppose there are five categorized SMS messages in the target group. Three of them are promotional messages, one is a notification, and one is a public service announcement. Since promotional messages are the most numerous (three in total, assuming a threshold of two), they are considered the primary message type. This approach comprehensively considers the types of multiple categorized SMS messages with high text matching, avoiding errors in message type determination due to inaccurate identification of a single categorized message type, thus improving the accuracy and reliability of message type determination. Furthermore, if, after counting the number of message types in the target group's categorized SMS messages, no message type exceeds the threshold, the scope of the target group's categorized SMS messages can be further expanded. For example, the preset ranking can be increased from the original top n positions to the top n + m positions, and the number of message types can be recounted to determine the primary message type.

[0050] In some examples, if the text matching degree is less than the preset threshold, the SMS content is type-identified based on a large model to obtain the second SMS type of the SMS content.

[0051] The large model can be one with semantic recognition capabilities. On the one hand, based on the fast response and high efficiency of the classification model, the classification model can quickly process highly similar SMS messages. On the other hand, based on the strong semantic understanding and high accuracy of the large model, the large model can process low-similarity SMS messages, thus achieving a balance between efficiency and accuracy.

[0052] Step 104: Feedback the SMS type to the regulatory platform so that the regulatory platform can process the SMS sending request according to the SMS type.

[0053] After determining the SMS type, the SMS type can be reported to the regulatory platform so that the platform can check in real time whether the SMS sending complies with the standards (i.e. whether the SMS type is consistent with the reported type), so as to quickly identify abnormal SMS (such as SMS that disguises commercial promotion as notification) and ensure that the SMS service complies with the standards.

[0054] In some examples, the real-time SMS processing method provided in this application further includes: labeling the SMS content based on a second SMS type to obtain labeled SMS; writing the labeled SMS into an SMS database storing categorized SMS, so that when other SMS sending requests are received, the SMS types of other SMS included in the other SMS sending requests are determined based on the labeled SMS and categorized SMS stored in the SMS database.

[0055] For example, adding labeled SMS messages to the SMS database continuously enriches the data resources within it. As labeled SMS messages are added, the database covers a wider variety of SMS types and content, providing more comprehensive and sufficient reference data for processing subsequent SMS sending requests. When other SMS sending requests are received, the classification module, based on the labeled and classified SMS messages stored in the database, can more accurately calculate text matching scores and thus more precisely determine the SMS type because there are more similar or related messages for reference. Furthermore, this dynamic updating of the SMS database allows the system to adapt to constantly changing SMS content and type trends, effectively responding to the emergence of various new types of SMS messages, ensuring the timeliness and accuracy of the entire real-time SMS processing method, continuously providing reliable SMS type feedback to the regulatory platform, and guaranteeing the standardized and orderly operation of SMS services.

[0056] In some examples, it is determined whether the SMS information in the SMS content matches the reporting category of the SMS content; if not, sending restrictions are imposed on the sender corresponding to the SMS sending request; if yes, no processing is required.

[0057] For example, the SMS content includes the specific content, sending time, and sending frequency of the message. The reporting category is the type of SMS message that the sender has reported to the regulatory platform in advance, such as commercial promotion or notification reminder. After determining the SMS content's type, the system further checks whether the SMS information matches the reported category. If the SMS content is found to be commercial promotion, but the reported category is notification reminder, or if the SMS content is sent too frequently, exceeding the normal frequency range for notification reminders, then the reported category of the SMS information will be deemed inconsistent. In this case, the system will restrict the sender corresponding to the SMS sending request, such as limiting the number of SMS messages they can send within a certain period, or completely prohibiting them from sending SMS messages, thereby ensuring that the SMS service complies with standards and preventing the spread of abnormal SMS messages. At the same time, the regulatory platform will also record this abnormal behavior as a basis for subsequent supervision.

[0058] The real-time SMS processing method provided in this application receives an SMS sending request containing SMS content to be sent, initiates a real-time classification request for the SMS content, so that the classification module performs text matching between the SMS content and the already classified SMS to obtain the text matching degree. Based on the text matching degree, the SMS type of the SMS content is determined, and the SMS type is fed back to the monitoring platform so that the monitoring platform can process the SMS sending request according to the SMS type. In this way, real-time SMS processing can be performed without relying on a large number of labeled samples, solving the cold start problem. It also adapts to the dynamic changes of SMS content by relying on text matching logic, eliminating the need for frequent manual updates of samples, meeting the real-time recognition requirements, reducing the dependence on the accuracy of sample labeling, and improving classification consistency by directly matching the already classified SMS, thus meeting the classification accuracy requirements.

[0059] Corresponding to the aforementioned embodiments of the real-time SMS processing method, this application also provides embodiments of a real-time SMS processing apparatus. Figure 3 A real-time SMS processing device provided in this application embodiment, such as Figure 3 As shown, the real-time SMS processing device 300 includes a request acquisition module 301, a text matching module 302, a type determination module 303, and an SMS type feedback module 304.

[0060] The request acquisition module 301 is used to receive SMS sending requests, wherein the SMS sending requests contain the content of the SMS to be sent; The text matching module 302 is used to initiate a real-time classification request for the SMS content, so that the classification module can perform text matching between the SMS content and the classified SMS to obtain the text matching degree. The type determination module 303 is used to determine the SMS type of the SMS content based on the text matching degree; The SMS type feedback module 304 is used to feed back the SMS type to the regulatory platform so that the regulatory platform can process the SMS sending request according to the SMS type.

[0061] In another possible implementation, the type determination module 303 is used to determine the first SMS type of the SMS content based on the SMS type corresponding to the classified SMS if the text matching degree is greater than or equal to a preset threshold; and to obtain the second SMS type of the SMS content by performing type recognition on the SMS content based on a large model if the text matching degree is less than the preset threshold.

[0062] In another possible implementation, the type determination module 303 is used to sort the classified SMS messages according to the text matching degree to obtain a list of classified SMS messages; to take the classified SMS messages in the list of classified SMS messages at a preset position as target classified SMS messages; to count the number of SMS types of the target classified SMS messages, and to take the SMS types with a number of SMS types greater than a threshold as the first SMS type of the SMS content.

[0063] In another possible implementation, the text matching module 302 is used to initiate a real-time classification request for the SMS content, so that the classification module extracts a first text feature of the SMS content; performs text matching based on the first text feature and a plurality of pre-extracted second text features of the classified SMS messages to obtain each matching feature item; and calculates the average value based on the number of classified SMS messages and each matching feature item to obtain the text matching degree. In yet another possible implementation, the method further includes labeling the SMS content based on a second SMS type to obtain labeled SMS messages; writing the labeled SMS messages into an SMS database storing the classified SMS messages, so that when other SMS sending requests are received, the SMS types of other SMS messages included in the other SMS sending requests are determined based on the labeled SMS messages and the classified SMS messages stored in the SMS database.

[0064] In another possible implementation, the method further includes: acquiring SMS samples; performing type identification on the SMS samples using a large model to obtain the SMS type of the SMS samples; and labeling the SMS samples based on the SMS type of the SMS samples to obtain the classified SMS messages.

[0065] In another possible implementation, the method further includes: determining whether the SMS information in the SMS content matches the reporting category of the SMS content; if not, imposing sending restrictions on the sender corresponding to the SMS sending request.

[0066] The beneficial technical effects corresponding to the above-described exemplary embodiment of the real-time SMS processing device 300 can be found in the corresponding beneficial technical effects in the above-described method embodiment section, and will not be repeated here.

[0067] Figure 4 This is a schematic diagram of an electronic device provided in some embodiments of this application. In some embodiments, the electronic device may be a server, a terminal device, etc. The electronic device includes a multi-core processor and a memory. The multi-core processor includes multiple processor cores; the memory is configured to store one or more programs. When the one or more programs are executed by the multi-core processor, the multi-core processor implements the real-time SMS processing method in the above embodiments.

[0068] like Figure 4 As shown, the electronic device 400 includes a multi-core processor 401 and a memory 402. Exemplarily, the electronic device 400 may also include a communications interface 403 and a communications bus 404.

[0069] The multi-core processor 401, memory 402, and communication interface 403 communicate with each other via communication bus 404. Communication interface 403 is used to communicate with other network elements such as clients or other servers.

[0070] In some examples, a multi-core processor 401 is used to execute program 405, specifically performing the relevant steps in the above-described real-time SMS processing method embodiments. Specifically, program 405 may include program code comprising computer-executable instructions.

[0071] For example, the multi-core processor 401 may be a central processing unit (CPU), an application-specific integrated circuit (ASIC), or one or more integrated circuits configured to implement some embodiments of this application. The electronic device 400 may include multi-core processors, which may be of the same type, such as one or more CPUs; or they may be of different types, such as one or more CPUs and one or more ASICs.

[0072] In some examples, memory 402 is used to store program 405. Memory 402 may include high-speed RAM memory, and may also include non-volatile memory (NVM), such as at least one disk storage device.

[0073] Specifically, program 405 can be called by multi-core processor 401 to enable electronic device 400 to perform real-time SMS processing operations.

[0074] Some embodiments of this application provide a computer-readable storage medium storing at least one executable instruction that, when executed on an electronic device 400, causes the electronic device 400 to perform the real-time SMS processing method described in the above embodiments.

[0075] The executable instructions can specifically be used to cause the electronic device 400 to perform operations of a real-time SMS processing method. For example, the computer-readable storage medium can be a read-only memory (ROM), a random access memory (RAM), a compact disc read-only memory (CD-ROM), magnetic tape, floppy disk, and optical data storage device, etc.

[0076] The beneficial effects that the readable storage medium provided in some embodiments of this application can achieve can be referred to the beneficial effects in the corresponding real-time SMS processing method provided above, and will not be repeated here.

[0077] In addition to the methods, apparatus, and devices described above, embodiments of this application may also provide a computer program product, including computer program instructions, which, when executed by a processor, cause the processor to perform the steps of the real-time SMS processing methods of various embodiments of this application described in the above-described method embodiments section.

[0078] Computer program products can be written in any combination of one or more programming languages ​​to perform the operations of the embodiments of this application. These programming languages ​​include object-oriented programming languages ​​such as Java and C++, as well as conventional procedural programming languages ​​such as C or similar languages. The program code can be executed entirely on the user's computing device, partially on the user's computing device, as a standalone software package, partially on the user's computing device and partially on a remote computing device, or entirely on a remote computing device or server.

[0079] Furthermore, embodiments of this application may also be computer-readable storage media storing computer program instructions thereon, which, when executed by a processor, cause the processor to perform the steps of the real-time SMS processing methods of various embodiments of this application described in the above-described method embodiment section.

[0080] Computer-readable storage media may take the form of any combination of one or more readable media. A readable medium may be a readable signal medium or a readable storage medium. A readable storage medium may include, but is not limited to, systems, apparatuses, or devices that are electrical, magnetic, optical, electromagnetic, infrared, or semiconductor, or any combination thereof. More specific examples of readable storage media (a non-exhaustive list) include: electrical connections having one or more wires, portable disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0081] The basic principles of this application have been described above with reference to specific embodiments. However, the advantages, benefits, and effects mentioned in this application are merely examples and not limitations, and should not be considered as essential features of each embodiment of this application. Furthermore, the specific details of the above embodiments are for illustrative and facilitative purposes only, and are not limitations. These details do not restrict this application from being implemented using the aforementioned specific details.

[0082] Those skilled in the art can make various modifications and variations to this application without departing from the spirit and scope of this application. Therefore, if such modifications and variations fall within the scope of the claims of this application and their equivalents, this application also intends to include such modifications and variations.

[0083] Furthermore, the embodiments described above are merely specific embodiments of this application and are not intended to limit the scope of protection of this application. Any modifications, equivalent substitutions, improvements, etc., made based on the technical solution of this application should be included within the scope of protection of this application.

Claims

1. A method for real-time processing of text messages, characterized in that, Applied to SMS gateways, the method includes: Receive an SMS sending request, wherein the SMS sending request contains the content of the SMS to be sent; Initiate a real-time classification request for the SMS content so that the classification module can perform text matching between the SMS content and the already classified SMS messages to obtain the text matching degree; Based on the text matching degree, the SMS type of the SMS content is determined; The SMS type is fed back to the regulatory platform so that the regulatory platform can process the SMS sending request according to the SMS type.

2. The real-time SMS processing method according to claim 1, characterized in that, Determining the SMS type based on the text matching degree includes: If the text matching degree is greater than or equal to a preset threshold, the first SMS type of the SMS content is determined based on the SMS type corresponding to the classified SMS. If the text matching degree is less than the preset threshold, the SMS content is type-identified based on the large model to obtain the second SMS type of the SMS content.

3. The real-time SMS processing method according to claim 2, characterized in that, The step of determining the SMS type of the SMS content based on the SMS type corresponding to the classified SMS includes: Based on the text matching degree, the categorized text messages are sorted to obtain a list of categorized text messages; The classified SMS messages that are in a preset position in the classified SMS list are taken as the target classified SMS messages; The number of SMS types in the target categorized SMS messages is counted, and the SMS types with a number greater than a threshold are taken as the first SMS type of the SMS content.

4. The real-time SMS processing method according to claim 1, characterized in that, The step of initiating a real-time classification request for the SMS content, so that the classification module can perform text matching between the SMS content and already classified SMS messages to obtain the text matching score, includes: Initiate a real-time classification request for the SMS content so that the classification module can extract the first text features of the SMS content; Based on the first text feature and the second text features of multiple pre-extracted classified text messages, text matching is performed to obtain each matching feature item; The text matching degree is obtained by calculating the mean of the number of classified text messages and each matching feature item.

5. The real-time SMS processing method according to claim 2, characterized in that, The method further includes: The SMS content is labeled based on a second SMS type to obtain labeled SMS messages; The labeled SMS messages are written into an SMS database that stores the categorized SMS messages, so that when other SMS message sending requests are received, the SMS message types of other SMS messages included in the other SMS message sending requests are determined based on the labeled SMS messages and the categorized SMS messages stored in the SMS database.

6. The real-time SMS processing method according to claim 1, characterized in that, The method further includes: Obtain SMS samples; The SMS sample is identified by a large model to obtain the SMS type of the SMS sample; The SMS samples are labeled based on their SMS types to obtain the categorized SMS messages.

7. The real-time SMS processing method according to claim 1, characterized in that, The method includes: Determine whether the SMS information in the SMS content matches the reporting category of the SMS content; If not, restrict the sending of the SMS message to the sender corresponding to the SMS sending request.

8. A real-time SMS processing device, characterized in that, The device includes: The request acquisition module is used to receive SMS sending requests, wherein the SMS sending request contains the content of the SMS to be sent; The text matching module is used to initiate a real-time classification request for the SMS content, so that the classification module can perform text matching between the SMS content and the classified SMS to obtain the text matching degree. The type determination module is used to determine the SMS type of the SMS content based on the text matching degree; The SMS type feedback module is used to feed back the SMS type to the regulatory platform so that the regulatory platform can process the SMS sending request according to the SMS type.

9. A computer-readable storage medium storing a computer program that, when executed by a processor, implements the real-time processing method for SMS messages according to any one of claims 1-7.

10. An electronic device, characterized in that, include: One or more processors; and The memory is configured to store one or more programs. When the one or more programs are executed by the one or more processors, the one or more processors implement the real-time SMS processing method according to any one of claims 1-7.

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