Short message content generation method and device, medium and product

Abstract

The invention discloses a short message content generation method and device, a medium and a product, and relates to the technical field of artificial intelligence and financial science and technology, and the method comprises the steps: building a short message template library through a first large model according to the short message content data of a regional business scene; according to the short message unsubscribing information, a customer group information set is generated based on a short message unsubscribing behavior division rule; according to the customer group information set and a preset short message scene information base, constructing a service scene base through a second large model; screening short message service templates according to the similarity between the short message scene information and the service scene information, and constructing a short message service library with the matched customer group description information; and when short message demand information is received, extracting target service scene information, a target region and target customer group description information, screening a target short message service template, and generating target short message content push. The short message template is screened according to the business scene and the customer group characteristics, so that the correlation of the short message content is ensured, and the accuracy and efficiency of generating the short message content are improved.

Description

Technical Field

[0001] The present invention relates to the fields of artificial intelligence and financial technology, and in particular to a method, device, medium and product for generating text message content. Background Art

[0002] In scenarios like SMS marketing or business notifications, the creation of SMS content requires approval and maintenance from multiple departments, including business and legal. The business department is responsible for developing the core business information and marketing points to be conveyed in the SMS, ensuring that the content accurately reflects business needs. The legal department, on the other hand, focuses on reviewing the legality and compliance of the SMS content.

[0003] In the prior art, business personnel typically select a template from a pre-established SMS template management system based on specific SMS content requirements, then manually modify the variable content to generate the final SMS content to be sent. However, with the development of businesses and the acceleration of market changes, the requirements for SMS content generation are becoming increasingly complex and large in volume. Traditional template management systems often require a long production cycle, increasing time and labor costs while reducing SMS content generation efficiency. Furthermore, the quality of the generated SMS messages is unstable, with relatively monotonous content and format, lacking individuality, and reducing the accuracy of SMS content generation. Summary of the Invention

[0004] The present invention provides a method, device, medium and product for generating text message content, so as to solve the problems of high time cost, high labor cost, low efficiency and poor accuracy in generating text message content.

[0005] According to one aspect of an embodiment of the present invention, a method for generating text message content is provided, comprising:

[0006] Constructing a SMS template library using a first model based on SMS content data for at least one business scenario in at least one region; wherein the SMS templates in the SMS template library correspond to the set region and business scenario information;

[0007] Based on the SMS unsubscription information of each customer, a customer group information set with different customer group description information is generated based on the SMS unsubscription behavior classification rules; wherein the customer group description information includes the type and level of the customer;

[0008] Based on the customer group information set and the preset SMS scenario information library, a business scenario library is constructed through the second model; wherein the business scenario library includes the correspondence between customer group description information and SMS scenario information;

[0009] Based on the similarity between SMS scenario information and business scenario information, SMS business templates are screened from the SMS template library, and the SMS business templates and matching customer group description information are used to build an SMS business library;

[0010] When receiving SMS demand information, extract the target business scenario information, target region and target customer group description information from the SMS demand information;

[0011] Based on the target business scenario information and target area, the target SMS business template is selected from the SMS business library, and the target SMS content generated based on the target SMS business template and SMS demand information is pushed to each customer in the target area who matches the target customer description information.

[0012] According to another aspect of an embodiment of the present invention, a device for generating text message content is provided, comprising:

[0013] A template library module, configured to construct a text message template library using a first model based on text message content data for at least one business scenario in at least one region; wherein the text message templates in the text message template library correspond to the set region and business scenario information;

[0014] The customer group module is used to generate customer group information sets with different customer group description information based on the SMS unsubscription information of each customer and the SMS unsubscription behavior classification rules; wherein the customer group description information includes the type and level of the customer;

[0015] The scenario library module is used to construct a business scenario library through the second model based on the customer group information set and the preset SMS scenario information library; wherein the business scenario library includes the correspondence between customer group description information and SMS scenario information;

[0016] The business library module is used to filter SMS business templates in the SMS template library based on the similarity between SMS scenario information and business scenario information, and to build an SMS business library using SMS business templates and matching customer group description information;

[0017] A demand extraction module is used to extract target business scenario information, target region and target customer group description information from the SMS demand information when receiving the SMS demand information;

[0018] The content generation module is used to filter the target SMS business template from the SMS business library according to the target business scenario information and the target area, and push the target SMS content generated according to the target SMS business template and SMS demand information to each customer in the target area who matches the target customer description information.

[0019] According to another aspect of an embodiment of the present invention, an electronic device is provided, the electronic device comprising:

[0020] At least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor so that the at least one processor can execute the method for generating text message content according to any embodiment of the present invention.

[0021] According to another aspect of an embodiment of the present invention, a computer-readable storage medium is provided, wherein the computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the method for generating text message content according to any embodiment of the present invention when executed.

[0022] According to another aspect of an embodiment of the present invention, a computer program product is provided, including a computer program, wherein when the computer program is executed by a processor, the steps of the method according to any embodiment of the present invention are implemented.

[0023] The technical solution of the embodiment of the present invention is to construct an SMS template library through a first large model based on SMS content data of at least one business scenario in at least one region; generate a customer information set under different customer description information based on SMS cancellation behavior classification rules according to the SMS cancellation information of each customer; construct a business scenario library through a second large model based on the customer information set and a preset SMS scenario information library; filter SMS business templates in the SMS template library based on the similarity between SMS scenario information and business scenario information, and construct an SMS business library using the SMS business templates and matching customer description information; when SMS demand information is received, extract target business scenario information, target region and target customer description information from the SMS demand information; filter target SMS business templates from the SMS business library based on the target business scenario information and target region, and push the target SMS content generated based on the target SMS business template and SMS demand information to each customer in the target region who matches the target customer description information. By analyzing and modeling SMS content data in different regions and business scenarios, as well as parsing customer unsubscribe information, we can achieve refined management of customer behaviors and needs in different regions and business scenarios. Combined with large models, we can automatically build SMS template libraries, customer information collections, and business scenario libraries. We can filter and match SMS templates according to different business scenarios and customer group characteristics to ensure that the SMS content sent is relevant to customer needs and interests, avoid sending irrelevant or uninteresting SMS to customers, improve customer satisfaction with SMS services, improve the accuracy of SMS content generation, reduce the time and labor costs of manual screening and matching SMS templates, and improve the efficiency of SMS content generation.

[0024] It should be understood that the content described in this section is not intended to identify the key or important features of the embodiments of the present invention, nor is it intended to limit the scope of the present invention. Other features of the present invention will become readily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0026] Figure 1 This is a flowchart of a method for generating text message content according to the first embodiment of the present invention;

[0027] Figure 2 This is a flowchart of another method for generating text message content according to the second embodiment of the present invention;

[0028] Figure 3 This is a schematic diagram of building a short message service library applicable to an embodiment of the present invention;

[0029] Figure 4 This is a structural diagram of a device for generating text message content according to a third embodiment of the present invention;

[0030] Figure 5 The present invention is a schematic diagram of the structure of an electronic device for implementing the method for generating text message content according to an embodiment of the present invention. DETAILED DESCRIPTION

[0031] In order to enable those skilled in the art to better understand the solutions of the present invention, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the embodiments described are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts should fall within the scope of protection of the present invention.

[0032] It should be noted that the terms "first", "second", etc. in the description and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that the numbers used in this way can be interchanged where appropriate so that the embodiments of the present invention described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0033] Example 1

[0034] Figure 1 This is a flowchart of a method for generating text message content provided by the first embodiment of the present invention. This embodiment is applicable to the case where text message content is automatically generated and pushed to each client. The method can be executed by a text message content generating device. The text message content generating device can be implemented in the form of hardware and / or software and can generally be configured in an electronic device. Figure 1 As shown, the method includes:

[0035] S110. Construct a text message template library using a first large model based on text message content data of at least one business scenario in at least one region.

[0036] Among them, the SMS templates in the SMS template library correspond to the set area and business scenario information.

[0037] In this embodiment of the present invention, the first large model can be specifically understood as a pre-trained machine learning or deep learning model used to parse SMS content data, extract key information and formatting, generate standardized SMS templates, and construct an SMS template library. The SMS template library can be specifically understood as storing a collection of SMS templates generated by the first large model. Optionally, the SMS template library may also include custom SMS templates maintained by business personnel. SMS templates can be specifically understood as SMS frameworks that do not contain any customer information, leave blank spaces or fill in specific characters in key information locations, and have unified scripting for subsequent personalized information during actual business push. Each SMS template is associated with a specific region. For example, some SMS templates may be designed specifically for a specific city or province to suit local language habits or business characteristics. Each SMS template is associated with a specific business scenario. For example, SMS templates can be used for different business scenarios such as account change notifications, credit card promotions, or holiday sales events.

[0038] Specifically, SMS content data (such as SMS text content, sending time, and recipient information) of at least one business scenario (such as account change notifications, financial product promotions, and holiday promotions) in at least one region is obtained, and the collected SMS content data is parsed and processed through the first model to generate standardized SMS templates, and these templates are stored in the SMS template library.

[0039] S120 : Generate customer group information sets under different customer group description information based on SMS unsubscription information of each customer and SMS unsubscription behavior classification rules.

[0040] Among them, the customer description information includes the type and level of customers.

[0041] In embodiments of the present invention, SMS unsubscription information can be specifically understood as a record of a customer's choice to no longer receive certain SMS messages, which can be generated by, for example, a customer clicking a unsubscribe link in a SMS message or replying to a unsubscribe instruction. SMS unsubscription behavior classification rules can be specifically understood as preset rules for categorizing customers based on their unsubscription behavior, which can include factors such as frequency of unsubscriptions, specific types of unsubscribed services, and the time of unsubscription. Customer group description information can be specifically understood as a description of the characteristics of a customer group, which can include, for example, customer type and level.

[0042] Specifically, the customer type can be understood as the business type to which the SMS cancellation behavior belongs, such as credit card users, savings account users, and loan customers, or the degree of SMS cancellation behavior, such as full cancellation, partial cancellation, and no cancellation. The customer level can be understood as the customer level divided according to factors such as the frequency or duration of the customer's SMS cancellation behavior. For example, if a customer cancels a credit card promotion SMS, they will be classified as "not interested in credit card promotion"; if a customer cancels SMS more than three times in a month, they will be classified as "high-frequency cancellation." Customer group information sets can be specifically understood as sets formed by grouping customers according to customer group description information, with each set including customers with similar characteristics. There are two ways to construct a customer information set: one is to cover the SMS cancellation information of at least one level of customers of the same type. For example, in the credit card business, it includes the cancellation status of customers with high frequency cancellations, low frequency cancellations, etc.; the other is to aggregate different types of customers at the same level. For example, the high-frequency cancellation customer group includes the cancellation status of customers with high frequency cancellations in the credit card SMS notification business, as well as the cancellation status of customers with high frequency cancellations in the savings account SMS notification business.

[0043] In a specific example, SMS unsubscription behavior can be categorized into three types: full unsubscription, partial unsubscription, and no unsubscription. These are ranked based on the order in which customers unsubscribe after activating SMS. For example, a customer who unsubscribes from a credit card promotional SMS within a week of activating SMS service is classified as "high probability unsubscribe." Meanwhile, a customer who unsubscribes from a holiday promotional SMS after using SMS service for several months is classified as "low probability unsubscribe."

[0044] S130. Build a business scenario library through the second largest model based on the customer group information set and the preset SMS scenario information library.

[0045] Among them, the business scenario library includes the correspondence between customer description information and SMS scenario information.

[0046] In the embodiment of the present invention, the preset SMS scenario information database can be specifically understood as a database including various SMS scenario information, such as SMS scenario information such as credit card promotion, account change notification, and holiday promotion.

[0047] The second largest model can be specifically understood as: a pre-trained machine learning or deep learning model used to analyze the relationship between the customer information set and the SMS scenario information library, and generate a business scenario library.

[0048] The business scenario library can be specifically understood as: analyzing and processing the customer information set and the SMS scenario information library through the second largest model, extracting the scenario characteristics of each SMS scenario information in the SMS scenario information library and the customer characteristics of each customer information in the customer information set and performing correlation analysis, identifying the behavior patterns and business needs of different customer groups in different SMS scenarios, and then generating a database including the business needs and behavior pattern information of different customer groups in different SMS scenarios.

[0049] S140 . Filter SMS service templates in the SMS template library based on the similarity between the SMS scenario information and the service scenario information, and construct an SMS service library using the SMS service templates and the matching customer group description information.

[0050] In the embodiment of the present invention, the SMS service library may be specifically understood as including information of various service scenarios, SMS templates corresponding to the information of various service scenarios, and customer group description information corresponding to the information of various service scenarios.

[0051] Specifically, the SMS scenario information and business scenario information are each converted into text feature vectors, including feature division dimensions such as keywords, phrases, and business themes. The text feature vectors are then encoded with business features to quantify the business attribute features in the business scenario information. The similarity between the feature vectors corresponding to the SMS scenario information and the business scenario information is calculated (similarity calculation methods such as cosine similarity or Jaccard similarity coefficient can be used). Based on business needs, the weights of the similarities of each feature division dimension, such as keyword similarity, phrase similarity, and business theme similarity, are determined. The similarities of each component are multiplied by their corresponding weights, and the weighted values are then added together to obtain the final weighted comprehensive similarity.

[0052] Filter out a target number of SMS templates from the SMS template library in descending order of similarity, or filter out SMS templates with similarity higher than a preset similarity threshold, and combine them with the corresponding customer group description information to form an SMS service library.

[0053] S150. When SMS demand information is received, target business scenario information, target region, and target customer group description information are extracted from the SMS demand information.

[0054] S160. Filter target SMS service templates from the SMS service library based on the target service scenario information and the target region, and push target SMS content generated based on the target SMS service templates and SMS demand information to each customer in the target region who matches the target customer description information.

[0055] Specifically, when a trigger instruction for SMS sending is received from a business department or business personnel, the instruction includes SMS demand information such as the specific requirements and targets for sending the SMS. The system identifies and obtains the specific business scenario, the geographic area to be sent, and the target customer's characteristics (including customer type and level) from the SMS demand information. The system searches the SMS service library for SMS templates that match the target business scenario. It further filters templates based on the target region and target customer group descriptions. Using a comprehensive similarity calculation method, the filtered templates are sorted from high to low similarity, automatically selecting the most matching SMS template or providing a preset number of recommended SMS templates for manual selection by business personnel. The system extracts the specific content required to be filled in the SMS template from the SMS demand information, such as the customer name, product name, promotion details, and links. The extracted personalized information replaces the corresponding blank spaces or variable placeholders in the selected SMS template. After all personalized information is replaced, the final target SMS content is generated and pushed to each customer in the target region who matches the target customer description.

[0056] The technical solution of the embodiment of the present invention is to construct an SMS template library through the first large model based on SMS content data of regional business scenarios; generate a customer information set under different customer description information based on SMS cancellation behavior classification rules according to the SMS cancellation information of each customer; construct a business scenario library through the second large model according to the customer information set and a preset SMS scenario information library; filter SMS business templates in the SMS template library according to the similarity between SMS scenario information and business scenario information, and use SMS business templates and matching customer description information to construct an SMS business library; when SMS demand information is received, extract target business scenario information, target region and target customer description information from the SMS demand information; filter target SMS business templates from the SMS business library according to the target business scenario information and target region, and push the target SMS content generated according to the target SMS business template and SMS demand information to each customer in the target region who matches the target customer description information. By analyzing and modeling SMS content data in different regions and business scenarios, as well as parsing customer unsubscribe information, we can achieve refined management of customer behaviors and needs in different regions and business scenarios. Combined with large models, we can automatically build SMS template libraries, customer information collections, and business scenario libraries. We can filter and match SMS templates according to different business scenarios and customer group characteristics to ensure that the SMS content sent is relevant to customer needs and interests, avoid sending irrelevant or uninteresting SMS to customers, improve customer satisfaction with SMS services, improve the accuracy of SMS content generation, reduce the time and labor costs of manual screening and matching SMS templates, and improve the efficiency of SMS content generation.

[0057] Furthermore, based on the above embodiments, the method for generating SMS content may further include:

[0058] Whenever a preset update cycle is reached, the similarity between the SMS scenario information in the business scenario library and the business scenario information in the SMS template library is calculated, and SMS templates with a similarity below a threshold are selected for updating.

[0059] Specifically, the system will regularly check the relevance of SMS templates to business scenarios. Whenever the preset update cycle (such as weekly, monthly or quarterly) is reached, the system will calculate the similarity between the SMS scenario information in the business scenario library and the business scenario information of each SMS template in the SMS template library. Compare the calculated similarity with the preset similarity threshold. If the similarity of a certain SMS template is lower than the threshold, it will be marked as a template that needs to be updated. Accordingly, the system can automatically regenerate or adjust these templates in the next update cycle to improve their similarity, such as automatically calling the first largest model to compare and integrate the SMS template that needs to be updated with the remaining SMS templates in the current business scenario, retaining the effective structure and feature information of the remaining templates in the current business scenario, while integrating the feature information of the SMS template that needs to be updated to improve the similarity. Alternatively, business personnel manually update the template to ensure that it is consistent with the business scenario.

[0060] Since business scenarios and customer needs change over time, regular updates to SMS templates ensure that SMS content always fits the current business scenario, promptly reflecting the latest business dynamics and customer preferences, and improving the adaptability and flexibility of SMS content generation. The automated update mechanism reduces the workload of manual inspection and modification of SMS templates, thereby improving the efficiency of SMS content generation.

[0061] Example 2

[0062] Figure 2 A flowchart of another SMS content generation method provided in Example 2 of the present invention. This embodiment is a refinement of the "constructing an SMS template library through a first large model based on SMS content data of at least one business scenario in at least one region" in the above embodiment, and can specifically include: obtaining SMS content data of at least one business scenario in at least one region, sorting the SMS content data by SMS type classification, and constructing at least one SMS type library based on the classification results; inputting the SMS content data in the SMS type library into the first large model to parse the SMS content, format key information, obtain at least one type of SMS template and add the SMS template to the constructed SMS template library.

[0063] Correspondingly, such as Figure 2 As shown, the method includes:

[0064] S210: Obtain SMS content data of at least one business scenario in at least one region, classify and sort the SMS content data according to SMS types, and construct at least one SMS type library based on the classification results.

[0065] In an embodiment of the present invention, the SMS type library can be specifically understood as a database that centrally stores and manages SMS messages of the same type. Based on the SMS type library, reports can be generated on SMS sending in different regions and for different business scenarios. These reports summarize SMS data for each region and business scenario, such as SMS sending volume, delivery rate, open rate, unsubscribe rate, and click-through rate, as well as predicted trends for each indicator based on a pre-trained machine learning model. This provides business personnel with a comprehensive overview of SMS sending and a foundation for data analysis.

[0066] Specifically, SMS content data of at least one business scenario in at least one region is obtained, and SMS messages are divided into different categories based on features such as the content, purpose or form of the SMS messages, for example, by region and business type. Further, the classification can be refined in the following ways: notification categories (such as account change notifications and system maintenance notifications, etc.), promotion categories (such as product promotions and event discounts, etc.), and service categories (such as customer consultation replies and business processing reminders), etc. The classified SMS messages are sorted according to preset rules, for example, by the frequency, time sequence or importance of SMS sending, thereby obtaining different SMS types and their corresponding SMS content, and creating one or more SMS type libraries.

[0067] S220: Input the SMS content data in the SMS type library into the first large model to parse the SMS content, format key information, obtain at least one type of SMS template, and add the SMS template to the constructed SMS template library.

[0068] Among them, the SMS templates in the SMS template library correspond to the set area and business scenario information.

[0069] Specifically, the system retrieves categorized and sorted SMS content data from a SMS type library and feeds it into the first model. This model then performs semantic understanding and structural analysis on the SMS content, extracting key information such as the subject line, target audience, and key business metrics. This extracted key information is then standardized and organized, such as by leaving blank spaces or filling in specific characters to ensure it conforms to predefined formatting requirements, facilitating the subsequent generation of SMS templates. Based on the parsed and formatted key information, one or more reusable SMS structure and content frameworks are generated as SMS templates, and these templates are added to the constructed SMS template library.

[0070] S230 : Generate customer group information sets under different customer group description information based on SMS unsubscription information of each customer and SMS unsubscription behavior classification rules.

[0071] Among them, the customer description information includes the type and level of customers.

[0072] S240. Build a business scenario library through the second largest model based on the customer group information set and the preset SMS scenario information library.

[0073] Among them, the business scenario library includes the correspondence between customer description information and SMS scenario information.

[0074] S250 , based on the similarity between the SMS scenario information and the business scenario information, screen the SMS business templates in the SMS template library, and construct an SMS business library using the SMS business templates and the matching customer group description information.

[0075] S260. When receiving SMS demand information, extract target business scenario information, target region, and target customer group description information from the SMS demand information.

[0076] S270. Filter target SMS service templates from the SMS service library based on the target service scenario information and the target region, and push target SMS content generated based on the target SMS service templates and SMS demand information to each customer in the target region who matches the target customer description information.

[0077] The technical solution of the embodiment of the present invention is to classify and sort the SMS content data according to SMS type based on the SMS content data of at least one business scenario in at least one region, build an SMS type library, improve the efficiency of SMS content management, realize classified storage and simplify maintenance; parse and format key information through the first large model, generate a variety of SMS templates and add them to the SMS template library, improve the quality and applicability of SMS templates, ensure that key information is prominent and meets the needs of different business scenarios; by analyzing and modeling SMS content data in different regions and different business scenarios, and parsing customer cancellation information, realize refined management of customer behavior and needs in different regions and business scenarios, and automatically build an SMS template library, customer information collection and business scenario library based on the large model, it can screen and match SMS templates according to different business scenarios and customer group characteristics, ensure that the SMS content sent is relevant to the customer's needs and interests, avoid sending irrelevant or uninteresting SMS to customers, improve customer satisfaction with SMS services, improve the accuracy of SMS content generation, reduce the time and labor costs of manual screening and matching SMS templates, and improve the efficiency of SMS content generation.

[0078] Furthermore, based on the above embodiments, after formatting the key information, the following steps may also be included:

[0079] Based on the parsing results of the SMS content, the business connections between the SMS content data in different SMS type libraries are analyzed through the first large model, at least one potential business scenario is constructed, and at least one type of SMS template matching the potential business scenario is generated.

[0080] Specifically, the first model performs semantic analysis and structural parsing on SMS content and SMS content data in the SMS type library to extract key information. This extracted key information is then compared and analyzed for correlation to uncover potential business connections. For example, credit card promotion SMS messages and loan product introduction SMS messages both involve customer financial needs. Therefore, credit card promotion and loan scenarios are related and serve as potential scenarios for each other. Accordingly, based on the analyzed business connections, new potential integrated business scenarios can be inferred. For example, by combining the business connections between credit card promotion SMS messages and loan product introduction SMS messages, a potential business scenario of "customers experiencing financial difficulties and requiring comprehensive financial services" can be constructed. Based on this constructed potential business scenario, the first model is used to generate SMS templates that are appropriate for it. These templates can include multiple business types. For example, a "comprehensive financial service recommendation" SMS template includes both credit card promotion and loan product introduction content to meet customers' diverse financial needs. By analyzing the business connections between SMS content data in different SMS type libraries, potential needs can be uncovered and SMS templates matching these potential business scenarios can be generated, further improving the accuracy and efficiency of SMS content generation and its adaptability to diverse business scenarios.

[0081] Furthermore, based on the above embodiments, after adding the SMS template to the constructed SMS template library, the following steps may be further included:

[0082] The problem SMS templates in the SMS template library are screened out through the first model, and the problem SMS templates are deleted from the SMS template library.

[0083] Specifically, the first model examines SMS templates in the SMS template library, analyzing their characters, semantics, and word usage. Based on pre-set rules and standards, it determines whether the templates contain illegal characters, semantic coherence, or misleading terms. It then identifies problematic SMS templates and removes them from the library, ensuring the standardization and professionalism of SMS templates and improving the overall quality of SMS content generation.

[0084] Furthermore, based on the above embodiments, before constructing the business scenario library through the second model according to the customer group information set and the preset SMS scenario information library, the following steps may also be included:

[0085] Each potential business scenario is added to the SMS scenario information library.

[0086] Specifically, before building the business scenario library through the second model, each potential business scenario can be added to the SMS scenario information library, thereby updating and expanding the SMS scenario information library to include more business scenario information, providing richer and more comprehensive basic data for the subsequent business scenario library construction, and improving the diversity and accuracy of SMS content generation.

[0087] Furthermore, based on the above embodiments, after pushing the message to each customer in the target area who matches the target customer description information, the following steps may be further performed:

[0088] In response to an upload instruction of a customized SMS template obtained by modifying the SMS template based on the push result, when the customized SMS template does not contain target customer group information, the customized SMS template is added to an SMS type library that matches the target region and target business scenario;

[0089] When target customer group information exists in a custom SMS template, the custom SMS template is added to an SMS service library that matches the target region, target business scenario, and target customer group information.

[0090] In the embodiment of the present invention, the customized SMS template may be specifically understood as a new SMS template obtained by a business person modifying and improving the SMS template according to the recommended SMS template.

[0091] Specifically, when business personnel make modifications based on the recommended SMS template and upload a custom SMS template, the system will add it to different libraries based on whether the template contains target customer information. If there is no target customer information in the template (that is, the customer type and level are not clear), the system will add the template to the SMS type library that matches the target area and target business scenario. If there is target customer information in the template (that is, the customer type and level are clear), the system will add it to the SMS business library that matches the target area, target business scenario and target customer information. By allowing business personnel to upload custom SMS templates and automatically adding them to the matching SMS type library or SMS business library based on whether there is target customer information in the template, the diversity, flexibility and adaptability of SMS content generation are improved, making SMS template management more accurate and efficient.

[0092] For ease of understanding, the specific application scenarios applicable to the above-mentioned embodiments of the invention are now described. In the field of financial technology, the process of generating text message content must strictly comply with the regulatory requirements of multiple departments. Business departments need to refine core business information and marketing points to ensure that the content of text messages accurately reflects the needs of financial technology services, such as key information such as new product promotion and risk management solutions, while combining market dynamics and customer needs to improve customer stickiness and business conversion rates. The legal department reviews the legality and compliance of text message content to ensure compliance with financial regulations and industry standards. As financial technology scenarios become increasingly diverse and complex, the demand for text message generation is becoming increasingly complex and the number is surging. Traditional template management systems are difficult to adapt to changing financial business scenarios due to their lack of flexibility, resulting in a long text message generation cycle, requiring a lot of time and manpower, and low efficiency. The quality of the generated text message content is uneven, the form is single, and lacks personalized elements, which makes it difficult to meet customer needs, thereby affecting the accuracy of text message marketing and customer experience. To solve the above problems, the embodiments of the present invention propose a method for generating text message content, Figure 3 FIG. 1 is a schematic diagram of a method for constructing a short message service library applicable to an embodiment of the present invention. Figure 3 The method shown includes:

[0093] SMS data from various business scenarios across regions is collected and categorized to build a SMS type library. This library provides reports on SMS messages across regions and business scenarios. The reports contain key data and trend analysis, helping business personnel understand important information such as SMS delivery effectiveness and customer feedback in different scenarios. This supports marketing strategy development, business process optimization, and improved customer service quality.

[0094] Large-scale modeling technology is used to parse SMS content in a library of SMS types. Based on this information, SMS templates are generated for various business scenarios and potential business scenarios. Key information (such as the card number and amount) is left blank or filled with specific characters. These generated SMS templates are then stored in a constructed SMS template library. Large-scale modeling technology is used to eliminate invalid SMS templates from the library that contain illegal characters, semantically incoherent content, or misleading terms.

[0095] Obtain SMS unsubscription data and categorize and sort it to establish different customer groups of different types and levels. Leverage large-scale modeling technology to assign different SMS scenarios to different customer groups of different types and levels (based on existing business scenarios, simulate and expand based on customer groups and constructed potential scenarios) to build a business scenario library.

[0096] The business scenario library and the SMS template library are matched and sorted by similarity to build an SMS business library.

[0097] According to the set update cycle, the similarity between the SMS scenario information in the business scenario library and the business scenario information in the SMS template library is calculated, and the SMS templates below the similarity threshold are screened out for update.

[0098] In response to business personnel's demand for sending SMS for a certain business scenario in a certain place, this method provides multiple SMS templates from the SMS business library according to the business scenario and region, sorted by similarity (the corresponding SMS template can be returned according to the number of recommendations set by the business personnel), and provides corresponding recommendations based on different customer groups in the area through big model technology.

[0099] After obtaining the information, business personnel will evaluate and select the appropriate SMS template. Custom modifications can be made if required. If the customer group information of the modified SMS template is uncertain, it will be re-entered into the SMS type library. If the customer group information is confirmed, it will be directly entered into the SMS business library.

[0100] The SMS content generation method proposed in the embodiment of the present invention can generate corresponding SMS content according to the characteristics of different regions, different business scenarios and different customer groups, reducing the repeated R&D work caused by regional differences, diverse business types and customer group segmentation, avoiding the manual trial and error costs in template design, and reducing the R&D investment in SMS business needs.

[0101] Example 3

[0102] Figure 4 This is a schematic diagram of the structure of a device for generating text message content provided by the third embodiment of the present invention. Figure 4 As shown, the device includes: a template library module 410, a customer group module 420, a scenario library module 430, a business library module 440, a demand extraction module 450 and a content generation module 460, wherein:

[0103] Template library module 410, configured to construct a SMS template library using a first large model based on SMS content data for at least one business scenario in at least one region; wherein the SMS templates in the SMS template library correspond to the set region and business scenario information;

[0104] The customer group module 420 is used to generate customer group information sets with different customer group description information based on the SMS unsubscription information of each customer and the SMS unsubscription behavior classification rules; wherein the customer group description information includes the type and level of the customer;

[0105] The scenario library module 430 is used to construct a business scenario library using the second model based on the customer group information set and the preset SMS scenario information library; wherein the business scenario library includes the correspondence between customer group description information and SMS scenario information;

[0106] The service library module 440 is used to filter SMS service templates from the SMS template library based on the similarity between the SMS scenario information and the service scenario information, and to construct an SMS service library using the SMS service templates and the matching customer group description information;

[0107] The demand extraction module 450 is used to extract target business scenario information, target region and target customer group description information from the SMS demand information when the SMS demand information is received;

[0108] The content generation module 460 is used to filter the target SMS service template from the SMS service library according to the target business scenario information and the target area, and push the target SMS content generated according to the target SMS service template and SMS demand information to each customer in the target area who matches the target customer description information.

[0109] The technical solution of the embodiment of the present invention is to construct an SMS template library through a first large model based on SMS content data of at least one business scenario in at least one region; generate a customer information set under different customer description information based on SMS cancellation behavior classification rules according to the SMS cancellation information of each customer; construct a business scenario library through a second large model based on the customer information set and a preset SMS scenario information library; filter SMS business templates in the SMS template library based on the similarity between SMS scenario information and business scenario information, and construct an SMS business library using the SMS business templates and matching customer description information; when SMS demand information is received, extract target business scenario information, target region and target customer description information from the SMS demand information; filter target SMS business templates from the SMS business library based on the target business scenario information and target region, and push the target SMS content generated based on the target SMS business template and SMS demand information to each customer in the target region who matches the target customer description information. By analyzing and modeling SMS content data in different regions and business scenarios, as well as parsing customer unsubscribe information, we can achieve refined management of customer behaviors and needs in different regions and business scenarios. Combined with large models, we can automatically build SMS template libraries, customer information collections, and business scenario libraries. We can filter and match SMS templates according to different business scenarios and customer group characteristics to ensure that the SMS content sent is relevant to customer needs and interests, avoid sending irrelevant or uninteresting SMS to customers, improve customer satisfaction with SMS services, improve the accuracy of SMS content generation, reduce the time and labor costs of manual screening and matching SMS templates, and improve the efficiency of SMS content generation.

[0110] Based on the above embodiments, the template library module 410 is specifically configured to:

[0111] Obtaining SMS content data for at least one business scenario in at least one region, classifying and sorting the SMS content data by SMS type, and building at least one SMS type library based on the classification results;

[0112] Input the SMS content data in the SMS type library into the first large model to parse the SMS content, format key information, obtain at least one type of SMS template and add the SMS template to the constructed SMS template library.

[0113] Optionally, based on the above embodiments, the template library module 410 may include:

[0114] The potential scenario unit is used to analyze the business connections between SMS content data in different SMS type libraries through the first large model after formatting key information based on the analysis results of the SMS content, construct at least one potential business scenario, and generate at least one type of SMS template matching the potential business scenario.

[0115] Optionally, based on the above embodiments, the template library module 410 may include:

[0116] The deletion unit is used to filter out the problem SMS templates in the SMS template library through the first model after adding the SMS templates to the constructed SMS template library, and delete the problem SMS templates from the SMS template library.

[0117] Furthermore, based on the above embodiments, the SMS content generating device may further include:

[0118] The potential adding module is used to add each potential business scenario to the SMS scenario information library before building the business scenario library through the second largest model based on the customer group information set and the preset SMS scenario information library.

[0119] Furthermore, based on the above embodiments, the SMS content generating device may further include:

[0120] The update module is used to calculate the similarity between the SMS scenario information in the business scenario library and the business scenario information in the SMS template library whenever a preset update cycle is reached, and filter out SMS templates with a similarity below a threshold for update.

[0121] Furthermore, based on the above embodiments, the SMS content generation device may further include: a first custom module and a second custom module, wherein:

[0122] A first customization module is configured to, after pushing the message to each customer in the target region that matches the target customer description, respond to an upload instruction of a customized SMS template obtained by modifying the SMS template based on the push result by a business personnel, and, if the customized SMS template does not contain the target customer group information, add the customized SMS template to a SMS type library that matches the target region and target business scenario;

[0123] The second customization module is used to add the customized SMS template to the SMS service library that matches the target area, target business scenario and target customer group information when the customized SMS template contains target customer group information.

[0124] The SMS content generation device provided in the embodiment of the present invention can execute the SMS content generation method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0125] In the technical solutions disclosed herein, the collection, storage, use, processing, transmission, provision and disclosure of user personal information involved comply with the provisions of relevant laws and regulations and do not violate public order and good morals.

[0126] Example 4

[0127] Figure 5 A schematic diagram of the structure of an electronic device 10 that can be used to implement an embodiment of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices (such as helmets, glasses, watches, etc.) and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present invention described and / or claimed herein.

[0128] like Figure 5 As shown, the electronic device 10 includes at least one processor 11 and a memory, such as a read-only memory (ROM) 12, a random access memory (RAM) 13, etc., which is communicatively connected to the at least one processor 11. The memory stores a computer program that can be executed by the at least one processor. The processor 11 can perform various appropriate actions and processes according to the computer program stored in the read-only memory (ROM) 12 or the computer program loaded from the storage unit 18 into the random access memory (RAM) 13. Various programs and data required for the operation of the electronic device 10 can also be stored in the RAM 13. The processor 11, ROM 12, and RAM 13 are connected to each other via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0129] Multiple components in the electronic device 10 are connected to the I / O interface 15, including an input unit 16, such as a keyboard, a mouse, etc.; an output unit 17, such as various types of displays, speakers, etc.; a storage unit 18, such as a magnetic disk, an optical disk, etc.; and a communication unit 19, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 19 allows the electronic device 10 to exchange information / data with other devices via a computer network such as the Internet and / or various telecommunication networks.

[0130] The processor 11 may be any general-purpose and / or specialized processing component with processing and computing capabilities. Some examples of the processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various specialized artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any appropriate processor, controller, microcontroller, etc. The processor 11 executes the various methods and processes described above, such as the SMS content generation method, namely:

[0131] Constructing a SMS template library using a first model based on SMS content data for at least one business scenario in at least one region; wherein the SMS templates in the SMS template library correspond to the set region and business scenario information;

[0132] Based on the SMS unsubscription information of each customer, a customer group information set with different customer group description information is generated based on the SMS unsubscription behavior classification rules; wherein the customer group description information includes the type and level of the customer;

[0133] Based on the customer group information set and the preset SMS scenario information library, a business scenario library is constructed through the second model; wherein the business scenario library includes the correspondence between customer group description information and SMS scenario information;

[0134] Based on the similarity between SMS scenario information and business scenario information, SMS business templates are screened from the SMS template library, and the SMS business templates and matching customer group description information are used to build an SMS business library;

[0135] When receiving SMS demand information, extract the target business scenario information, target region and target customer group description information from the SMS demand information;

[0136] Based on the target business scenario information and target area, the target SMS business template is selected from the SMS business library, and the target SMS content generated based on the target SMS business template and SMS demand information is pushed to each customer in the target area who matches the target customer description information.

[0137] In some embodiments, the text message content generation method can be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program can be loaded and / or installed on electronic device 10 via ROM 12 and / or communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the text message content generation method described above can be performed. Alternatively, in other embodiments, processor 11 can be configured to execute the text message content generation method in any other appropriate manner (e.g., via firmware).

[0138] Various embodiments of the systems and techniques described herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), system-on-chip systems (SOCs), programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments can include being implemented in one or more computer programs that are executable and / or interpreted on a programmable system comprising at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.

[0139] Computer programs for implementing the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when the computer program is executed by the processor, the functions / operations specified in the flowcharts and / or block diagrams are implemented. The computer program may be executed entirely on the machine, partially on the machine, as a stand-alone software package, partially on the machine and partially on a remote machine, or entirely on a remote machine or server.

[0140] In the context of the present invention, computer-readable storage media can be tangible media that can contain or store a computer program for use with an instruction execution system, device or equipment or used in combination with an instruction execution system, device or equipment. Computer-readable storage media can include but are not limited to electronic, magnetic, optical, electromagnetic, infrared or semiconductor systems, devices or equipment, or any suitable combination of the foregoing. Alternatively, computer-readable storage media can be machine-readable signal media. More specific examples of machine-readable storage media can include electrical connections based on one or more lines, portable computer disks, hard disks, random access memories (RAM), read-only memories (ROM), erasable programmable read-only memories (EPROM or flash memory), optical fibers, portable compact disk read-only memories (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the foregoing.

[0141] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user can provide input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).

[0142] The systems and techniques described herein can be implemented in a computing system that includes back-end components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes front-end components (e.g., a user computer with a graphical user interface or web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such back-end components, middleware components, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: a local area network (LAN), a wide area network (WAN), a blockchain network, and the Internet.

[0143] A computing system may include clients and servers. The clients and servers are typically remote from each other and typically interact via a communication network. This client-server relationship arises through computer programs running on the respective computers, creating a client-server relationship. The server may be a cloud server, also known as a cloud computing server or cloud host. This server is a hosting product within the cloud computing service ecosystem that addresses the management difficulties and limited scalability of traditional physical hosting and VPS services.

[0144] It should be understood that the various forms of the processes shown above can be used to reorder, add, or delete steps. For example, the steps described in the present invention can be performed in parallel, sequentially, or in a different order, as long as the desired results of the technical solution of the present invention can be achieved. This is not limited herein.

[0145] The above specific embodiments do not limit the scope of protection of the present invention. Those skilled in the art will appreciate that various modifications, combinations, sub-combinations, and substitutions may be made based on design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention are intended to be included within the scope of protection of the present invention.

Claims

1. A method for generating text message content, characterized in that: include: Constructing a SMS template library using a first model based on SMS content data for at least one business scenario in at least one region; wherein the SMS templates in the SMS template library correspond to the set region and business scenario information; Based on the SMS unsubscription information of each customer, a customer group information set with different customer group description information is generated based on the SMS unsubscription behavior classification rules; wherein the customer group description information includes the type and level of the customer; Based on the customer group information set and the preset SMS scenario information library, a business scenario library is constructed through the second model; wherein the business scenario library includes the correspondence between customer group description information and SMS scenario information; Based on the similarity between SMS scenario information and business scenario information, SMS business templates are screened from the SMS template library, and the SMS business templates and matching customer group description information are used to build an SMS business library; When receiving SMS demand information, extract the target business scenario information, target region and target customer group description information from the SMS demand information; Based on the target business scenario information and target area, the target SMS business template is selected from the SMS business library, and the target SMS content generated based on the target SMS business template and SMS demand information is pushed to each customer in the target area who matches the target customer description information.

2. The method according to claim 1, characterized in that Based on SMS content data of at least one business scenario in at least one region, a SMS template library is constructed using a first model, including: Obtaining SMS content data for at least one business scenario in at least one region, classifying and sorting the SMS content data by SMS type, and building at least one SMS type library based on the classification results; Input the SMS content data in the SMS type library into the first large model to parse the SMS content, format key information, obtain at least one type of SMS template and add the SMS template to the constructed SMS template library.

3. The method according to claim 2, characterized in that After formatting the key information, also include: Based on the parsing results of the SMS content, the business connections between the SMS content data in different SMS type libraries are analyzed through the first large model, at least one potential business scenario is constructed, and at least one type of SMS template matching the potential business scenario is generated.

4. The method according to claim 2, characterized in that After adding SMS templates to the built SMS template library, it also includes: The problem SMS templates in the SMS template library are screened out through the first model, and the problem SMS templates are deleted from the SMS template library.

5. The method according to claim 3, characterized in that Before building the business scenario library through the second model based on the customer group information collection and the preset SMS scenario information library, it also includes: Each potential business scenario is added to the SMS scenario information library.

6. The method according to claim 1, characterized in that The method further comprises: Whenever a preset update cycle is reached, the similarity between the SMS scenario information in the business scenario library and the business scenario information in the SMS template library is calculated, and SMS templates with a similarity below a threshold are selected for updating.

7. The method according to claim 2, characterized in that After the push is sent to each customer in the target region who matches the target customer description, it also includes: In response to an upload instruction of a customized SMS template obtained by modifying the SMS template based on the push result, when the customized SMS template does not contain target customer group information, the customized SMS template is added to an SMS type library that matches the target region and target business scenario; When target customer group information exists in a custom SMS template, the custom SMS template is added to an SMS service library that matches the target region, target business scenario, and target customer group information.

8. An electronic device, characterized in that: The electronic device comprises: at least one processor; and a memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor. The computer program is executed by the at least one processor so that the at least one processor can execute the method for generating text message content according to any one of claims 1 to 7.

9. A computer-readable storage medium, characterized in that The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a processor to implement the method for generating text message content according to any one of claims 1 to 7 when executed.

10. A computer program product, characterized in that The computer program product includes a computer program, and when the computer program is executed by a processor, the computer program implements the method for generating text message content according to any one of claims 1 to 7.

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