A product information processing method, device, equipment and program product

Abstract

This application discloses a product information processing method, apparatus, device, and program product. The method includes: in response to a product editing request, entering a modular tabbed product editing interface; in response to an editing operation on the product editing interface, acquiring input data; performing multi-level data verification processing on the input data to obtain target data; generating recommendation processing on the target data according to an artificial intelligence model; modifying the initial product information of the product editing interface based on the generated recommendation content; and determining the target product information. The embodiments of this application can improve the efficiency of product information processing and can be widely applied in the field of computer technology.

Description

Technical Field

[0001] This application relates to the field of computer technology, and in particular to a product information processing method, apparatus, equipment, and program product. Background Technology

[0002] With the rapid development of e-commerce, product management systems are becoming increasingly complex. In related technologies, product editing interfaces often concentrate all functions on a single page, resulting in cluttered interfaces, poor user experience, and low operational efficiency. Furthermore, when users need to manually input large amounts of product information, the system's efficiency is low and errors are prone to occur.

[0003] In summary, the technical problems existing in the relevant technologies need to be improved. Summary of the Invention

[0004] The main objective of this application is to provide a product information processing method, apparatus, device, and program product that can improve the efficiency of product information processing.

[0005] To achieve the above objectives, one aspect of this application proposes a product information processing method, the method comprising:

[0006] In response to the product editing request, enter the product editing interface of the modular label; In response to editing operations on the product editing interface, input data is obtained; The input data is subjected to multi-level data validation processing to obtain the target data; The target data is processed using an artificial intelligence model to generate recommendations. Based on the generated recommendations, the initial product information in the product editing interface is modified to determine the target product information.

[0007] In some embodiments, the step of responding to a product editing request and entering the product editing interface of the modular label includes the following steps: The product editing request is processed to identify the request intent. Based on the requested intent, multiple tags in the product editing interface are matched to obtain matching tags; Based on the matching tags, the tabs of the product editing interface are switched, and the user enters the product editing interface.

[0008] In some embodiments, performing multi-level data validation processing on the input data to obtain target data includes the following steps: The input data is subjected to data format validation processing to obtain initial validation data; The initial verification data is processed by business logic verification to obtain business verification data; Error messages and modifications are made to the business verification data to obtain the target data.

[0009] In some embodiments, performing business logic verification processing on the initial verification data to obtain business verification data includes the following steps: The product editing request is subjected to context analysis to obtain the business context; The editing area of ​​the product editing interface is determined based on the editing operation, and the editing logic corresponding to the editing area is obtained; Based on the editing logic and the business context, the initial verification data is processed for content verification to obtain the business verification data.

[0010] In some embodiments, the process of generating recommendations based on the target data using an artificial intelligence model includes the following steps: Based on the artificial intelligence model, the product name and industry characteristics of the target data are processed to generate a product description. The product description is optimized for search engines and keywords are generated to obtain search keywords.

[0011] In some embodiments, modifying the initial product information of the product editing interface based on generated recommended content to determine the target product information includes the following steps: Determine operation permissions based on the product editing request; Based on the operation permissions, data permission control processing is performed on the generated recommended content to obtain the permission control result; Based on the permission control results, the initial product information of the product editing interface is modified to determine the target product information.

[0012] In some embodiments, modifying the initial product information of the product editing interface based on the permission control result to determine the target product information includes the following steps: Based on the permission control results, the initial product information of the product editing interface is modified to obtain the modified information; Based on the state management library, the modified information is updated responsively and the state is synchronized to obtain the target product information.

[0013] To achieve the above objectives, another aspect of this application provides a product information processing apparatus, which is applied to the product information processing method described above, and the apparatus includes: The request and response module is used to respond to product editing requests and enter the product editing interface of the modular tab; The data acquisition module is used to acquire input data in response to editing operations on the product editing interface; The data verification module is used to perform multi-level data verification processing on the input data to obtain the target data; The recommendation generation module is used to generate recommendations based on the target data using an artificial intelligence model, modify the initial product information of the product editing interface based on the recommended content, and determine the target product information.

[0014] To achieve the above objectives, another aspect of this application provides an electronic device, which includes a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the method described above.

[0015] To achieve the above objectives, another aspect of the embodiments of this application proposes a computer-readable storage medium storing a computer program that, when executed by a processor, implements the methods described above.

[0016] The embodiments of this application include at least the following beneficial effects: This application provides a product information processing method, apparatus, device and program product. This solution responds to a product editing request and enters a modular tabbed product editing interface. The tabbed layout improves user experience and operational efficiency, and combined with intelligent artificial intelligence-assisted functions, it improves user work efficiency, thereby improving the processing efficiency of product information. Attached Figure Description

[0017] Figure 1 This is a schematic diagram of an implementation environment provided in the embodiments of this application; Figure 2 This is a flowchart of a product information processing method provided in an embodiment of this application; Figure 3 This is a schematic diagram of the structure of a product information processing device provided in an embodiment of this application; Figure 4 This is a schematic diagram of the hardware structure of the electronic device provided in the embodiments of this application. Detailed Implementation

[0018] To make the objectives, technical solutions, and advantages of this application clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of this application and are not intended to limit it. In the following description, when referring to the accompanying drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with those of this application; they are merely examples of apparatuses and methods consistent with some aspects of the embodiments of this application as detailed in the appended claims.

[0019] It is understood that the terms “first,” “second,” etc., used in this application may be used herein to describe various concepts, but unless otherwise stated, these concepts are not limited by these terms. These terms are only used to distinguish one concept from another. For example, without departing from the scope of the embodiments of this application, first information may also be referred to as second information, and similarly, second information may also be referred to as first information. Depending on the context, the words “if,” “when,” or “in response to a determination” as used herein may be interpreted as “when…” or “when…” or “in response to a determination.”

[0020] As used in this application, the terms "at least one", "multiple", "each", "any", etc., "at least one" includes one, two or more, "multiple" includes two or more, "each" refers to each of the corresponding multiples, and "any" refers to any one of the multiples.

[0021] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used herein is for the purpose of describing embodiments of this application only and is not intended to limit this application.

[0022] With the rapid development of e-commerce, the complexity of product management systems is increasing. Related product editing interfaces concentrate all functions on a single page, resulting in cluttered interfaces, poor user experience, and low operational efficiency. Furthermore, different product types (such as physical products, travel products, and hotel products) have different attributes and management requirements. The lack of a unified management framework in these systems necessitates the development of separate editing interfaces for each product type, increasing development costs and maintenance difficulty. Moreover, product information includes both globally applicable and product-specific data; the lack of an effective data separation mechanism makes data corruption and errors likely. When users need to manually input large amounts of product information, work efficiency is low and errors are prone to occur. Additionally, the rigid system architecture makes it difficult to support the addition of new product types and functional modules, limiting the system's application scope. The lack of real-time verification mechanisms means users only discover errors upon submission, increasing operational costs.

[0023] In view of this, this application provides a product information processing method, apparatus, device, and program product. This solution is based on modular tabs for editing product information and can be applied to the product management backend of e-commerce platforms. This application, by adopting a tab-based layout, can independently manage different types of product information. Furthermore, by responding to product editing requests, it performs real-time verification of input data, while providing intelligent error prompts and location, improving the accuracy of data editing. Moreover, this application automatically generates product descriptions through an artificial intelligence model, enhancing user work efficiency.

[0024] This application provides a product information processing method, relating to the field of computer technology. The product information processing method provided in this application can be applied to a terminal, a server, or software running on a terminal or server. In some embodiments, the terminal can be a smartphone, tablet, laptop, desktop computer, smart speaker, smartwatch, or in-vehicle terminal, but is not limited to these. The server can be configured as an independent physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server providing basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, CDN, and big data and artificial intelligence platforms. The server can also be a node server in a blockchain network. The software can be an application implementing the product information processing method, but is not limited to the above forms.

[0025] This application can be used in a wide variety of general-purpose or special-purpose computer system environments or configurations. Examples include: personal computers, server computers, handheld or portable devices, tablet devices, multiprocessor systems, microprocessor-based systems, set-top boxes, programmable consumer electronics devices, network PCs, minicomputers, mainframe computers, and distributed computing environments including any of the above systems or devices. This application can be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc., that perform specific tasks or implement specific abstract data types. This application can also be practiced in distributed computing environments where tasks are performed by remote processing devices connected via a communication network. In distributed computing environments, program modules can reside in local and remote computer storage media, including storage devices.

[0026] It should be noted that in all specific embodiments of this application, when processing data related to user identity or characteristics, such as user information, user behavior data, user historical data, and user location information, user permission or consent is obtained first. Furthermore, the collection, use, and processing of this data comply with relevant laws, regulations, and standards. In addition, when embodiments of this application require access to sensitive personal information of users, separate permission or consent from the user is obtained through pop-ups or redirection to confirmation pages. Only after obtaining the user's separate permission or consent is the necessary user-related data required for the proper functioning of these embodiments acquired.

[0027] Figure 1 This is a schematic diagram illustrating the implementation environment of a method provided in an embodiment of this application. (Refer to...) Figure 1 The main hardware and software components of this implementation environment include a terminal 101 and a server 102, which are communicatively connected. The method can be executed based on the interaction between the terminal 101 and the server 102. Furthermore, the terminal 101 and the server 102 can be nodes in a blockchain; this embodiment does not specifically limit this.

[0028] Figure 2 This is an optional flowchart of a product information processing method provided in an embodiment of this application. Figure 2 The method may include, but is not limited to, steps S201 to S204.

[0029] Step S201: In response to the product editing request, enter the product editing interface of the modular label; Step S202: In response to the editing operation on the product editing interface, input data is obtained; Step S203: Perform multi-level data verification processing on the input data to obtain the target data; Step S204: Generate recommendations based on the target data using an artificial intelligence model, modify the initial product information of the product editing interface based on the generated recommendations, and determine the target product information.

[0030] Steps S201 to S204, as illustrated in this embodiment, involve entering a modular tabbed product editing interface in response to a product editing request. This product editing request is a user-initiated request to edit product information. The product editing interface is a modular tab component used to display different types of product editing interfaces. Furthermore, in response to editing operations on the product editing interface, user input data can be obtained. This embodiment also performs multi-level data validation on the input data, enabling real-time data validation during user input. Based on an artificial intelligence model, recommendations are generated from the validated target data, automatically generating selling point descriptions based on the product name and providing search engine optimization (SEO) keyword suggestions. Then, based on the content generated by the model, the initial product information in the product editing interface is modified to determine the edited target product information.

[0031] One of the above technical solutions has the following advantages or beneficial effects: The embodiments of this application improve the efficiency of product information processing by editing product information through the product editing interface of the modular tab page, and by combining data verification and artificial intelligence generation functions. It has the characteristics of good user experience, low development cost, strong maintainability and good scalability, and is suitable for the product management backend of various e-commerce platforms.

[0032] In step S201 of some embodiments, the step of entering the product editing interface of the modular label in response to the product editing request includes the following steps: The product editing request is processed to identify the request intent. Based on the requested intent, multiple tags in the product editing interface are matched to obtain matching tags; Based on the matching tags, the tabs of the product editing interface are switched, and the user enters the product editing interface.

[0033] In this embodiment, the request intent can be obtained by performing intent recognition processing on the product editing request. Specifically, multi-source fusion and standardization are performed on API parameters, user operation sequences, and contextual features in the product editing request to extract multi-dimensional feature vectors such as user, product, operation type, and time environment. Then, deep semantic reasoning is performed using a deep learning model trained on business knowledge graphs and historical behavior patterns to identify the core business intent of the request. The identified intent is then compiled into a structured intent descriptor that the rule engine can understand. For example, if the product editing request is for editing product information of a target product, the identified request intent is "editing product information of the target product." This embodiment also performs matching processing on multiple tags in the product editing interface based on the request intent to obtain matching tags. These matching tags allow switching between tabs in the product editing interface to access the tab page for the specified product information. The product editing interface is a modular tab component used to display different types of product information. The tag page can include a basic information module for managing basic product information; a price setting module for managing product pricing strategies; a product specification module for managing product specifications and inventory; a detailed description module for managing detailed product descriptions; a coupon code setting module for managing coupon code information for virtual products; and other settings modules for managing product SEO, permissions, and delivery settings. This embodiment of the application improves user experience and operational efficiency by providing a modular and extensible product editing interface.

[0034] In some embodiments, performing multi-level data validation processing on the input data to obtain target data includes the following steps: The input data is subjected to data format validation processing to obtain initial validation data; The initial verification data is processed by business logic verification to obtain business verification data; Error messages and modifications are made to the business verification data to obtain the target data.

[0035] In this embodiment, by performing real-time data verification during user input, it is possible to verify whether the data conforms to business logic and provide intelligent error prompts and location functions, thereby determining the target data after verification. This embodiment can verify whether the input data format meets the requirements. For example, when the format for a specific character is Chinese input, the data format of the input data is verified to determine if it is Chinese input. When the data format is met, initial verification data is obtained. Then, based on the business logic of the target product to be edited, the initial verification data undergoes business logic verification. When verification passes, the target data can be directly obtained. This embodiment can also prompt and correct errors during the verification process. For example, during verification, error prompts are given for non-Chinese characters in the input data, and non-Chinese characters are deleted, thereby obtaining the target data after verification. This embodiment, through a real-time verification mechanism, can detect errors during data input, reducing subsequent operational costs.

[0036] In some embodiments, performing business logic verification processing on the initial verification data to obtain business verification data includes the following steps: The product editing request is subjected to context analysis to obtain the business context; The editing area of ​​the product editing interface is determined based on the editing operation, and the editing logic corresponding to the editing area is obtained; Based on the editing logic and the business context, the initial verification data is processed for content verification to obtain the business verification data.

[0037] In this embodiment, by performing context analysis on product editing requests, raw signals related to the current request can be collected in real time from multiple data sources in parallel. This raw data is then transformed into features with business significance. By assembling all features according to a predefined format, a structured context object is formed, resulting in the business context. Furthermore, the editing area of ​​the product editing interface is determined based on the editing operation, such as identifying the text box to be edited through a click operation, and obtaining the corresponding editing logic within that text box, such as the size range of a certain data item. By combining the editing logic and the business context, the specific content of the initial verification data can be verified, thereby obtaining business verification data.

[0038] In some embodiments, the process of generating recommendations based on the target data using an artificial intelligence model includes the following steps: Based on the artificial intelligence model, the product name and industry characteristics of the target data are processed to generate a product description. The product description is optimized for search engines and keywords are generated to obtain search keywords.

[0039] In this embodiment, an artificial intelligence model is used to process the product name and industry characteristics of the target data to generate a corresponding product description. A pre-trained language model combined with a domain knowledge graph can be used to analyze the core functions, materials, technologies, and brands in the product name. Simultaneously, industry characteristics are mapped to a standardized industry knowledge framework. A multi-task learning framework is employed to simultaneously perform selling point mining and description generation. The model analyzes the product from multiple dimensions, extracting functional selling points based on product parameters, such as performance indicators and technical parameters. It also combines user reviews and competitor analysis to generate experiential selling points, resulting in a product description. Furthermore, natural language processing technology is used to extract core terms from the product description. By combining and expanding these terms with a preset search intent template, a seed keyword library is generated. Then, using keyword research tools and GPT-like models, synonym replacement, scenario association, and long-tail keyword optimization are performed based on the seed words. Candidate words with high search volume and moderate competition are selected to generate corresponding search keywords.

[0040] In some embodiments, modifying the initial product information of the product editing interface based on generated recommended content to determine the target product information includes the following steps: Determine operation permissions based on the product editing request; Based on the operation permissions, data permission control processing is performed on the generated recommended content to obtain the permission control result; Based on the permission control results, the initial product information of the product editing interface is modified to determine the target product information.

[0041] In this embodiment, the user's access permissions can be determined based on the product editing request. For example, the user information can be obtained through the product editing request, and the user's access permissions can be searched in the system based on the user information, such as controlling the user's access permissions to specific functions and controlling the user's access permissions to specific data. Based on these access permissions, data permission control processing can be performed on the generated recommended content, that is, it can be determined whether the generated recommended content meets the corresponding access permissions or operation permissions to obtain the permission control result. If the permission control result is that the permissions are met, the initial product information on the product editing interface is modified to determine the target product information. If the permissions are not met, the user's operation behavior is recorded and the corresponding operation behavior is sent to the administrator for review. After the administrator approves, the corresponding initial product information can be modified to obtain the target product information.

[0042] In some embodiments, modifying the initial product information of the product editing interface based on the permission control result to determine the target product information includes the following steps: Based on the permission control results, the initial product information of the product editing interface is modified to obtain the modified information; Based on the state management library, the modified information is updated responsively and the state is synchronized to obtain the target product information.

[0043] In this embodiment, when the access control result is approved, the initial product information on the product editing interface is updated to the corresponding edited information, thereby obtaining the modified information. This embodiment modifies information on the corresponding tabs. The modular tab components are implemented using the Vue.js framework. Each tab is an independent Vue component, and each tab component implements independent data management and event handling, achieving communication between components through an event bus mechanism. The system uses the Vuex framework to implement the state management library, managing state modularly. A blacklist mechanism is also used to prevent accidental modification of critical fields. This state management library divides product information into globally common fields and product-specific fields. Globally common fields include product name, selling point description, product code, product image, product parameters, main image video, and product category; product-specific fields are stored in isolation according to product type.

[0044] The solutions of this application embodiment will be described in detail and explained below with reference to specific application examples: This application embodiment applies to the product management backend of an e-commerce platform. The system adopts a layered architecture design, including a user interface layer, a business logic layer, an intelligent service layer, a data access layer, and an external integration layer. The user interface layer uses modular tab components to provide an intuitive operation interface. Each tab corresponds to a functional module, and users can switch between different editing interfaces by clicking the tabs. The business logic layer implements an intelligent state management system, responsible for managing global data and product-specific data. The system uses the Vuex state management framework to achieve reactive data updates and state synchronization. The intelligent service layer integrates AI-assisted functions, providing intelligent product information generation and optimization suggestions. The system implements intelligent functions by calling external AI service interfaces. The data access layer manages data storage and access, supporting unified access to multiple data sources. The system uses an Object Relational Mapping (ORM) framework to implement object-oriented data operations. The external integration layer integrates with third-party systems, supporting data import and export and data synchronization between systems. This application embodiment receives a product editing request, enters the corresponding modular tab's product editing interface, and obtains the corresponding input data by performing editing operations on the product editing interface. The system utilizes a multi-layered data validation and recommendation generation mechanism through its business logic layer and intelligent service layer to modify the initial product information in the product editing interface, ultimately yielding the target product information. The product editing interface displays six tabs. The Basic Information, Details, and Others tabs are general-purpose. Basic Information allows editing of product information such as product name, selling points, product catalog, and product images. Details allows users to edit the product's description, supporting rich text editing, text, image, and video insertion, and formatting. Others tabs support extended functionalities such as delivery methods, listing settings (custom listing and delisting times), and transaction settings. Product Specifications is a tab specific to physical products, supporting multiple specification combinations and setting corresponding prices and inventory information. Coupon Codes are specific to electronic coupons. Prices are specific to travel products. The system uses the Vuex framework for intelligent state management, managing states through modularization. A blacklist mechanism prevents accidental modification of critical fields. A multi-layered validation mechanism is also implemented through a data validation system. Real-time Validation: The system validates data format and content in real time during user input, promptly displaying error messages. Required Field Validation: The system checks if required fields are filled in; unfilled fields display error messages. Format Validation: The system validates data format for compliance with requirements, such as email address or phone number formats. Business Validation: The system validates data for compliance with business logic, such as prices not being negative or inventory not exceeding limits. Error Handling: The system provides intelligent error prompts, automatically locating errors and supporting scrolling to the error field. The system sends the product name to the AI ​​service, which generates appropriate selling point descriptions based on the product name and industry characteristics.After a user enters a product name and clicks the AI ​​robot icon, the front-end initiates a request. The AI ​​model then outputs a suitable three-day description of the product's selling points based on the product name. Users can also click "Regenerate" to change the description if they feel it's unsuitable. The AI ​​service analyzes product information and recommends relevant SEO keywords to help improve the product's ranking in search engines. Simultaneously, the access control system implements multi-level permission management. By determining the entry point for editing products and verifying the permissions of the currently logged-in role, the system grants corresponding editing pop-up permissions, allowing either editing or viewing only. Role-based permission management: The system defines different user roles, such as platform administrators and merchant administrators, each with different operational permissions. Platform administrators can view merchant products but are not allowed to edit them. Data access control: The system controls user access permissions to specific data; for example, some users can only view information about products they are responsible for. If a user does not have permission to view a product, they will be prompted that their permissions are insufficient and will not be allowed to view the product pop-up content. Read-only mode support: The system supports a read-only viewing mode, allowing users to view product information but not perform editing operations. Operation log recording: The system records all user operations, including operation time, operation content, operation results, etc., to facilitate auditing and troubleshooting.

[0045] Please see Figure 3 This application also provides a product information processing apparatus that can implement the above-described product information processing method. The apparatus includes: The request response module 301 is used to respond to a product editing request and enter the product editing interface of the modular label; The data acquisition module 302 is used to acquire input data in response to the editing operation of the product editing interface; Data verification module 303 is used to perform multi-level data verification processing on the input data to obtain target data; The recommendation generation module 304 is used to generate recommendations based on the target data using an artificial intelligence model, modify the initial product information of the product editing interface based on the recommended content, and determine the target product information.

[0046] It is understood that the content of the above method embodiments is applicable to the present device embodiments. The specific functions implemented by the present device embodiments are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0047] This application also provides an electronic device, which includes a memory and a processor. The memory stores a computer program, and the processor executes the computer program to implement the above-described method. This electronic device can be any smart terminal, including tablet computers, in-vehicle computers, etc.

[0048] It is understood that the content of the above method embodiments is applicable to this device embodiment. The specific functions implemented by this device embodiment are the same as those of the above method embodiments, and the beneficial effects achieved are also the same as those achieved by the above method embodiments.

[0049] Please see Figure 4 , Figure 4 The hardware structure of an electronic device according to another embodiment is illustrated. The electronic device includes: The processor 401 can be implemented using a general-purpose CPU (Central Processing Unit), microprocessor, application-specific integrated circuit (ASIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided in the embodiments of this application. The memory 402 can be implemented as a read-only memory (ROM), a static storage device, a dynamic storage device, or a random access memory (RAM). The memory 402 can store the operating system and other applications. When the technical solutions provided in the embodiments of this specification are implemented through software or firmware, the relevant program code is stored in the memory 402 and is called and executed by the processor 401. Input / output interface 403 is used to implement information input and output; The communication interface 404 is used to enable communication and interaction between this device and other devices. Communication can be achieved through wired means (such as USB, Ethernet cable, etc.) or wireless means (such as mobile network, WIFI, Bluetooth, etc.). Bus 405 transmits information between various components of the device (e.g., processor 401, memory 402, input / output interface 403, and communication interface 404); The processor 401, memory 402, input / output interface 403 and communication interface 404 are connected to each other within the device via bus 405.

[0050] This application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described method.

[0051] It is understood that the content of the above method embodiments is applicable to this storage medium embodiment. The specific functions implemented in this storage medium embodiment are the same as those in the above method embodiments, and the beneficial effects achieved are also the same as those achieved in the above method embodiments.

[0052] Memory, as a non-transitory computer-readable storage medium, can be used to store non-transitory software programs and non-transitory computer-executable programs. Furthermore, memory may include high-speed random access memory, and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid-state storage device. In some embodiments, memory may optionally include memory remotely located relative to the processor, and these remote memories can be connected to the processor via a network. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.

[0053] The embodiments described in this application are for the purpose of more clearly illustrating the technical solutions of the embodiments of this application, and do not constitute a limitation on the technical solutions provided by the embodiments of this application. As those skilled in the art will know, with the evolution of technology and the emergence of new application scenarios, the technical solutions provided by the embodiments of this application are also applicable to similar technical problems.

[0054] Those skilled in the art will understand that the technical solutions shown in the figures do not constitute a limitation on the embodiments of this application, and may include more or fewer steps than shown, or combine certain steps, or different steps.

[0055] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0056] Those skilled in the art will understand that all or some of the steps in the methods disclosed above, as well as the functional modules / units in the systems and devices, can be implemented as software, firmware, hardware, or suitable combinations thereof.

[0057] The terms “first,” “second,” “third,” “fourth,” etc. (if present) in the specification and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms “comprising” and “having,” and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0058] It should be understood that in this application, "at least one (item)" means one or more, and "more than" means two or more. "And / or" is used to describe the relationship between related objects, indicating that three relationships can exist. For example, "A and / or B" can represent three cases: only A exists, only B exists, and both A and B exist simultaneously, where A and B can be singular or plural. The character " / " generally indicates that the preceding and following related objects are in an "or" relationship. "At least one (item) of the following" or similar expressions refer to any combination of these items, including any combination of single or plural items. For example, at least one (item) of a, b, or c can represent: a, b, c, "a and b", "a and c", "b and c", or "a and b and c", where a, b, and c can be single or multiple.

[0059] In the several embodiments provided in this application, it should be understood that the disclosed apparatus and methods can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of the units described above is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0060] The units described above as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0061] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0062] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes multiple instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this application. The aforementioned storage medium includes various media capable of storing programs, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0063] The preferred embodiments of the present application have been described above with reference to the accompanying drawings, but this does not limit the scope of the claims of the present application. Any modifications, equivalent substitutions, and improvements made by those skilled in the art without departing from the scope and substance of the embodiments of the present application shall be within the scope of the claims of the present application.

Claims

1. A product information processing method, characterized in that, The method includes the following steps: In response to the product editing request, enter the product editing interface of the modular label; In response to editing operations on the product editing interface, input data is obtained; The input data is subjected to multi-level data validation processing to obtain the target data; The target data is processed using an artificial intelligence model to generate recommendations. Based on the generated recommendations, the initial product information in the product editing interface is modified to determine the target product information.

2. The method according to claim 1, characterized in that, The process of responding to a product editing request and entering the product editing interface of the modular label includes the following steps: The product editing request is processed to identify the request intent. Based on the requested intent, multiple tags in the product editing interface are matched to obtain matching tags; Based on the matching tags, the tabs of the product editing interface are switched, and the user enters the product editing interface.

3. The method according to claim 1, characterized in that, The process of performing multi-level data validation on the input data to obtain the target data includes the following steps: The input data is subjected to data format validation processing to obtain initial validation data; The initial verification data is processed by business logic verification to obtain business verification data; Error messages and modifications are made to the business verification data to obtain the target data.

4. The method according to claim 3, characterized in that, The process of performing business logic verification on the initial verification data to obtain business verification data includes the following steps: The product editing request is subjected to context analysis to obtain the business context; The editing area of ​​the product editing interface is determined based on the editing operation, and the editing logic corresponding to the editing area is obtained; Based on the editing logic and the business context, the initial verification data is processed for content verification to obtain the business verification data.

5. The method according to claim 1, characterized in that, The process of generating recommendations based on the target data using an artificial intelligence model includes the following steps: Based on the artificial intelligence model, the product name and industry characteristics of the target data are processed to generate a product description. The product description is optimized for search engines and keywords are generated to obtain search keywords.

6. The method according to claim 5, characterized in that, The process of modifying the initial product information on the product editing interface based on generated recommended content to determine the target product information includes the following steps: Determine operation permissions based on the product editing request; Based on the operation permissions, data permission control processing is performed on the generated recommended content to obtain the permission control result; Based on the permission control results, the initial product information of the product editing interface is modified to determine the target product information.

7. The method according to claim 6, characterized in that, Modifying the initial product information of the product editing interface based on the permission control result and determining the target product information includes the following steps: Based on the permission control results, the initial product information of the product editing interface is modified to obtain the modified information; Based on the state management library, the modified information is updated responsively and the state is synchronized to obtain the target product information.

8. A product information processing device, characterized in that, The apparatus is used in the method as described in any one of claims 1 to 7, the apparatus comprising: The request and response module is used to respond to product editing requests and enter the product editing interface of the modular tab; The data acquisition module is used to acquire input data in response to editing operations on the product editing interface; The data verification module is used to perform multi-level data verification processing on the input data to obtain the target data; The recommendation generation module is used to generate recommendations based on the target data using an artificial intelligence model, modify the initial product information of the product editing interface based on the recommended content, and determine the target product information.

9. An electronic device, characterized in that, The electronic device includes a memory and a processor, the memory storing a computer program, and the processor executing the computer program to implement the method according to any one of claims 1 to 7.

10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the method of any one of claims 1 to 7.

Images