Product nameplate information configuration and verification method, equipment and medium
By analyzing and mapping nameplate information, nameplate information that meets the standards is generated, which solves the problems of entry errors and inconsistent formats, and realizes the accuracy and consistency management of nameplate information.
Patent Information
- Application Number
- CN202510381717.3
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-03-28
- Publication Date
- 2025-07-04
AI Technical Summary
In the prior art, product nameplate information entry is prone to errors, lack of effective information correlation analysis, resulting in inaccurate information, different formats and contents, making it difficult to meet the information needs of different products, and bringing difficulties to enterprise management and traceability.
By obtaining nameplate information items, analyzing the information association status, and mapping them into the pre-constructed information architecture, identifying the information item association, obtaining matching format constraints, and generating nameplate information that meets the standards.
It improves the accuracy and reliability of nameplate information, achieves consistency in information processing, and supports enterprise management and traceability.
Smart Images
Figure CN120256485A_ABST
Abstract
Description
Technical Field
[0001] This application relates to the technical field of product nameplates, and particularly to a method, device, and medium for configuring and verifying product nameplate information. Background Art
[0002] A product nameplate is a permanent identifier fixed on a product or device, used to clearly display key information to help users, maintenance personnel, and regulatory agencies quickly understand the product characteristics.
[0003] In related technologies, errors are prone to occur when entering nameplate information, such as incorrect or inaccurate filling of information such as product models and configuration parameters. Moreover, due to the lack of effective information correlation analysis, it is difficult to discover logical problems between information, resulting in the nameplate information not accurately reflecting the actual situation of the product.
[0004] Different products may be handled by different personnel for nameplate information. Due to the lack of unified standards and specifications, the formats, contents, and expressions of nameplate information vary. This brings difficulties to the enterprise's information management and product traceability. With the continuous increase in the types of products and the diversification of application scenarios, it is difficult for the nameplate information processing method to flexibly respond. Different products have different information requirements and format requirements, and the generation and configuration of nameplate information in related technologies are difficult to meet the usage requirements. Summary of the Invention
[0005] The present invention provides a method for configuring and verifying product nameplate information, which reduces the error rate of nameplate information, improves the accuracy and reliability of nameplate information; and realizes the consistency of nameplate information processing, facilitating the enterprise's nameplate information management and product traceability.
[0006] The method includes: Obtain the nameplate items of the nameplate information to be processed, and read the nameplate writing information in the nameplate items; Perform nameplate information parsing on the nameplate writing information to obtain the nameplate information association status; Obtain the pre-constructed nameplate information architecture, and map the nameplate information association status into the nameplate information architecture; In the nameplate information architecture, based on the nameplate information association status, identify the information item association between the nameplate writing information and the knowledge nodes of the nameplate information architecture through information logical relationships to obtain an information item association representation; Obtain the nameplate format corresponding to the nameplate information to be processed from the nameplate item, and obtain the nameplate format constraint conditions matching the nameplate format in the preset nameplate format definition library; Generate nameplate information matching the nameplate item based on the information item association representation and the nameplate format constraint conditions.
[0007] It should be further noted that the step of obtaining the pre-constructed nameplate information architecture and mapping the nameplate information association status to the nameplate information architecture specifically includes: Construct a nameplate mapping rule and create multiple product keywords within the nameplate mapping rule; Identify the nameplate items of the nameplate information architecture and pair the nameplate items of the nameplate information architecture with the product keywords within the nameplate mapping rule to obtain a knowledge feature pairing result; According to the knowledge feature pairing result, import the nameplate information architecture into the nameplate mapping rule.
[0008] It should be further noted that the step of identifying the information item association between the nameplate writing information and the knowledge nodes of the nameplate information architecture based on the nameplate information association status through information logical relationships to obtain an information item association representation specifically includes: Perform nameplate information parsing on the nameplate items of the nameplate information architecture to obtain the manifestation of the product attributes of the nameplate items; Based on the nameplate information association status and the manifestation of the product attributes of the nameplate items, determine whether there is an information item association between the nameplate writing information and the nameplate items; If there is an information item association between the nameplate writing information and the nameplate items, extract the information item association features and generate an information item association manifestation.
[0009] It should be further noted that the step of determining whether there is an information item association between the nameplate writing information and the nameplate items based on the nameplate information association status and the manifestation of the product attributes of the nameplate items specifically includes: Calculate the nameplate information association similarity between the nameplate information association status and the manifestation of the product attributes of the nameplate items; Compare the nameplate information association similarity with a preset similarity threshold; When the nameplate information association similarity is greater than or equal to the similarity threshold, it is determined that there is an information item association between the nameplate writing information and the nameplate items; When the nameplate information association similarity is less than the similarity threshold, it is determined that there is no information item association between the nameplate writing information and the nameplate items.
[0010] It should be further noted that the step of generating nameplate information matching the nameplate items based on the information item association representation and the nameplate format constraint conditions specifically includes: Input the information item association manifestation and the nameplate format constraint conditions into a pre-trained nameplate analysis model; Traverse the nameplate information library of the nameplate analysis model to identify the target nameplate information matching the information item association manifestation; Combine the target nameplate information according to the nameplate format constraint conditions to obtain the nameplate information matching the nameplate items.
[0011] Further, it should be noted that after generating the nameplate information matching the nameplate items, it further includes: Obtain the product nameplate image, and use the product recognition module to parse the keywords of the product nameplate image to obtain the nameplate information of the product nameplate image; According to the nameplate information, use the product attribute information extraction model to extract information from the product nameplate image, and extract the key product information of the product nameplate image; Obtain the product preset data corresponding to the product nameplate image, and compare and verify the key product information with the product preset data; If the comparison and verification pass, it is determined that the product nameplate image passes the verification, and the nameplate body corresponding to the product nameplate image is determined to be in a verified state.
[0012] Further, it should be noted that according to the nameplate information, using the product attribute information extraction model to extract information from the product nameplate image, and extracting the key product information of the product nameplate image includes: According to the nameplate information, use the product attribute information extraction model to detect the nameplate items of the product nameplate image to obtain the key nameplate item information; Use the nameplate analysis model of the product attribute information extraction model to process the key nameplate item information, and extract the key nameplate information of the key nameplate item information; Use the structured processing module of the product attribute information extraction model to convert the format of the key nameplate information according to the nameplate format to obtain the key product information of the product nameplate image.
[0013] Further, it should be noted that the step of comparing and verifying the key product information with the product preset data specifically includes: Structurally process the product preset data according to a predefined structure template to obtain the structured product preset data; Compare and verify the key product information with the information in the same identification position of the product preset data; If the comparison and verification fails, mark the product nameplate image as an abnormal product image.
[0014] According to another embodiment of the present application, an electronic device is provided, including a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the program, the steps of the product nameplate information configuration and verification method are implemented.
[0015] According to still another embodiment of the present application, a storage medium is further provided, on which a computer program is stored. When the computer program is executed by a processor, the steps of the product nameplate information configuration and verification method are implemented.
[0016] From the above technical solutions, it can be seen that the present invention has the following advantages: The product nameplate information configuration and verification method provided by this application parses the information written on the nameplate to obtain the associated status of the nameplate information, and identifies the association of information items based on the information logic relationship in the nameplate information architecture. At the same time, after obtaining the product nameplate image, a product recognition module and a product attribute information extraction model are used for information extraction, and compared and verified with the preset product data to improve the accuracy of the nameplate information.
[0017] This application constructs a nameplate information architecture, defines unified nameplate mapping rules and product keywords, and standardizes the processing process of nameplate information. By mapping the associated status of nameplate information into the nameplate information architecture and obtaining the matching nameplate format constraint conditions in the preset nameplate format definition library, the consistency of the nameplate information in format and content is ensured. This application realizes the full-automatic processing flow from nameplate information acquisition, parsing, mapping to generation and verification. Constructing a flexible nameplate information architecture and a configurable nameplate format definition library can be adjusted and expanded according to the characteristics and requirements of different products. It effectively reduces the error rate of nameplate information, improves the accuracy and reliability of information; realizes the standardization and consistency of nameplate information processing, and is convenient for users to manage product information and trace products. Brief Description of the Drawings
[0018] In order to more clearly illustrate the technical solutions of the present invention, the accompanying drawings required for description will be briefly introduced below. Obviously, the accompanying drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.
[0019] Figure 1 It is a flowchart of the product nameplate information configuration and verification method; Figure 2 It is a flowchart of an embodiment of the product nameplate information configuration and verification method; Figure 3 It is a schematic diagram of an electronic device. Detailed Embodiments
[0020] The following will detail the specific steps of the product nameplate information configuration and verification method. For the purpose of illustration rather than limitation, specific details such as specific system structures and technologies are proposed to thoroughly understand the embodiments of this application. However, those skilled in the art should clearly understand that this application can also be implemented in other embodiments without these specific details.
[0021] It should be understood that when used in the specification of this application, the term "comprising" indicates the presence of the described features, wholes, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components and / or their combinations. The terms "comprising", "including", "having" and their variants all mean "including but not limited to", unless otherwise specifically emphasized in other ways.
[0022] For the convenience of clearly describing the technical solutions of this application, terms such as "first" and "second" are used to distinguish the same items or similar items with basically the same functions and roles. Those skilled in the art can understand that the terms "first", "second", etc. do not limit the quantity and execution order, and the terms "first", "second", etc. do not necessarily limit being different.
[0023] The statements such as "an embodiment" or "some embodiments" described in this application mean that the specific features, structures or characteristics described in the embodiment are included in one or more embodiments of this application. Thus, the statements such as "in an embodiment", "in some embodiments", "in other some embodiments", "in still other embodiments" and the like that appear in different parts of this application do not necessarily refer to the same embodiment, but mean "one or more but not all embodiments", unless otherwise specifically emphasized in other ways.
[0024] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts belong to the scope of protection of the present invention.
[0025] Please refer to Figure 1 The following is a flowchart of the method for configuring and verifying product nameplate information in a specific embodiment. The method includes: S101, obtain the nameplate items of the nameplate information to be processed, and read the nameplate writing information in the nameplate items.
[0026] In some embodiments, the nameplate information to be processed is a set of relevant data that needs to be filled in, adjusted or verified on the product nameplate. The nameplate items are the specific categories that make up the nameplate information, such as product model, production date, production batch, etc. By locating the position of the nameplate information to be processed and according to the preset reading rules, the information that has been written or to be written in each nameplate item is read out.
[0027] Exemplarily, the nameplate information comes from sources such as Excel spreadsheets, databases, API interfaces, or manual entry. Preprocessing is performed on the original nameplate information, such as deduplication, trimming whitespace, and unifying case. For example, a server nameplate may contain "SERIAL-NUMBER: SN2023-ABC123", and "SN2023-ABC123" needs to be extracted as a valid field.
[0028] Optionally, during the reading process, preliminary data format verification is performed to ensure that the information read conforms to the preset data type requirements. For example, the product model should be a text string, and the production date should conform to a specific date format, etc.
[0029] S102, Parse the nameplate write information to obtain the nameplate information association status.
[0030] In some embodiments, after obtaining the nameplate write information, the system enters the information parsing phase. The parsing work starts with extracting keywords. The keyword extraction algorithm will identify key words from the nameplate write information according to pre-set language rules, product domain term libraries, and common grammar structures.
[0031] Exemplarily, if the nameplate write information is "A certain server, model FWQA-100, produced in May 2023", the keywords may be "server", "FWQA-100", "January 2021". After extracting the keywords, natural language processing techniques and product-specific semantic understanding models are used to deeply analyze the keywords. For different product types, there will be corresponding product type knowledge bases in the system, which contain various specifications, common expression methods, and semantic associations of the nameplate information of this type of product.
[0032] For the keyword "FWQA-100", search for the matching model information in the server product knowledge base, understand the relevant semantic descriptions of this model in terms of performance parameters, configuration characteristics, etc., and at the same time analyze its position and relationship in the entire server product model system. In this way, the meaning of each keyword and its usage in different product types can be understood, and finally the nameplate information association status is obtained. The association status includes information such as the semantic association degree between keywords and the associated product attribute categories.
[0033] Optionally, use NLP technology to identify core entities. For example, extract "Intel Xeon Gold 6248R" as the processor model from "CPU: Intel Xeon Gold 6248R".
[0034] S103, Obtain the pre-constructed nameplate information architecture and map the nameplate information association status into the nameplate information architecture.
[0035] In this embodiment, the pre-constructed nameplate information architecture is a structured system that defines the composition structure of product nameplate information, the relationships between its various parts, and the mapping to the actual attributes of the product. The nameplate information architecture is constructed based on product design standards, industry specifications, and the data management requirements within the enterprise. After obtaining this pre-constructed nameplate information architecture, the nameplate information association status obtained in the previous step is matched and corresponded to each element in the nameplate information architecture through a preset mapping algorithm.
[0036] Exemplarily speaking, in the nameplate information architecture of server products, the product model is classified into the "product identification" category, and the production date is classified into the "production information" category. After obtaining the nameplate information association status regarding the server model "FWQA-100" and the production date "January 2021", they are respectively mapped to the corresponding "product identification" and "production information" categories in the nameplate information architecture, establishing a corresponding relationship from the specific information association status to the architecture system.
[0037] S104. In the nameplate information architecture, based on the nameplate information association status, identify the information item association between the nameplate writing information and the nameplate items in the nameplate information architecture through information logic relationships, and obtain the information item association manifestation.
[0038] In this embodiment, in the established nameplate information architecture, based on the obtained nameplate information association status, identify the information item association between the nameplate writing information and the nameplate items in the nameplate information architecture through pre-defined information logic relationship rules.
[0039] The information logic relationship rules of this embodiment include information matching rules, attribute inheritance rules, hierarchical relationship rules, etc.
[0040] Exemplarily speaking, for server products, it is stipulated in the nameplate information architecture that there is a logical association based on product configuration between the "product model" and the "processor model" because a server model usually comes with a specific processor model. When the system processes the nameplate writing information with the server model "FWQA-100" and knows from its knowledge base that this model usually comes with the "Intel Xeon E5 - 2620 v4" processor, if keywords related to this processor model appear in the subsequent nameplate writing information, the information item association will be identified according to the pre-set information logic relationship. Through the identification process, the information item association manifestation is obtained.
[0041] S105. Obtain the nameplate format corresponding to the to-be-processed nameplate information from the nameplate item, and obtain the nameplate format constraint conditions matching the nameplate format in the preset nameplate format definition library.
[0042] In this embodiment, according to the description in the nameplate item, by matching with a pre-set format mapping table or format parsing algorithm, the nameplate format information expected by the user is obtained.
[0043] Exemplarily speaking, for server products, if the nameplate information of the server is mainly used for the online product display platform, then the nameplate format can be made concise to highlight key information such as product model, main performance parameters, etc., and the layout should conform to the visual design specifications of the platform.
[0044] After obtaining the nameplate format information in this embodiment, a search is performed in the pre-set nameplate format definition library. A large number of format constraint conditions matching different nameplate formats are stored in the nameplate format definition library, and the conditions include font requirements, layout requirements, character limitations, etc.
[0045] For example, it involves font type, font size requirements, the arrangement order of each information item, spacing requirements, and the maximum number of characters for each information item.
[0046] In this embodiment, according to the obtained nameplate format information, the nameplate format constraint conditions matching it are extracted from the nameplate format definition library to prepare for generating nameplate information that meets the format requirements later.
[0047] S106. Based on the information item association manifestation and the nameplate format constraint conditions, generate nameplate information that matches the nameplate item.
[0048] In this embodiment, based on the information item association manifestation and the nameplate format constraint conditions obtained previously, nameplate information that matches the nameplate item is generated. According to the relationships between the various information items determined in the information item association manifestation, and in accordance with the format requirements specified by the nameplate format constraint conditions, the nameplate information is reorganized and arranged.
[0049] Exemplarily speaking, for server products, assuming that the information item association manifestation indicates that there is a close association between the product model "FWQA-100" and information such as the processor model "Intel Xeon E5 - 2620 v4" and the memory capacity "32GB", and the nameplate format constraint conditions require that the product model be placed at the top, with the font being Arial 14 bold, and the information such as the processor model and memory capacity be arranged in sequence below, with the font being Arial 12 regular. Then according to the requirements, nameplate information in the following format is generated. Product model: FWQA-100. Processor model: Intel Xeon E5 - 2620 v4. Memory capacity: 32GB. During the generation process, verification and optimization can also be performed to ensure that the generated nameplate information is complete, accurate, and meets all format and association requirements.
[0050] The product nameplate information configuration and verification method involved in this application can effectively avoid the problem of inaccurate nameplate information caused by incorrect information entry or misunderstanding by parsing the written information on the nameplate and identifying the association of information items based on the information logical relationship. By obtaining the matching nameplate format constraint conditions according to the usage scenario and generating the nameplate information accordingly, it ensures that the nameplate information meets the corresponding format requirements in various scenarios. The entire process realizes automated processing, from information reading, parsing, association identification to format matching and information generation. For the processing of a large number of server product nameplate information, it can be completed quickly and accurately, improving the production and operation efficiency.
[0051] Further, as a verification method for the above product nameplate information configuration and verification method, the following embodiments are the specific verification processes for the nameplate information. To fully illustrate the specific implementation process in this embodiment, as Figure 2 shown, the method further includes: S201. Obtain the product nameplate image, and perform keyword parsing on the product nameplate image based on the product identification module to obtain the nameplate information of the product nameplate image.
[0052] In some embodiments, the product nameplate image refers to generating the nameplate information that matches the nameplate item based on the information item association representation and the nameplate format constraint conditions. This nameplate information is used on the corresponding product. The nameplate information of the product nameplate image can be obtained by relevant detection equipment, specifically based on the product nameplate image captured in real time by a camera or imported by an industrial scanner. The format of the product nameplate image can be JPEG, PNG, or BMP. In some embodiments, obtain the product nameplate image, preprocess the product nameplate image to obtain a standard product nameplate image, input the standard product nameplate image into the product identification module, and identify the nameplate information of the standard product nameplate image through the product identification module.
[0053] Specifically, in this embodiment, the color image can be converted into a grayscale image to reduce complexity. The text and background are separated by an adaptive threshold algorithm. Gaussian filtering is used to remove noises such as fingerprints and contaminants. The visibility of the text in the dark area is enhanced by combining the contrast stretching algorithm. This embodiment can also perform image enhancement. By techniques such as histogram equalization and contrast stretching, the gray dynamic range of the image is extended, the overall clarity and contrast of the image are improved, and the text and pattern details on the nameplate are highlighted.
[0054] The product identification module involved in this embodiment can be based on deep learning algorithms, such as the Convolutional Neural Network (CNN) architecture. During the training phase, the product identification module uses a large amount of image data containing various product nameplate information for training. During the training process, the model continuously learns the feature representations of different texts, numbers, symbols, and patterns in the images. When a standard product nameplate image is input, the convolutional layer in the module slides convolutional kernels over the image to extract local features of the image, and the pooling layer reduces the dimension of the convolutional features, retaining the main features while reducing the amount of data. After multiple layers of convolution and pooling operations, the model gradually extracts the key features in the image and performs classification and recognition through the fully connected layer, finally outputting the nameplate information in the image, such as product model, serial number, production date, etc.
[0055] S202. According to the nameplate information, use the product attribute information extraction model to extract information from the product nameplate image and extract the key product information of the product nameplate image.
[0056] In this embodiment, the product attribute information extraction model can incorporate NLP processing algorithms to perform word segmentation on the nameplate information, splitting the continuous text content into individual words or phrases with independent semantics.
[0057] Exemplarily speaking, for the nameplate information "a certain server, model FWQA-100, produced in January 2021, memory 32GB", after word segmentation, we get "server", "model", "FWQA-100", "January 2021", "memory", "32GB", etc. Then, use a pre-trained language model, such as BERT (Bidirectional Encoder Representations from Transformers), to perform semantic encoding on the word segmentation to obtain the semantic vector representation of each word in a specific context, thereby understanding its semantic meaning.
[0058] With the help of the nameplate information architecture, the correlation relationships between these semantic vectors can be mined. In the nameplate information architecture of server products, there are clear associations between the "FWQA-100" model and specific processor models, memory types, hard disk specifications, etc. Through this correlation analysis, the model extracts the key attribute information of the product from the nameplate information, such as processor model, memory capacity, hard disk capacity, etc.
[0059] S203. Obtain the product preset data corresponding to the product nameplate image, and compare and verify the product key information with the product preset data.
[0060] The product key information database involved in this embodiment is a structured data set that contains detailed standard information of various products produced by the enterprise. For server products, the database records comprehensive configuration parameters of different models of servers, such as processor model, number of cores, main frequency, memory capacity, type, frequency, hard disk type, capacity, rotation speed, network interface type, rate, etc., and also includes information such as production process standards and quality inspection indicators of the products.
[0061] For numerical data, such as memory capacity and hard disk capacity, the system directly compares the magnitudes of the values and also considers the consistency of units. For example, if the extracted memory capacity is "32GB", it is numerically matched with the memory capacity in the preset data. If the two are equal and the units are consistent, this part of the comparison passes.
[0062] For text data, such as product model and processor model, this embodiment uses a string matching algorithm for exact matching. Optionally, this embodiment also pre - establishes a thesaurus for auxiliary matching. For example, the processor model recorded in the product preset data is "Intel Xeon E5 - 2620 v4", and the information extracted may have an abbreviated form such as "Xeon E5- 2620 v4". Through the mapping of the thesaurus, it can be determined whether the two are consistent. During the comparison process, the system also considers the integrity and accuracy of the data. For data with missing or obviously incorrect key information, the comparison is determined to fail.
[0063] S204. If the comparison and verification pass, then it is determined that the product nameplate image passes the verification, and it is determined that the nameplate body corresponding to the product nameplate image is in a verified state.
[0064] In some embodiments, if the comparison and verification pass, then it is determined that the product nameplate image passes the verification, and then it is determined that the nameplate body corresponding to the product image uploaded by the user is in a verified state.
[0065] When the comparison and verification of the product key information with the product preset data pass, the information contained in the product nameplate image involved in this embodiment is consistent with the user's product standard information, so it is determined that the product nameplate image passes the verification.
[0066] As an implementation example of this application, an industrial camera takes pictures of the nameplates of each server about to come off the production line. After obtaining the images, the images are grayscale processed to convert the color images into grayscale images. Then, the median filtering algorithm is used to remove the noise points in the images and improve the image quality. Next, the histogram equalization technique is used to enhance the contrast of the images, making the text on the nameplates clearer. After geometric correction, the tilted images are corrected to standard front views to obtain standard product nameplate images. These images are input into the product recognition module trained based on a convolutional neural network. After multiple convolutional and pooling operations, the nameplate information is successfully recognized, including the product model "PowerEdge R740xd", serial number "CN12345678", production date "2023 - 09 - 15", etc.
[0067] For the recognized nameplate information "PowerEdge R740xd, CN12345678, 2023 - 09 - 15", the product attribute information extraction model first performs word segmentation to obtain words such as "PowerEdge", "R740xd", "CN12345678", "2023 - 09 - 15". The pre-trained language model is used to perform semantic encoding on these segmented words, and then the association is analyzed with the help of the nameplate information architecture. The key product information such as the processor model "Intel Xeon Silver 4210R", memory capacity "64GB DDR4", and hard disk capacity "8TB SAS" usually equipped with this model of server is extracted.
[0068] The product key information database stores the preset data of the PowerEdge R740xd server. For this model of server, the preset data records information such as the standard configuration of "Intel Xeon Silver 4210R processor", "64GB DDR4 memory", and "8TB SAS hard disk". The system compares the key information such as the processor model "Intel Xeon Silver 4210R", memory capacity "64GB", and hard disk capacity "8TB" extracted from the product nameplate image with the corresponding items in the product preset data. When comparing the memory capacity, it is confirmed that the data type is numerical and the value is consistent with the preset; when comparing the processor model, through string matching and the assistance of a thesaurus, it is judged that the two are consistent. After comprehensive comparison, all key information matches the preset data.
[0069] Since the comparison and verification of the product key information and the product preset data pass, it is determined that the product nameplate image passes the verification.
[0070] In this embodiment, through multi-link processing and verification of the product nameplate image, from image acquisition, preprocessing to information extraction and comparison, the accuracy of the nameplate information is ensured.
[0071] In this embodiment, after determining that the nameplate body corresponding to the product nameplate image is in a verified passed state, it further includes: storing the verified passed product key information in a preset product key information database.
[0072] When a request for addition, deletion, or modification is received, add, delete, or modify the product key information corresponding to the request for addition, deletion, or modification from the preset product key information database; determine whether the product key information corresponding to the request for addition, deletion, or modification is within the operable time; when the product key information corresponding to the request for addition, deletion, or modification is within the operable time, call the product key information corresponding to the request for addition, deletion, or modification to complete the addition, deletion, or modification operation.
[0073] In some embodiments, after obtaining the user's consent, store the verified passed product key information in a preset product key information database. In the next addition, deletion, or modification cycle, when the user initiates a request for addition, deletion, or modification, extract the product key information corresponding to the request for addition, deletion, or modification from the preset product key information database, determine whether the product key information corresponding to the request for addition, deletion, or modification is within the operable time. If the product key information for addition, deletion, or modification is within the operable time, use the verified passed product key information to complete the request for addition, deletion, or modification. If the product key information for the request for addition, deletion, or modification is not within the operable time, prompt the user to re-upload a compliant product image for verification.
[0074] Further, the steps of obtaining the pre-constructed nameplate information architecture and mapping the nameplate information association status to the nameplate information architecture specifically include: constructing a nameplate mapping rule and creating several product keywords within the nameplate mapping rule.
[0075] Identify the nameplate items of the nameplate information architecture, pair the nameplate items of the nameplate information architecture with the product keywords within the nameplate mapping rule to obtain a knowledge feature pairing result; according to the knowledge feature pairing result, import the nameplate information architecture into the nameplate mapping rule.
[0076] In this embodiment, by constructing a nameplate mapping rule, the relationship between the nameplate information architecture and the product keywords is effectively integrated. In this mapping space, first, according to dimensions such as product characteristics and nameplate information association status, several product keywords are created, and these product keywords represent the core elements that need to be concerned in the generation of nameplate information. By identifying the nameplate items in the nameplate information architecture, these nodes are paired with the product keywords within the nameplate mapping rule, and the pairing process is achieved through methods such as nameplate information association similarity calculation and embedding vector matching to ensure that the nameplate items can be accurately mapped to the most relevant product keywords.
[0077] In some specific embodiments, in the nameplate information architecture, based on the nameplate information association status, the information item association between the nameplate written information and the nameplate items of the nameplate information architecture is identified through information logic relationships, and the steps reflected by the information item association are specifically as follows: Parse the nameplate information of the nameplate items in the nameplate information architecture to obtain the product attribute representation of the nameplate items.
[0078] Based on the nameplate information association status and the product attribute representation of the nameplate items, determine whether there is an information item association between the nameplate written information and the nameplate items.
[0079] If there is an information item association between the nameplate written information and the nameplate items, extract the information item association features and generate the information item association representation.
[0080] In this embodiment, first, parse the nameplate information of the nameplate items in the nameplate information architecture to generate the product attribute representation of the nameplate items. Here, the nameplate items can be converted into computable product attribute vectors through natural language processing technology, and the product attribute vectors can represent the product attribute features of the nameplate items. Based on the previously obtained nameplate information association status and the product attribute representation of the nameplate items, calculate the nameplate information association similarity or relevance between the nameplate information association status and the product attribute representation of the nameplate items. Through this similarity calculation, it is possible to determine whether there is an information item association between the nameplate written information and the nameplate items. If it is detected that there is an information item association, further extract the associated feature information, such as the weight of the association, the type of the association, etc. The features are used to generate the information item association representation, providing detailed information item association information about the relationship between the nameplate written information and the product characteristics. The generation of the information item association representation not only includes the direct association between keywords and nameplate items, ensuring that the generated content can accurately reflect the product information.
[0081] Through the above method, the information item association analysis between the nameplate written information and the product nameplate items is realized, and a detailed information item association representation is generated. It is possible to generate more targeted and product-attribute nameplate information, ensuring that the nameplate information conforms to the product attributes.
[0082] Furthermore, the step of determining whether there is an information item association between the nameplate written information and the nameplate items based on the nameplate information association status and the product attribute representation of the nameplate items specifically includes: Calculate the nameplate information association similarity between the nameplate information association status and the product attribute representation of the nameplate items. Compare the nameplate information association similarity with a preset similarity threshold. When the nameplate information association similarity is greater than or equal to the similarity threshold, it is determined that there is an information item association between the nameplate written information and the nameplate items.
[0083] When the nameplate information association similarity is less than the similarity threshold, it is determined that there is no information item association between the nameplate written information and the nameplate items.
[0084] In this embodiment, in order to calculate the similarity, the VSM (Vector Space Model) is adopted to convert both the associated status of the nameplate information and the product attribute manifestation of the nameplate items into vector representations.
[0085] It should be noted that through natural language processing technology, keywords are converted into word vectors. For the product attribute manifestation of the nameplate items, information such as its attribute category and attribute value is also converted into vector representations. For example, the attribute category of "product model" can be converted into a vector through an encoding method, and the attribute value of "FWQA-100" can also be converted into a corresponding vector.
[0086] The cosine similarity algorithm is used to calculate the similarity between these two vectors. Cosine similarity measures the similarity between two vectors by calculating the cosine value of the angle between them, and its value range is between [-1, 1]. The closer the value is to 1, the more similar the two vectors are, that is, the higher the similarity between the associated status of the nameplate information and the product attribute manifestation of the nameplate items.
[0087] The preset similarity threshold is a value preset in advance according to actual business requirements and experience, and is used to determine whether there is an information item association. The setting of the threshold needs to comprehensively consider various factors, such as the type of product, the accuracy requirements of the nameplate information, and the possible error range, etc.
[0088] Optionally, the calculated nameplate information association similarity is compared with the preset similarity threshold. For example, if the preset similarity threshold is 0.6 and the calculated nameplate information association similarity is 0.7, then the next step of judgment is continued.
[0089] If the nameplate information association similarity is greater than or equal to the preset similarity threshold, it indicates that there is a high similarity between the associated status of the nameplate information and the product attribute manifestation of the nameplate items, that is, the attributes represented by the keywords in the nameplate written information match or are associated with the attribute category and specific attribute values in the product attribute manifestation of the nameplate items to a certain extent. It can be determined that there is an information item association between the nameplate written information and the nameplate item.
[0090] When the nameplate information association similarity is less than the preset similarity threshold, it indicates that the similarity between the associated status of the nameplate information and the product attribute manifestation of the nameplate items is low, that is, the attributes represented by the keywords in the nameplate written information do not match or have a low degree of association with the attribute category and specific attribute values in the product attribute manifestation of the nameplate items. Therefore, it is determined that there is no information item association between the nameplate written information and the nameplate item.
[0091] For this embodiment, the steps of generating nameplate information that matches the nameplate item based on the information item association representation and the nameplate format constraint conditions specifically include: Input the information item association representation and nameplate format constraints into the pre-trained nameplate analysis model; traverse the nameplate information library of the nameplate analysis model to identify the target nameplate information that matches the information item association representation; combine the target nameplate information according to the nameplate format constraints to obtain the nameplate information that matches the nameplate item.
[0092] In this embodiment, the pre-trained nameplate analysis model is trained based on a large amount of historical nameplate data and corresponding format specifications. The information item association representation includes the association relationships between various information items extracted from the nameplate written information. For example, the association between the product model and configuration information such as the processor model and memory capacity is presented in a structured form, such as using the JSON format to describe each information item and its association type and strength. The nameplate format constraints stipulate the format requirements for nameplate information during display, covering aspects such as font, font size, layout, and character limit, and are also stored in a specific data structure. For example, an XML file details the parameters of each format requirement. Inputting these two into the model is to enable the model to process and analyze the input information based on the knowledge and pattern recognition capabilities accumulated during its training, and prepare for generating nameplate information that meets the requirements.
[0093] The nameplate information library of the nameplate analysis model in this embodiment stores historical nameplate information and corresponding various attributes and association relationships. The traversal process is like searching in a large database. The model will search for records that match it in the information library based on the key information in the information item association representation, such as a specific product model and its associated configuration information characteristics.
[0094] Exemplarily speaking, if the information item association representation mentions that the product model is "FWQA-100" and the processor model usually associated with this model is "Intel Xeon E5-2620 v4", the nameplate analysis model searches the information library for all nameplate information records that contain the model "FWQA-100" and whose processor model matches. The search and matching process is based on the semantics and association relationships understood by the nameplate analysis model, taking into account factors such as possible synonymous expressions, abbreviated forms, and differences in the association strength between different records, so as to accurately identify the target nameplate information that highly matches the currently input information item association representation.
[0095] After identifying the target nameplate information, the nameplate analysis model recombines and formats this information according to the nameplate format constraint conditions. Exemplarily speaking, if the format constraint conditions stipulate that the product model uses a preset font in bold and is left-aligned, then the model will set the font and adjust the position of the product model field in the target nameplate information according to this requirement. If there are character limitations, such as the product description information cannot exceed a preset number of characters, the nameplate analysis model will truncate or streamline the relevant information to ensure that the finally generated nameplate information completely conforms to the given constraint conditions in terms of format, so as to present a standardized, unified and business-requirement-compliant nameplate display effect.
[0096] Through the pre-trained nameplate analysis model and the comprehensive processing of the information item association representation and format constraint conditions, the nameplate information can be accurately identified and combined. Combining the information according to the nameplate format constraint conditions makes all the generated nameplate information highly consistent in format.
[0097] It should be understood that the magnitudes of the sequence numbers of the steps in the above embodiments do not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation to the implementation process of the embodiments of the present invention.
[0098] As Figure 3 shown, the present application also provides an electronic device, including a display module 103, a memory 102, a processor 101, and a computer program stored on the memory and executable on the processor 101. When the processor 101 executes the program, it implements the steps of the product nameplate information configuration and verification method.
[0099] In the embodiments of the present invention, the electronic device includes, but is not limited to, a laptop computer, a desktop computer, a workbench, a personal digital assistant, a server, a blade server, a mainframe computer, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as a personal digital processor, a cellular phone, a smart phone, a wearable device, 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 embodiments of the present application described herein and / or claimed.
[0100] In the embodiments of the present application, the processor 101 can be implemented by using at least one of an application specific integrated circuit (ASIC), a programmable logic device (PLD), a field programmable gate array (FPGA), a processor, a controller, a microcontroller, a microprocessor, and an electronic unit designed to execute the functions described herein. In some cases, such an implementation can be implemented in a controller. For a software implementation, an implementation of a process or function can be implemented with a separate software module that allows execution of at least one function or operation. The software code can be implemented by a software application (or program) written in any suitable programming language. The software code can be stored in a memory and executed by a controller.
[0101] The display module 103 is used to display information input by the user or information provided to the user. The display module 103 may include a display panel, and the display panel may be configured in the form of a liquid crystal display (LCD), an organic light-emitting diode (OLED), or the like.
[0102] The memory 102 can be used to store software programs and various data. The memory 102 may include a high-speed random access memory, and may also include a non-volatile memory, such as at least one magnetic disk storage device, a flash memory device, or other volatile solid-state storage devices.
[0103] The present application also provides a storage medium, on which a computer program is stored. When the computer program is executed by a processor, the steps of the method for configuring and verifying product nameplate information are implemented.
[0104] The storage medium can adopt any combination of one or more readable media. The readable media can be a readable signal medium or a readable storage medium. The readable storage medium can be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the above. More specific examples (non-exhaustive list) of the readable storage medium include: an electrical connection having one or more wires, a portable disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above.
[0105] The foregoing description of the disclosed embodiments enables those skilled in the art to implement or use the present invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the present invention. Thus, the present invention is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims
1. A method for configuring and verifying product nameplate information, characterized in that, The method includes: Obtain the nameplate item of the nameplate information to be processed, and read the nameplate writing information in the nameplate item; Perform nameplate information parsing on the nameplate writing information to obtain the nameplate information association status; Obtain the pre-constructed nameplate information architecture, and map the nameplate information association status into the nameplate information architecture; In the nameplate information architecture, based on the nameplate information association status, identify the information item association between the nameplate writing information and the knowledge nodes of the nameplate information architecture through information logical relationships, and obtain the information item association representation; Obtain the nameplate format corresponding to the nameplate information to be processed from the nameplate item, and obtain the nameplate format constraint conditions matching the nameplate format in the preset nameplate format definition library; Generate the nameplate information matching the nameplate item based on the information item association representation and the nameplate format constraint conditions.
2. The product nameplate information configuration and verification method according to claim 1, characterized in that The step of obtaining the pre-constructed nameplate information architecture and mapping the nameplate information association status into the nameplate information architecture specifically includes: Construct a nameplate mapping rule, and create multiple product keywords within the nameplate mapping rule; Identify the nameplate items of the nameplate information architecture, and pair the nameplate items of the nameplate information architecture with the product keywords in the nameplate mapping rule to obtain the knowledge feature pairing result; According to the knowledge feature pairing result, import the nameplate information architecture into the nameplate mapping rule.
3. The product nameplate information configuration and verification method according to claim 1, characterized in that The step of identifying the information item association between the nameplate writing information and the knowledge nodes of the nameplate information architecture through information logical relationships based on the nameplate information association status to obtain the information item association representation specifically includes: Perform nameplate information parsing on the nameplate items of the nameplate information architecture to obtain the product attribute manifestation of the nameplate item; Based on the nameplate information association status and the product attribute manifestation of the nameplate item, judge whether there is an information item association between the nameplate writing information and the nameplate item; If there is an information item association between the nameplate writing information and the nameplate item, extract the information item association feature and generate the information item association manifestation.
4. The product nameplate information configuration and verification method according to claim 3, characterized in that The step of judging whether there is an information item association between the nameplate writing information and the nameplate item based on the nameplate information association status and the product attribute manifestation of the nameplate item specifically includes: Calculate the nameplate information association similarity between the nameplate information association status and the product attribute manifestation of the nameplate item; Compare the nameplate information association similarity with the preset similarity threshold; When the nameplate information association similarity is greater than or equal to the similarity threshold, it is determined that there is an information item association between the nameplate writing information and the nameplate item; When the nameplate information association similarity is less than the similarity threshold, it is determined that there is no information item association between the nameplate writing information and the nameplate item.
5. The product nameplate information configuration and verification method according to claim 1, characterized in that The step of generating the nameplate information matching the nameplate item based on the information item association representation and the nameplate format constraint conditions specifically includes: Input the information item association manifestation and the nameplate format constraint conditions into the pre-trained nameplate analysis model; Traverse the nameplate information library of the nameplate analysis model to identify the target nameplate information that matches the information item association. Combine the target nameplate information according to the nameplate format constraint conditions to obtain the nameplate information that matches the nameplate item.
6. The product nameplate information configuration and verification method according to claim 1, characterized in that After generating the nameplate information that matches the nameplate item, it further includes: Obtain the product nameplate image, and use the product recognition module to perform keyword parsing on the product nameplate image to obtain the nameplate information of the product nameplate image. According to the nameplate information, use the product attribute information extraction model to extract information from the product nameplate image, and extract the key product information of the product nameplate image. Obtain the product preset data corresponding to the product nameplate image, and compare and verify the key product information with the product preset data. If the comparison and verification pass, it is determined that the product nameplate image passes the verification, and the nameplate body corresponding to the product nameplate image is determined to be in a verified state.
7. The product nameplate information configuration and verification method according to claim 6, characterized in that According to the nameplate information, using the product attribute information extraction model to extract information from the product nameplate image, and extracting the key product information of the product nameplate image includes: According to the nameplate information, use the product attribute information extraction model to detect the nameplate items of the product nameplate image to obtain the key nameplate item information. Use the nameplate analysis model of the product attribute information extraction model to process the key nameplate item information, and extract the key nameplate information of the key nameplate item information. Use the structured processing module of the product attribute information extraction model to perform format conversion on the key nameplate information according to the nameplate format to obtain the key product information of the product nameplate image.
8. The product nameplate information configuration and verification method according to claim 6, characterized in that The step of comparing and verifying the key product information with the product preset data specifically includes: Perform structured processing on the product preset data according to the predefined structure template to obtain the structured product preset data. Compare and verify the key product information with the information in the same identification position in the product preset data. If the comparison and verification fails, mark the product nameplate image as an abnormal product image.
9. An electronic device, comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the steps of the product nameplate information configuration and verification method according to any one of claims 1 to 8.
10. A storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps of the product nameplate information configuration and verification method according to any one of claims 1 to 8.