Commodity information auditing method, program product, electronic equipment and storage medium

Abstract

The invention provides a commodity information auditing method, a program product, electronic equipment and a storage medium, which are applied to the technical field of computers, and the method comprises the following steps: obtaining commodity information input by a user, the commodity information comprising a commodity text and a commodity image; respectively verifying the commodity text and the commodity image to obtain corresponding commodity verification results; receiving a commodity auditing result of the auditing personnel for the commodity verification result; and processing the commodity information according to the commodity auditing result. By introducing a machine auditing mechanism, the commodity text and the commodity image of the commodity are subjected to machine auditing by using the electronic equipment, so that the accuracy and the efficiency of auditing the commodity information are improved. Besides, after the commodity verification result is obtained based on machine auditing, manual auditing can be performed to re-check the commodity verification result, so that the accuracy of the commodity auditing result can be ensured, and the commodity information can be correspondingly processed according to the commodity auditing result.

Description

Technical Field

[0001] The present application relates to the field of computer technology, and more specifically, to a product information review method, program product, electronic device, and storage medium. Background Art

[0002] With the continuous growth of user demand and the increasing variety of goods, Internet e-commerce platforms are facing a huge challenge: how to efficiently and accurately review massive amounts of product information to ensure the quality and compliance of the products on the platform.

[0003] Traditionally, product information review relies primarily on manual labor, with reviewers required to review and process massive amounts of product information daily. This process is not only time-consuming and labor-intensive, but also susceptible to subjective factors, making it difficult to ensure the accuracy and consistency of review results. With the rapid advancement of technology, the variety and volume of product information are increasing, covering the diversity and complexity of various products. This surge in product information places a significant burden on reviewers, increases product availability, and impacts overall operational efficiency. Summary of the Invention

[0004] The purpose of the embodiments of the present application is to provide a product information review method, program product, electronic device and storage medium to solve the technical problem of low accuracy in reviewing product information in the prior art.

[0005] In a first aspect, an embodiment of the present application provides a product information review method, comprising: obtaining product information input by a user, wherein the product information includes product text and product image; verifying the product text and the product image respectively to obtain corresponding product verification results; receiving a product review result from a reviewer based on the product verification result; and processing the product information according to the product review result.

[0006] In the above solution, by introducing a machine review mechanism, electronic equipment is used to perform machine review of product text and product images, thereby improving the accuracy and efficiency of product information review. In addition, after the product verification results are obtained based on machine review, manual review can be performed to review the product verification results, thereby ensuring the accuracy of the product verification results, and then the product information can be processed accordingly based on the product review results.

[0007] In an optional embodiment, the verification of the product text and the product image to obtain corresponding product verification results includes: performing at least one of the following verifications on the product text: category verification, attribute verification, sales information verification, title structure verification, and size verification; and performing at least one of the following verifications on the product image: image quality verification, children's clothing strap verification, and duplicate product verification. In the above scheme, during the review of product information, not only the text description and image of the product are reviewed, but also multiple dimensions such as the product's attributes, category, price, and sales information are combined to ensure the comprehensiveness and effectiveness of the review results, thereby improving the accuracy of the product information review.

[0008] In an optional embodiment, the product information includes the product title, applicable population, product attributes, and product category, and performing the category verification on the product text includes: inputting the product information into a category prediction model to obtain a predicted category output by the category prediction model; and determining whether the predicted category is consistent with the product category, wherein the consistency between the predicted category and the product category indicates that the product text has passed the category verification. In the above scheme, the predicted category of the product can be obtained by inputting the product information into the category prediction model, and then the product category can be verified by comparing the predicted category with the product category.

[0009] In an optional embodiment, the product information includes product categories and product attributes, and the product attributes include general attributes, applicable seasons, and primary colors. Attribute verification of the product text includes: inputting the product information into an attribute prediction model to obtain predicted attributes output by the attribute prediction model; and determining whether the predicted attributes are consistent with the product attributes, wherein consistency between the predicted attributes and the product attributes indicates that the product text has passed the attribute verification. In the above scheme, the predicted attributes of the product can be obtained by inputting the product information into the attribute prediction model, and then the product category can be verified by comparing the predicted attributes with the product attributes.

[0010] In an optional embodiment, the product information includes sales information, and the sales information includes sales time and sales price. The sales information verification is performed on the product text, including: determining whether the sales time exceeds the preset time, wherein the sales time exceeding the preset time indicates that the product text has not passed the sales information verification; and determining whether the sales price exceeds the preset price, wherein the sales price exceeding the preset price indicates that the product text has not passed the sales information verification, and the preset price includes the average price of products under the brand corresponding to the product information, the highest sales price within a preset time period under the brand, and the lowest sales price. In the above scheme, by comparing the sales time with the preset time, products with too long a sales time can be screened out; similarly, by comparing the sales price with the pre-sale price, products with too high or too low sales prices can be screened out, thereby maintaining fair competition in the market and improving the user experience.

[0011] In an optional embodiment, the product information includes a product title, and performing the title structure check on the product text includes: splitting the product title into different types of segments; and determining whether each segment complies with a naming specification, wherein each segment complies with the naming specification indicating that the product text has passed the title structure check. In the above solution, by structuring the product title and splitting the product title into different types of segments, it is possible to determine whether each segment complies with the naming specification, thereby improving the accuracy of the product title review.

[0012] In an optional embodiment, the product information includes product size, and performing the size verification on the product text includes: determining whether the product size is within a standard size chart, wherein if the product size is not within the standard size chart, it indicates that the product text has failed the size verification; and determining whether the product size matches the applicable population, wherein if the product size does not match the applicable population, it indicates that the product text has failed the size verification. In the above solution, by determining whether the product size is within the standard size chart and determining whether the product size matches the applicable population, the size of each product is standardized, thereby improving the user experience.

[0013] In an optional embodiment, performing the image quality verification on the product image includes: determining whether the product image complies with preset rules, wherein compliance with the preset rules indicates that the product image has passed the image quality verification, and the preset rules include the product image having a white background, the product image being a tiled image of the front or back of the product, and the number and clarity of the product images meeting requirements. In the above scheme, by determining whether the product image has a white background, whether it is a tiled image of the front or back of the product, and whether the number and clarity of the product images meet requirements, the product images can be standardized, thereby improving the user experience.

[0014] In an optional embodiment, performing the children's clothing strap verification on the product image includes determining whether the product image contains children's clothing straps, wherein the presence of children's clothing straps in the product image indicates that the product image has passed the image quality verification. In this solution, by determining whether the product image contains children's clothing straps, it is ensured that the product information related to children's clothing complies with market and legal requirements, thereby reducing safety hazards such as suffocation caused by improperly designed children's clothing straps.

[0015] In an optional embodiment, performing duplicate product verification on the product image includes: determining, based on the product image, whether the product corresponding to the product image is a duplicate of an existing product, wherein a duplicate of the existing product indicates that the product image has failed the duplicate product verification. In the above solution, by determining whether the product is a duplicate of an existing product based on the product image, duplicate product verification is performed on the product, effectively identifying duplicate products, copied products, and homogeneous products, maintaining fair competition in the market, and enhancing product uniqueness.

[0016] In an optional embodiment, processing the product information based on the product review result includes: if the product review result indicates that the product has failed the review, outputting modification information to the user; if the product review result indicates that the product has passed the review, listing the product corresponding to the product information. In the above solution, product information can be processed differently based on the product review result, thereby ensuring that users can receive timely feedback.

[0017] In the second aspect, an embodiment of the present application provides a product information review device, including: an acquisition module for obtaining product information input by a user, wherein the product information includes product text and product image; a verification module for verifying the product text and the product image respectively to obtain corresponding product verification results; a receiving module for receiving the product review result of the reviewer based on the product verification result; and a processing module for processing the product information according to the product review result.

[0018] In the above solution, by introducing a machine review mechanism, electronic equipment is used to perform machine review of product text and product images, thereby improving the accuracy and efficiency of product information review. In addition, after the product verification results are obtained based on machine review, manual review can be performed to review the product verification results, thereby ensuring the accuracy of the product verification results, and then the product information can be processed accordingly based on the product review results.

[0019] In an optional embodiment, the verification module is specifically configured to: perform at least one of the following verifications on the product text: category verification, attribute verification, release information verification, title structure verification, and size verification; and perform at least one of the following verifications on the product image: image quality verification, children's clothing strap verification, and duplicate product verification. In this solution, during the review of product information, the review not only focuses on the product's text description and image, but also incorporates multiple dimensions such as the product's attributes, category, price, and release information. This ensures the comprehensiveness and effectiveness of the review results, thereby improving the accuracy of the product information review.

[0020] In an optional embodiment, the product information includes the product title, applicable population, product attributes, and product category, and the verification module is specifically used to: input the product information into a category prediction model to obtain a predicted category output by the category prediction model; and determine whether the predicted category is consistent with the product category, wherein the consistency between the predicted category and the product category indicates that the product text has passed the category verification. In the above scheme, the predicted category of the product can be obtained by inputting the product information into the category prediction model, and then the product category can be verified by comparing the predicted category with the product category.

[0021] In an optional embodiment, the product information includes product categories and product attributes, wherein the product attributes include general attributes, applicable seasons, and primary colors. The verification module is specifically configured to: input the product information into an attribute prediction model to obtain predicted attributes output by the attribute prediction model; and determine whether the predicted attributes are consistent with the product attributes, wherein consistency between the predicted attributes and the product attributes indicates that the product text has passed the attribute verification. In the above scheme, the predicted attributes of the product can be obtained by inputting the product information into the attribute prediction model, and then the product category can be verified by comparing the predicted attributes with the product attributes.

[0022] In an optional embodiment, the product information includes sales information, and the sales information includes sales time and sales price. The verification module is specifically used to: determine whether the sales time exceeds the preset time, wherein the sales time exceeding the preset time indicates that the product text has not passed the sales information verification; and determine whether the sales price exceeds the preset price, wherein the sales price exceeding the preset price indicates that the product text has not passed the sales information verification, and the preset price includes the average price of products under the brand corresponding to the product information, the highest sales price within a preset time period under the brand, and the lowest sales price. In the above scheme, by comparing the sales time with the preset time, products with too long sales time can be screened out; similarly, by comparing the sales price with the pre-sale price, products with too high or too low sales prices can be screened out, thereby maintaining fair competition in the market and improving user experience.

[0023] In an optional embodiment, the product information includes a product title, and the verification module is specifically configured to: split the product title into different types of segments; and determine whether each segment complies with a naming specification, wherein compliance with the naming specification by each segment indicates that the product text has passed the title structure verification. In the above solution, by structuring the product title and splitting the product title into different types of segments, it is possible to determine whether each segment complies with the naming specification, thereby improving the accuracy of the product title review.

[0024] In an optional embodiment, the product information includes product size, and the verification module is specifically configured to: determine whether the product size is within a standard size chart, wherein if the product size is not within the standard size chart, it indicates that the product information has failed the size verification; and determine whether the product size matches the applicable population, wherein if the product size does not match the applicable population, it indicates that the product information has failed the size verification. In the above solution, by determining whether the product size is within the standard size chart and whether the product size matches the applicable population, the size of each product is standardized, thereby improving the user experience.

[0025] In an optional embodiment, the verification module is specifically configured to determine whether the product image complies with preset rules, wherein compliance with the preset rules indicates that the product image has passed the image quality verification, and the preset rules include the product image having a white background, the product image being a tiled image of the front or back of the product, and the number and clarity of the product images meeting requirements. In the above scheme, by determining whether the product image has a white background, whether it is a tiled image of the front or back of the product, and whether the number and clarity of the product images meet requirements, the product images can be standardized, thereby improving the user experience.

[0026] In an optional embodiment, the verification module is specifically configured to determine whether the product image contains children's clothing strings, wherein the presence of children's clothing strings in the product image indicates that the product image has passed the image quality verification. In this embodiment, by determining whether the product image contains children's clothing strings, it is ensured that children's clothing product information complies with market and legal requirements, thereby reducing safety hazards such as suffocation caused by improperly designed children's clothing strings.

[0027] In an optional embodiment, the verification module is specifically configured to determine, based on the product image, whether the product corresponding to the product image is a duplicate of an existing product, wherein a duplicate of the product indicates that the product image has failed the duplicate product verification. In the above solution, by determining whether the product is a duplicate of an existing product based on the product image, duplicate product verification is performed on the product, effectively identifying duplicate products, copied products, and homogeneous products, maintaining fair competition in the market, and enhancing product uniqueness.

[0028] In an optional embodiment, the processing module is specifically configured to: if the product review result indicates that the product has failed the review, output modification information to the user; if the product review result indicates that the product has passed the review, put the product corresponding to the product information on the shelves. In the above solution, product information can be processed differently based on the product review result, thereby ensuring that users can receive timely feedback.

[0029] In a third aspect, an embodiment of the present application provides a computer program product, comprising computer program instructions, which, when read and executed by a processor, execute the product information review method as described in the first aspect.

[0030] In a fourth aspect, an embodiment of the present application provides an electronic device comprising: a processor, a memory, and a bus; the processor and the memory communicate with each other through the bus; the memory stores computer program instructions that can be executed by the processor, and the processor calls the computer program instructions to execute the product information review method described in the first aspect.

[0031] In a fifth aspect, an embodiment of the present application provides a computer-readable storage medium, which stores computer program instructions. When the computer program instructions are executed by a computer, the computer executes the product information review method as described in the first aspect.

[0032] In order to make the above-mentioned objects, features and advantages of the present application more obvious and easy to understand, the following specifically cites the embodiments of the present application and provides a detailed description in conjunction with the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following is a brief introduction to the drawings required for use in the embodiments of the present application. It should be understood that the following drawings only show certain embodiments of the present application and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other relevant drawings can be obtained based on these drawings without creative work.

[0034] Figure 1 A flowchart of a product information review method provided in an embodiment of the present application;

[0035] Figure 2 This is a diagram of the overall architecture of a product information review solution provided in an embodiment of the present application;

[0036] Figure 3 A structural block diagram of a commodity information review device provided in an embodiment of the present application;

[0037] Figure 4 This is a structural block diagram of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0038] The technical solutions in the embodiments of the present application will be described below in conjunction with the drawings in the embodiments of the present application.

[0039] Please refer to Figure 1 , Figure 1 This is a flowchart of a product information review method provided in an embodiment of the present application. The method can be, but is not limited to, executed by an electronic device. Figure 4 The possible structure of the electronic device is shown. For details, please refer to the following Figure 4 The above-mentioned product information review method may specifically include the following steps:

[0040] Step S101: Acquire product information input by a user, wherein the product information includes product text and product image.

[0041] Step S102: Verify the product text and product image respectively to obtain corresponding product verification results.

[0042] Step S103: receiving the product review result from the reviewer based on the product verification result.

[0043] Step S104: Process the product information according to the product review result.

[0044] Specifically, in step S101 above, product information may include product text and product images. Product text refers to the basic product information entered by the user on the product upload interface, such as product title, product category, product attributes, product release date, product release price, target audience, product size, etc.; product images refer to the image modal information of the product uploaded by the user on the product upload interface, such as a carousel image of the product, an outfit image, etc.

[0045] It should be noted that the embodiments of this application do not specifically limit the specific implementation methods for obtaining product information described above, and those skilled in the art may make appropriate adjustments based on actual circumstances. For example, product information may be received from an external device; or product information may be received from a user in real time on a product upload interface; or product information may be read from a local or cloud-based storage location.

[0046] It is understood that after receiving the product information uploaded by the user in real time on the product upload interface, the format of the uploaded product information can be verified first, and subsequent steps can be performed after the format verification passes to ensure that all required fields are filled in and the information format is correct. It should be noted that the embodiments of this application do not specifically limit the specific implementation method of the above-mentioned format verification, and those skilled in the art can make appropriate adjustments based on existing technologies.

[0047] As an implementation method, the verified product information will generate a Standard Product Unit (SPU), the status of which is set to pending review and saved to the database for subsequent steps.

[0048] In the above step S102, the product text and product image can be verified separately to obtain corresponding product verification results. The specific implementation methods of the present application are not specifically limited, and those skilled in the art can make appropriate adjustments based on actual conditions. For example, the product text and product image can be input into a pre-trained deep learning model to obtain the output product verification result; or, the product text can be compared with preset information or preset standards to obtain the comparison result as the product verification result; or, the product image can be subjected to image recognition to obtain the recognition result as the product verification result, etc.

[0049] As an implementation method, the above-mentioned step S102 can be triggered by monitoring data changes. At this time, there are two situations: in the first situation, the user uploads product information for a new product. At this time, it can be considered that all product information has been updated, and the above-mentioned step S102 can be triggered; in the second situation, the user modifies the product information for an old product. At this time, it can be considered that part of the product information has been updated, and the above-mentioned step S102 can be triggered.

[0050] As another implementation, when product information is modified, the modified product information can be sent to a message queue, which is continuously monitored. Upon receiving the modified product information, the modified product information is compared with the original product information. If the modified product information differs from the original product information, the audit policy corresponding to the modified product information can be searched based on the product category, and the corresponding audit policy can be applied to the modified product information for audit.

[0051] As another embodiment, the audit request parameters (which may include product information) may be encoded and compared with the encoding of the previous request parameters. If they are inconsistent, step S102 may be executed. The encoding method may be MD5, a hash algorithm, a symmetric encryption algorithm, etc., which is not specifically limited in this embodiment of the application.

[0052] In the above step S103, the reviewer can view the entire content of the product information and the product verification result, and obtain the product review result based on the above product information and product verification result.

[0053] As an implementation method, during the review process, reviewers can query the product verification results based on the product identity document (ID). If it is found that certain product information has not passed the machine review, the reviewer can reject the product accordingly based on the relevant results. For example, the reviewer can determine the accuracy of the product verification results. If the product verification results are incorrect, or the product information not covered by the machine review does not meet the requirements, the reviewer can choose to reject the product and require the uploader to modify and resubmit. If all product information passes the review, the product will be confirmed as approved.

[0054] In step S104, the product information can be processed accordingly based on the product review results. For example, the processed product can be divided into two states: "pending modification" and "on sale." If the product status is "pending modification," a message can be sent to the corresponding user, notifying them to make the necessary modifications and providing the specific reason for the rejection. If the product status is "on sale," the product can be uploaded directly.

[0055] In the above solution, by introducing a machine review mechanism, electronic equipment is used to perform machine review of product text and product images, thereby improving the accuracy and efficiency of product information review. In addition, after the product verification results are obtained based on machine review, manual review can be performed to review the product verification results, thereby ensuring the accuracy of the product verification results, and then the product information can be processed accordingly based on the product review results.

[0056] Furthermore, based on the above embodiments, the product text and product image are verified respectively to obtain corresponding product verification results, including: performing at least one of the following verifications on the product text: category verification, attribute verification, sales information verification, title structure verification, and size verification; and performing at least one of the following verifications on the product image: image quality verification, children's clothing strap verification, and duplicate product verification.

[0057] Specifically, category verification predicts the predicted category of a product by analyzing product information such as the product title and product category; attribute verification is used to automatically predict product attributes such as general attributes, applicable seasons and main colors; release information verification is used to predict and pre-fill the release date and release price of a product; title structure verification is used to perform a structured check on the product title to ensure that it complies with the naming specifications of a specific category; size verification is used to ensure the accuracy and consistency of product information such as the applicable population, size, release price, release date, etc., and at the same time check information such as brand name, material and ingredient content to ensure that it complies with regulations.

[0058] Image quality verification is used to check the clarity of the product carousel images and outfit pictures to ensure that the product images meet the display requirements, and verify whether the background color and quantity of the carousel images meet the standards; children's clothing strap verification is used to ensure that all children's clothing-related product information meets market and legal requirements; duplicate product verification is used to detect whether the products submitted by users are duplicates of existing products. If duplicate products are found, the system can choose to prompt or reject them. At the same time, it identifies appearance plagiarism and homogeneous products to ensure the uniqueness of the products.

[0059] In the above scheme, during the process of reviewing product information, not only the text description and image of the product are considered, but also multiple dimensions such as the product attributes, categories, prices, and sales information are combined to ensure the comprehensiveness and effectiveness of the review results, thereby improving the accuracy of the review of product information.

[0060] The following is an introduction to the specific implementation of category verification. At this time, the product information may include the product title, applicable population, product attributes, and product category. The above-mentioned steps of category verification of product text may specifically include the following steps:

[0061] Step 1) Input the product information into the category prediction model to obtain the predicted category output by the category prediction model.

[0062] Step 2) determines whether the predicted category is consistent with the product category, wherein the consistency between the predicted category and the product category indicates that the product text has passed the category verification.

[0063] Specifically, the product title refers to the title information that users are required to fill in on the product upload interface. As an implementation, the product title can be structured to be divided into multiple different types of segments. The various segments of the product title that users are required to fill in on the product upload interface can be pre-set, and users are required to fill in the product title for each segment before uploading the corresponding product.

[0064] Applicable population refers to the information about the population that the product is suitable for, which the user needs to fill in on the product upload interface. For example: the applicable population of the product is women, men, children or the elderly, etc.

[0065] Product attributes can be categorized into general attributes and other attributes. General attributes are the distinguishing attributes of a product. For example, for shoes, general attributes might include suitable seasons, upper height, and closure type, while other attributes might include color and style.

[0066] Product categories can include multiple dimensions. For example, product categories can include primary, secondary, and tertiary categories, such as: shoes (primary category) - sports shoes (secondary category) - running shoes (tertiary category). You can pre-set the number of product category dimensions that users need to enter on the product upload interface. Users must enter product categories in multiple dimensions before uploading the corresponding products.

[0067] By analyzing the product title, target demographics, product attributes, and product category input by the user, a predicted product category can be predicted. As an implementation method, the product title, target demographics, product attributes, and product category can be input into a category prediction model to obtain a predicted category output by the category prediction model.

[0068] It should be noted that the embodiments of the present application do not make any specific limitations on the specific implementation methods of the above-mentioned category prediction model, and those skilled in the art do not make any specific limitations on this, for example: decision tree, support vector machine, random forest, neural network model, etc.

[0069] As an implementation method, if the predicted category is inconsistent with the product category, the product verification result may be stored as: incorrect category entry, xxx is recommended.

[0070] In the above scheme, by inputting the product information into the category prediction model, the predicted category of the product can be obtained, and then by comparing the above predicted category with the product category, the product category can be verified.

[0071] The following is an introduction to the specific implementation of attribute verification. In this case, product information may include product categories and product attributes. Product attributes include general attributes, applicable seasons, and product main colors. The above-mentioned steps of performing attribute verification on product text may specifically include the following steps:

[0072] Step 1) Input the product information into the attribute prediction model to obtain the predicted attributes output by the attribute prediction model.

[0073] Step 2) determines whether the predicted attribute is consistent with the product attribute, wherein the consistency between the predicted attribute and the product attribute indicates that the product text passes the attribute verification.

[0074] Specifically, a general attribute is a distinguishing attribute of a product. For example, for shoes, general attributes might include applicable season, upper height, closure type, and so on. Applicable season refers to the seasonal information that users enter on the product upload screen, for example, spring, summer, autumn, and winter. The primary color of a product refers to the primary color of the product that users enter on the product upload screen.

[0075] By analyzing the product categories and product attributes input by the user, the predicted attributes of the product can be predicted. As an implementation method, the above product categories and product attributes can be input into the attribute prediction model to obtain the predicted attributes output by the attribute prediction model.

[0076] It should be noted that the embodiments of the present application do not make any specific limitations on the specific implementation methods of the above-mentioned attribute prediction model, and those skilled in the art do not make any specific limitations on this, for example: decision tree, support vector machine, random forest, neural network model, etc.

[0077] As an implementation method, if the predicted attribute is inconsistent with the product attribute, the product verification result may be stored as: wrong attribute entry, xxx is recommended.

[0078] In the above scheme, by inputting the product information into the attribute prediction model, the predicted attributes of the product can be obtained, and then by comparing the above predicted attributes with the product attributes, the product category can be verified.

[0079] The following is an introduction to the specific implementation of sales information verification. In this case, the product information may include sales information, which includes sales time and sales price. The above steps of verifying the sales information of the product text may specifically include the following steps:

[0080] Step 1) determines whether the release time exceeds the preset time, wherein the release time exceeds the preset time, indicating that the product text has not passed the release information verification.

[0081] Step 2) determines whether the selling price exceeds the preset price, wherein the selling price exceeding the preset price indicates that the product text has not passed the selling information verification.

[0082] Specifically, the release information refers to the release time and release price corresponding to the product that the user needs to fill in on the product upload interface.

[0083] Regarding the release time, the release time can be compared to see if it exceeds the preset time. The embodiment of the present application does not specifically limit the specific implementation of the preset time, and those skilled in the art can make appropriate adjustments based on actual conditions. For example, the preset time can be within 180 days before the current time.

[0084] The selling price can be compared to see if it exceeds a preset price, wherein the preset price includes the average price of the product under the brand corresponding to the product information, the highest selling price under the brand within a preset time period, and the lowest selling price.

[0085] It is understandable that when comparing the selling price and the preset price, it can be considered that the selling price is greater than the average price of the goods, indicating that the selling price exceeds the preset price, or it can be considered that the difference between the selling price and the average price of the goods is too large, indicating that the selling price exceeds the preset price; similarly, it can be considered that the selling price is outside the highest selling price and the lowest selling price, indicating that the selling price exceeds the preset price, or it can be considered that the difference between the selling price and the highest selling price and the lowest selling price is too large, indicating that the selling price exceeds the preset price.

[0086] As an implementation method, if the sales time exceeds the preset time, the product verification result can be stored as: the sales time may be inaccurate; as another implementation method, if the sales price exceeds the preset price, the product verification result can be stored as: the sales price may be inaccurate.

[0087] It should be noted that the above steps 1) and 2) correspond to two different verification methods for the sale information, and therefore belong to parallel solutions, not sequential execution solutions.

[0088] In the above scheme, by comparing the release time with the preset time, products with too long release time can be screened out; similarly, by comparing the release price with the pre-sale price, products with too high or too low release prices can be screened out, thereby maintaining fair competition in the market and improving the user experience.

[0089] The following is an introduction to the specific implementation of title structure verification. In this case, the product information may include the product title. The steps of performing title structure verification on the product text may specifically include the following steps:

[0090] Step 1), split the product title into different types of segments.

[0091] Step 2) determines whether each segment complies with the naming specification, wherein each segment complies with the naming specification and indicates that the product text has passed the title structure verification.

[0092] Specifically, by structuring product titles and breaking them down into different types of segments, users only need to fill in the appropriate segments. The various types of title segments filled in by users and the rest of the product information are analyzed to verify whether the product titles contain content that does not comply with naming standards.

[0093] As an implementation method, if each segment does not comply with the naming specification, the product verification result may be stored as: the structured title linkage field is inconsistent with the product information.

[0094] In the above solution, by structuring the product title and splitting the product title into different types of segments, it is possible to judge whether each segment complies with the naming specification, thereby improving the accuracy of the product title review.

[0095] The following is an introduction to the specific implementation of size verification. In this case, the product information may include the product size. The above steps of size verification of the product text may specifically include the following steps:

[0096] Step 1) determines whether the product size is in the standard size table, wherein if the product size is not in the standard size table, it indicates that the product text has failed the size verification.

[0097] Step 2) determines whether the product size matches the applicable population. If the product size does not match the applicable population, it indicates that the product text has failed the size verification.

[0098] Specifically, the standard size chart refers to the sizes commonly used in the industry. When filling in the product size, users can try to fill in the size that is consistent with the size in the standard size chart. In addition, it can be checked whether the size is too large or too small for the target group (general, men, women, etc.) entered by the user.

[0099] As an implementation method, if the product size fails the size verification, the product verification result may be stored as: the size does not meet the specifications.

[0100] It should be noted that the above steps 1) and 2) correspond to two different ways of verifying product size, and therefore belong to parallel solutions, not sequential solutions.

[0101] In the above solution, by determining whether the product size is in the standard size table and whether the product size matches the applicable population, the size of each product is standardized, thereby improving the user experience.

[0102] The specific implementation of image quality verification is introduced below. At this time, the above-mentioned steps of performing image quality verification on the product image may specifically include the following steps:

[0103] It is determined whether the product image complies with the preset rules, wherein the product image complies with the preset rules, indicating that the product image has passed the image quality verification.

[0104] Specifically, the above-mentioned preset rules may include that the product image has a white background, the product image is a flat image of the front or back of the product, and the number and clarity of the product images meet the requirements.

[0105] For example, you can verify whether the first image of the product carousel and the first image of each specification have a white background to ensure the uniform color tone of the product display interface; or, you can verify whether the first image of the product carousel and the first image of each specification are front or back tiled images; or, you can verify whether the number and clarity of the carousel images meet the requirements.

[0106] As an implementation method, if the product image does not conform to the preset rules, the product verification result can be stored as: the main carousel image does not conform to the specifications, or the first specification image does not conform to the specifications.

[0107] In the above solution, by judging whether the product image has a white background, whether it is a flat image of the front or back of the product, and whether the number and clarity of the product images meet the requirements, the product images can be standardized and unified, thereby improving the user experience.

[0108] The following describes a specific implementation method for checking the straps of children's clothing. In this case, the above-mentioned steps of checking the straps of children's clothing on product images may specifically include the following steps:

[0109] Determine whether the product image contains children's clothing strings, wherein the product image containing children's clothing strings indicates that the product image passes the image quality verification.

[0110] Specifically, for the children's clothing category, by analyzing product images uploaded by users, we ensure that all children's clothing-related product information complies with market and legal requirements, and reduce safety hazards such as suffocation caused by improper design of children's clothing straps.

[0111] As an implementation manner, if the product image contains children's clothing strings, the product verification result may be stored as: the image contains children's clothing strings.

[0112] In the above solution, by determining whether the product image contains children's clothing straps, it is ensured that the product information related to children's clothing complies with market and legal requirements, and safety hazards such as suffocation caused by improper design of children's clothing straps are reduced.

[0113] The following describes a specific implementation method for duplicate product verification. In this case, the above-mentioned steps of performing duplicate product verification on product images may specifically include the following steps:

[0114] Based on the product image, it is determined whether the product corresponding to the product image is a duplicate of an existing product, wherein the duplicate of the product is represented by the product image failing the duplicate product verification.

[0115] Specifically, first, by analyzing the product information filled in by the user, such as product category, product brand, product number, applicable population, product title and product main picture, it is possible to verify whether the product submitted by the user is a duplicate of existing products or has a high homogeneity ratio.

[0116] As an implementation method, if a product is a duplicate of an existing product, the product verification result may be stored as: there is a duplicate / homogeneous product, the link of the duplicate / homogeneous product is xxx, and the similarity is xxx.

[0117] In addition, by analyzing the carousel images uploaded by users, it is possible to verify whether they contain elements of well-known brands. If so, it can be regarded as appearance plagiarism, and the product verification result is stored as: the product is highly similar to xxx elements and does not meet the platform requirements.

[0118] In the above solution, the product image is used to determine whether the product is a duplicate of an existing product, thereby realizing duplicate product verification, effectively identifying duplicate products, copied appearances, and homogeneous products, maintaining fair competition in the market, and improving product uniqueness.

[0119] Furthermore, based on the above embodiment, the above step S104 may specifically include the following steps:

[0120] Step 1): If the product review result indicates that the product has failed the review, modification information is output to the user.

[0121] Step 2): If the product review result indicates that the product has passed the review, the product corresponding to the product information is put on the shelves.

[0122] It should be noted that the above steps 1) and 2) correspond to two different situations of product review results, and therefore belong to parallel solutions, not sequential execution solutions.

[0123] In the above solution, product information can be processed differently according to the product review results, thereby ensuring that users can obtain feedback in a timely manner.

[0124] Please refer to Figure 2 , Figure 2 This is a diagram of the overall architecture of a product information review solution provided in an embodiment of the present application. The solution can include four modules: a product information entry module, a machine review module, a manual review module, and a product processing module.

[0125] The product information entry module is primarily responsible for entering product information. This information includes both textual and image modal information. Textual modal information includes the product title, category, attributes, release date, price, target demographics, and sizes. Image modal information includes carousel images and outfit images.

[0126] The machine review module automatically verifies product information submitted by users using an algorithmic model to ensure data accuracy and compliance. The module supports multiple review types and implements an efficient review process by invoking algorithmic models in parallel. Effective machine review can significantly improve review efficiency, reduce labor costs, and enhance the user experience.

[0127] As an implementation, the machine review module configures review rules based on product categories. When creating a product, the machine review module monitors data changes, queries MongoDB for the corresponding machine review policy based on the product category, and invokes multiple algorithm models in parallel to perform a comprehensive review of different product types. The review results are ultimately stored in Elasticsearch for subsequent retrieval and analysis.

[0128] When product information is modified, the product information entry module sends the modified content to the message queue. The machine review module continuously monitors this message queue and, upon receiving the modified information, compares it with the original product information. Based on the product category, the module queries MongoDB for the corresponding machine review policy and applies the corresponding review rules only to the modified product information. The system then concurrently calls multiple algorithm models for machine review and stores the review results in Elasticsearch.

[0129] Therefore, this solution introduces an efficient machine audit module that automatically audits product information by concurrently invoking multiple algorithm models. This module monitors changes in product information in real time and flexibly invokes appropriate audit strategies based on product categories, significantly improving audit speed and accuracy.

[0130] The manual review module is primarily used to review the results of the machine review module and manually review product information that has not been machine-reviewed. Reviewers can view the machine review results and conduct a review based on the required review standards. If the machine review results are disputed, human reviewers will intervene for further evaluation. In addition, manual review provides additional protection for certain special products (such as luxury goods and limited edition items).

[0131] Therefore, this solution incorporates a comprehensive manual review process. Even if machine review errors occur, the manual review module can review the machine review results to ensure the accuracy of the final review. Reviewers can view all relevant information through a unified interface, allowing them to make more accurate judgments.

[0132] The product processing module promptly provides feedback on product review results to the uploader. If a product fails review, detailed rejection reasons are provided to assist users in making modifications. This module also updates product statuses, such as marking them as "pending revision" or "approved." This status management feature ensures system transparency, allowing users to track product review progress in real time. The module also records the results and process of each review for subsequent tracking and analysis.

[0133] Therefore, this solution introduces a status management feature within the product processing module. This module categorizes product status based on review results and automatically sends notifications to the uploader. This feature improves review transparency and ensures that uploaders receive timely feedback. The results and progress of each review are recorded, enabling the system to track, analyze, and optimize the review process.

[0134] In summary, this solution introduces four modules: product information entry module, machine review module, manual review module and product processing module. The designs of these four modules coordinate and work with each other to ensure the overall template is clear, the process is quickly processed, and the convenience of use is increased.

[0135] Please refer to Figure 3 , Figure 3 This is a structural block diagram of a product information review device provided in an embodiment of the present application, wherein the product information review device 300 includes: an acquisition module 301, used to obtain product information input by a user, wherein the product information includes product text and product image; a verification module 302, used to verify the product text and the product image respectively to obtain corresponding product verification results; a receiving module 303, used to receive a product review result from a reviewer based on the product verification result; and a processing module 304, used to process the product information according to the product review result.

[0136] In the above solution, by introducing a machine review mechanism, electronic equipment is used to perform machine review of product text and product images, thereby improving the accuracy and efficiency of product information review. In addition, after the product verification results are obtained based on machine review, manual review can be performed to review the product verification results, thereby ensuring the accuracy of the product verification results, and then the product information can be processed accordingly based on the product review results.

[0137] Furthermore, based on the above embodiment, the verification module 302 is specifically used to: perform at least one of the following verifications on the product text: category verification, attribute verification, sales information verification, title structure verification, and size verification; and perform at least one of the following verifications on the product image: image quality verification, children's clothing strap verification, and duplicate product verification.

[0138] In the above scheme, during the process of reviewing product information, not only the text description and image of the product are considered, but also multiple dimensions such as the product attributes, categories, prices, and sales information are combined to ensure the comprehensiveness and effectiveness of the review results, thereby improving the accuracy of the review of product information.

[0139] Furthermore, based on the above embodiment, the product information includes product title, applicable population, product attributes and product category, and the verification module 302 is specifically used to: input the product information into the category prediction model to obtain the predicted category output by the category prediction model; determine whether the predicted category is consistent with the product category, wherein the consistency between the predicted category and the product category indicates that the product text has passed the category verification.

[0140] In the above scheme, by inputting the product information into the category prediction model, the predicted category of the product can be obtained, and then by comparing the above predicted category with the product category, the product category can be verified.

[0141] Furthermore, based on the above embodiment, the product information includes product categories and product attributes, and the product attributes include general attributes, applicable seasons, and main colors of the product. The verification module 302 is specifically used to: input the product information into the attribute prediction model to obtain the predicted attributes output by the attribute prediction model; determine whether the predicted attributes are consistent with the product attributes, wherein the consistency between the predicted attributes and the product attributes indicates that the product text has passed the attribute verification.

[0142] In the above scheme, by inputting the product information into the attribute prediction model, the predicted attributes of the product can be obtained, and then by comparing the above predicted attributes with the product attributes, the product category can be verified.

[0143] Further, based on the above embodiment, the product information includes sales information, and the sales information includes sales time and sales price. The verification module 302 is specifically used to: determine whether the sales time exceeds the preset time, wherein the sales time exceeding the preset time indicates that the product text has not passed the sales information verification; and determine whether the sales price exceeds the preset price, wherein the sales price exceeding the preset price indicates that the product text has not passed the sales information verification, and the preset price includes the average price of the product under the brand corresponding to the product information, the highest sales price within the preset time period under the brand, and the lowest sales price.

[0144] In the above scheme, by comparing the release time with the preset time, products with too long release time can be screened out; similarly, by comparing the release price with the pre-sale price, products with too high or too low release prices can be screened out, thereby maintaining fair competition in the market and improving the user experience.

[0145] Furthermore, based on the above embodiment, the product information includes a product title, and the verification module 302 is specifically used to: split the product title into different types of segments; determine whether each segment complies with the naming specification, wherein each segment complies with the naming specification, indicating that the product text has passed the title structure verification.

[0146] In the above solution, by structuring the product title and splitting the product title into different types of segments, it is possible to judge whether each segment complies with the naming specification, thereby improving the accuracy of the product title review.

[0147] Furthermore, based on the above embodiment, the product information includes product size, and the verification module 302 is specifically configured to: determine whether the product size is in a standard size chart, wherein if the product size is not in the standard size chart, it indicates that the product text has failed the size verification; and determine whether the product size matches the applicable population, wherein if the product size does not match the applicable population, it indicates that the product text has failed the size verification.

[0148] In the above solution, by determining whether the product size is in the standard size table and whether the product size matches the applicable population, the size of each product is standardized, thereby improving the user experience.

[0149] Furthermore, based on the above embodiment, the verification module 302 is specifically used to: determine whether the product image complies with preset rules, wherein the compliance of the product image with the preset rules indicates that the product image has passed the image quality verification, and the preset rules include that the product image has a white background, the product image is a tiled image of the front or back of the product, and the quantity and clarity of the product images meet the requirements.

[0150] In the above solution, by judging whether the product image has a white background, whether it is a flat image of the front or back of the product, and whether the number and clarity of the product images meet the requirements, the product images can be standardized and unified, thereby improving the user experience.

[0151] Furthermore, based on the above embodiment, the verification module 302 is specifically used to determine whether the product image contains children's clothing strings, wherein the presence of children's clothing strings in the product image indicates that the product image has passed the image quality verification.

[0152] In the above solution, by determining whether the product image contains children's clothing straps, it is ensured that the product information related to children's clothing complies with market and legal requirements, and safety hazards such as suffocation caused by improper design of children's clothing straps are reduced.

[0153] Furthermore, based on the above embodiment, the verification module 302 is specifically used to: determine whether the product corresponding to the product image is a duplicate of an existing product based on the product image, wherein the duplication of the product with the existing product indicates that the product image has failed the duplicate product verification.

[0154] In the above solution, the product image is used to determine whether the product is a duplicate of an existing product, thereby realizing duplicate product verification, effectively identifying duplicate products, copied appearances, and homogeneous products, maintaining fair competition in the market, and improving product uniqueness.

[0155] Furthermore, based on the above embodiment, the processing module 304 is specifically used to: if the product review result indicates that the product has not passed the review, output modification information to the user; if the product review result indicates that the product has passed the review, put the product corresponding to the product information on the shelves.

[0156] In the above solution, product information can be processed differently according to the product review results, thereby ensuring that users can obtain feedback in a timely manner.

[0157] Please refer to Figure 4 , Figure 4This is a block diagram of the structure of an electronic device provided in an embodiment of the present application. The electronic device 400 includes: at least one processor 401, at least one communication interface 402, at least one memory 403, and at least one communication bus 404. Among them, the communication bus 404 is used to realize direct connection and communication between these components, the communication interface 402 is used to communicate signaling or data with other node devices, and the memory 403 stores machine-readable instructions executable by the processor 401. When the electronic device 400 is running, the processor 401 communicates with the memory 403 via the communication bus 404, and the above-mentioned product information review method is executed when the machine-readable instructions are called by the processor 401.

[0158] For example, the processor 401 of the embodiment of the present application reads a computer program from the memory 403 through the communication bus 404 and executes the computer program to implement the following method: obtaining product information input by a user, wherein the product information includes product text and product image; verifying the product text and the product image respectively to obtain corresponding product verification results; receiving the product review result of the reviewer based on the product verification result; and processing the product information according to the product review result.

[0159] Among them, the processor 401 includes one or more, which can be an integrated circuit chip with signal processing capabilities. The above-mentioned processor 401 can be a general-purpose processor, including a central processing unit (CPU), a micro control unit (MCU), a network processor (NP) or other conventional processors; it can also be a special-purpose processor, including a neural network processor (NPU), a graphics processing unit (GPU), a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components. Moreover, when there are multiple processors 401, some of them can be general-purpose processors and the other part can be special-purpose processors.

[0160] The memory 403 includes one or more, which may be, but is not limited to, random access memory (RAM), read only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), etc.

[0161] I understand. Figure 4 The structure shown is for illustration only. The electronic device 400 may also include Figure 4 More or fewer components than shown, or with Figure 4 Different configurations shown. Figure 4 Each component shown in the figure can be implemented using hardware, software, or a combination thereof. In the embodiments of the present application, the electronic device 400 can be, but is not limited to, a physical device such as a desktop computer, a laptop computer, a smartphone, a smart wearable device, an in-vehicle device, or a virtual device such as a virtual machine. In addition, the electronic device 400 does not necessarily have to be a single device, but can also be a combination of multiple devices, such as a server cluster, etc.

[0162] The embodiment of the present application also provides a computer program product, including a computer program stored on a computer-readable storage medium, the computer program including computer program instructions. When the computer program instructions are executed by a computer, the computer can execute the steps of the product information review method in the above embodiment, for example including: Step S101: Obtain product information input by the user, wherein the product information includes product text and product image. Step S102: Verify the product text and product image respectively to obtain the corresponding product verification results. Step S103: Receive the product review results of the reviewer based on the product verification results. Step S104: Process the product information according to the product review results.

[0163] An embodiment of the present application further provides a computer-readable storage medium, wherein the computer-readable storage medium stores computer program instructions. When the computer program instructions are executed by a computer, the computer executes the commodity information review method described in the aforementioned method embodiment.

[0164] In the embodiments provided in this application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are merely schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some communication interface, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0165] In addition, the units described as separate components may or may not be physically separate, and 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 may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0166] Furthermore, the functional modules in each embodiment of the present application can be integrated together to form an independent part, or each module can exist independently, or two or more modules can be integrated to form an independent part.

[0167] It should be noted that if the function is implemented in the form of a software function module 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 the present application, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the method described in each embodiment of the present application. The aforementioned storage medium includes: various media that can store program codes, such as a USB flash drive, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0168] In this document, relational terms such as first and second, etc. are used merely to distinguish one entity or operation from another entity or operation, but do not necessarily require or imply any actual relationship or order between these entities or operations.

[0169] The above description is merely an embodiment of the present application and is not intended to limit the scope of protection of the present application. For those skilled in the art, various modifications and variations of the present application are possible. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present application shall be included in the scope of protection of the present application.

Claims

1. A commodity information review method, characterized in that: include: Acquire product information input by a user, wherein the product information includes product text and product image; Verifying the product text and the product image respectively to obtain corresponding product verification results; Receive the product review results from the reviewer based on the verification results of the product; The product information is processed according to the product review result.

2. The commodity information review method according to claim 1, characterized in that: The verifying the product text and the product image respectively to obtain corresponding product verification results includes: Perform at least one of the following verifications on the product text: category verification, attribute verification, sales information verification, title structure verification, and size verification; and The product image is subjected to at least one of the following verifications: image quality verification, children's clothing strap verification, and duplicate product verification.

3. The commodity information review method according to claim 2, characterized in that: The product information includes the product title, applicable population, product attributes and product category. The category verification of the product text includes: Inputting the product information into a category prediction model to obtain a predicted category output by the category prediction model; Determining whether the predicted category is consistent with the product category, wherein the consistency between the predicted category and the product category indicates that the product text passes the category verification; or, The product information includes product categories and product attributes. The product attributes include general attributes, applicable seasons, and main colors of the product. The attribute verification of the product text includes: Inputting the commodity information into an attribute prediction model to obtain predicted attributes output by the attribute prediction model; It is determined whether the predicted attribute is consistent with the commodity attribute, wherein the consistency between the predicted attribute and the commodity attribute indicates that the commodity text passes the attribute verification.

4. The commodity information review method according to claim 2, characterized in that: The product information includes sales information, which includes sales time and sales price. Verifying the sales information on the product text includes: Determining whether the release time exceeds a preset time, wherein the release time exceeding the preset time indicates that the product text has failed the release information verification; and Determining whether the selling price exceeds a preset price, wherein if the selling price exceeds the preset price, it indicates that the product text has failed the selling information verification, and the preset price includes an average price of products under the brand corresponding to the product information, a highest selling price under the brand within a preset time period, and a lowest selling price; or, The product information includes a product title, and performing the title structure check on the product text includes: Splitting the product title into different types of segments; Determining whether each segment complies with a naming specification, wherein compliance with the naming specification indicates that the product text has passed the title structure verification; or, The product information includes product size, and performing the size verification on the product text includes: Determining whether the product size is in a standard size chart, wherein if the product size is not in the standard size chart, it indicates that the product text has failed the size verification; and Determine whether the product size matches the applicable population, wherein if the product size does not match the applicable population, it indicates that the product text has failed the size verification.

5. The commodity information review method according to claim 2, characterized in that: Performing the image quality check on the product image includes: Determining whether the product image meets preset rules, wherein the product image meeting the preset rules indicates that the product image has passed the image quality verification, and the preset rules include that the product image has a white background, the product image is a tiled image of the front or back of the product, and the number and clarity of the product images meet requirements; or, Performing the children's clothing strap verification on the product image includes: It is determined whether the product image contains a children's clothing string, wherein the presence of the children's clothing string in the product image indicates that the product image has passed the image quality verification.

6. The commodity information review method according to claim 2, characterized in that: Performing duplicate product verification on the product image includes: Based on the product image, it is determined whether the product corresponding to the product image is a duplicate of an existing product, wherein the duplicate of the product is a sign that the product image fails the duplicate product check.

7. The commodity information review method according to any one of claims 1 to 4, characterized in that: The processing of the product information according to the product review result includes: If the product review result indicates that the product has failed the review, outputting modification information to the user; If the product review result indicates that it has passed the review, the product corresponding to the product information will be put on the shelves.

8. A computer program product, characterized in that The method comprises computer program instructions, which, when read and executed by a processor, executes the commodity information review method according to any one of claims 1 to 7.

9. An electronic device, characterized in that: include: processor, memory, and bus; The processor and the memory communicate with each other via the bus; The memory stores computer program instructions that can be executed by the processor, and the processor calls the computer program instructions to execute the product information review method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores computer program instructions, and when the computer program instructions are executed by a computer, the computer is caused to execute the commodity information review method according to any one of claims 1 to 7.

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