Commodity data processing method and device, storage medium and processor

Abstract

The application discloses a kind of commodity data processing method, device, storage medium and processor.Therein, the method includes: the commodity data of commodity object is collected, wherein commodity data includes at least one of the following: commodity picture, commodity video and the sentence for describing commodity;Commodity information of commodity object is generated by identifying commodity data;Based on the commodity information of commodity object, search to obtain similar target commodity of commodity object;Analysis target commodity, and return the commodity data of adjustment commodity object based on analysis result.The application solves the technical problem that commodity information accuracy is low.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of data processing, in particular to a commodity data processing method and device, a storage medium and a processor. BACKGROUND

[0002] At present, for the commodities published on the commodity platform, similar commodity information is matched through commodity classification and attributes to help users improve content filling quality and obtain better data feedback. However, this method cannot accurately match the commodity classification, resulting in low commodity information accuracy. In addition, related technologies can match the information of the same commodity through text analysis to help users improve content filling quality and data feedback. However, this method needs to prepare the text of the same commodity in advance, which is high in cost, and many merchants in the market will pile up keywords, which cannot be accurately matched through text analysis, thus resulting in the technical problem of low commodity information accuracy.

[0003] At present, there is no effective solution to the above problems. SUMMARY

[0004] The embodiments of the present application provide a commodity data processing method and device, a storage medium and a processor to at least solve the technical problem of low commodity information accuracy.

[0005] According to one aspect of the embodiments of the present application, a commodity data processing method is provided, comprising: collecting commodity data of a commodity object, wherein the commodity data comprises at least one of the following: commodity pictures, commodity videos and sentences for describing commodities; identifying the commodity data to generate commodity information of the commodity object; searching for target commodities similar to the commodity object based on the commodity information of the commodity object; and analyzing the target commodities and returning adjusted commodity data of the commodity object based on the analysis result.

[0006] According to another aspect of the embodiments of the present application, another commodity data processing method is provided, comprising: displaying the collected commodity data of a commodity object on an operation interface, wherein the commodity data comprises at least one of the following: commodity pictures, commodity videos and sentences for describing commodities; displaying commodity information of the commodity object on the operation interface, wherein the commodity information of the commodity object is generated by identifying the commodity data; displaying target commodities similar to the commodity object searched on the operation interface; and displaying adjusted commodity data of the commodity object on an adjustment page on the operation interface, wherein the adjusted commodity data of the commodity object is generated by analyzing the target commodities.

[0007] According to another aspect of the embodiments of the present application, another method for processing product data is provided, including: displaying product data of a product object collected by a shooting device on an operation interface, wherein the product data includes at least one of the following: product pictures, product videos and sentences for describing the product; adjusting a resolution of a display result on the operation interface when the resolution is lower than a predetermined resolution; identifying the product data when the resolution of the display result is higher than the predetermined resolution, and generating product information of the product object; displaying target products similar to the product object searched on the operation interface; analyzing the target products, and displaying adjusted product data of the product object based on an analysis result on the operation interface.

[0008] According to another aspect of the embodiments of the present application, another method for processing product data is provided, including: inputting product data of a product object on an input page of an operation interface, wherein the product data includes at least one of the following: product pictures, product videos and sentences for describing the product; identifying the product data, and searching target products similar to the product object based on the product data; displaying an adjustment result of the product data of the product object on a publishing page of the operation interface, wherein the adjustment result is returned based on an analysis result of the target products.

[0009] According to another aspect of the embodiments of the present application, a device for processing product data is provided, including: a collecting unit configured to collect product data of a product object, wherein the product data includes at least one of the following: product pictures, product videos and sentences for describing the product; a first identifying unit configured to identify the product data, and generate product information of the product object; a searching unit configured to search target products similar to the product object based on the product information of the product object; and a first analyzing unit configured to analyze the target products, and return adjusted product data of the product object based on an analysis result.

[0010] According to another aspect of the embodiments of the present application, another device for processing product data is provided, including: a first displaying unit configured to display product data of a product object collected on an operation interface, wherein the product data includes at least one of the following: product pictures, product videos and sentences for describing the product; a second displaying unit configured to display product information of the product object on the operation interface, wherein the product information of the product object is generated by identifying the product data; a third displaying unit configured to display target products similar to the product object searched on the operation interface; and a fourth displaying unit configured to display adjusted product data of the product object on an adjustment page of the operation interface, wherein the adjusted product data of the product object is generated by analyzing the target products.

[0011] According to another aspect of the embodiments of the present application, there is further provided another apparatus for processing product data, comprising: a fourth display unit configured to display product data of a product object captured by a photographing device on an operation interface, wherein the product data comprises at least one of a product picture, a product video and a statement describing the product; an adjusting unit configured to adjust a resolution of a display result on the operation interface when the resolution is lower than a predetermined resolution; a second identifying unit configured to identify the product data when the resolution of the display result is higher than the predetermined resolution, and generate product information of the product object; a fifth display unit configured to display a target product similar to the product object searched on the operation interface; and a second analyzing unit configured to analyze the target product and return adjusted product data of the product object based on an analysis result on the operation interface.

[0012] According to another aspect of the embodiments of the present application, there is further provided another apparatus for processing product data, comprising: an input unit configured to input product data of a product object in an input page on an operation interface, wherein the product data comprises at least one of a product picture, a product video and a statement describing the product; a third identifying unit configured to identify the product data and search a target product similar to the product object based on the product data; and a second display unit configured to display an adjustment result of the product data of the product object on a publishing page on the operation interface, wherein the adjustment result is returned based on an analysis result of the target product.

[0013] According to another aspect of the embodiments of the present application, there is further provided a computer readable storage medium comprising a stored program, wherein the program, when executed, causes a device on which the computer readable storage medium is located to perform the method for processing product data according to the embodiments of the present application.

[0014] According to another aspect of the embodiments of the present application, there is further provided a processor configured to execute a program, wherein the program, when executed, performs the method for processing product data according to the embodiments of the present application.

[0015] According to another aspect of the embodiments of the present application, there is further provided a system for processing product data, comprising: a processor; and a memory connected to the processor and configured to provide the processor with instructions for processing the following processing steps: capturing product data of a product object, wherein the product data comprises at least one of a product picture, a product video and a statement describing the product; identifying the product data and generating product information of the product object; searching a target product similar to the product object based on the product information of the product object; and analyzing the target product and returning adjusted product data of the product object based on an analysis result.

[0016] In this embodiment of the invention, product data of a product object is collected, wherein the product data includes at least one of the following: product images, product videos, and statements describing the product; the product data is identified to generate product information for the product object; based on the product information of the product object, target products similar to the product object are searched; the target products are analyzed, and the product data of the product object is adjusted based on the analysis results. In related technologies, for products published on product platforms, information of similar products is usually matched by product categories and attributes to help users improve the quality of content filling and obtain better data feedback. However, this method has low information accuracy because product categories cannot be accurately matched. In addition, information of the same product can be matched by text parsing to help users improve the quality of content filling and data feedback. However, this method requires the preparation of text of the same product in advance, and many merchants in the market will stuff keywords, which cannot be accurately matched by text parsing. In this application, after obtaining the product data of the product object, the product data needs to be identified to generate product information, and then based on the product information, the product data is adjusted. This method searches for similar products within the product information, analyzes them, and generates adjusted product data based on the analysis results. Adjusting the product object using this data ensures accurate matching between the product object and the target product. This avoids the inaccuracy and low accuracy of matching product information that occurs when matching similar products based on product categories and attributes. It also avoids the inaccuracy caused by pre-prepared text and keyword stuffing when matching similar products through text parsing. Therefore, it solves the technical problem of low product information accuracy and achieves the technical effect of improving product information accuracy. Attached Figure Description

[0017] The accompanying drawings, which are included to provide a further understanding of the invention and form part of this application, illustrate exemplary embodiments of the invention and, together with their description, serve to explain the invention and do not constitute an undue limitation thereof. In the drawings:

[0018] Figure 1 This is a hardware structure block diagram of a computer terminal (or mobile device) for implementing a method for processing commodity data according to an embodiment of the present invention.

[0019] Figure 2 This is a flowchart of a product data processing method according to an embodiment of the present invention;

[0020] Figure 3 This is a flowchart of another method for processing commodity data according to an embodiment of the present invention;

[0021] Figure 4 This is a flowchart of another method for processing commodity data according to an embodiment of the present invention;

[0022] Figure 5 This is a flowchart of another method for processing commodity data according to an embodiment of the present invention;

[0023] Figure 6 This is a flowchart of another method for processing commodity data according to an embodiment of the present invention;

[0024] Figure 7 This is a flowchart of another method for processing commodity data according to an embodiment of the present invention;

[0025] Figure 8 This is a schematic diagram illustrating a scenario of processing commodity data according to an embodiment of the present invention;

[0026] Figure 9 This is a schematic diagram of a commodity data processing device according to an embodiment of the present invention;

[0027] Figure 10 This is a schematic diagram of another commodity data processing apparatus according to an embodiment of the present invention;

[0028] Figure 11 This is a schematic diagram of another commodity data processing apparatus according to an embodiment of the present invention;

[0029] Figure 12 This is a schematic diagram of another commodity data processing apparatus according to an embodiment of the present invention; and

[0030] Figure 13 This is a structural block diagram of a computer terminal according to an embodiment of the present invention. Detailed Implementation

[0031] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0032] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0033] First, some nouns or terms that appear in the description of the embodiments of this application shall be interpreted as follows:

[0034] Artificial intelligence (AI) is a technology that uses computer programs to represent human intelligence. It is the ability of a system to correctly interpret external data, learn from this data, and use this knowledge to achieve specific goals and tasks through flexible adaptation.

[0035] Artificial Neural Network (ANN) is a mathematical or computational model that mimics the structure and function of biological neural networks, consisting of a large number of interconnected artificial neurons performing computations.

[0036] Artificial neural network models are mathematical models built upon mathematical models of neurons, and are represented by network topology, node characteristics, and learning rules.

[0037] Example 1

[0038] According to an embodiment of the present invention, an embodiment of a method for processing commodity data is also provided. It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions. Furthermore, although a logical order is shown in the flowchart, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0039] The method embodiment provided in Embodiment 1 of this application can be executed on a mobile terminal, computer terminal, or similar computing device. Figure 1 A hardware block diagram of a computer terminal (or mobile device) for implementing a method for processing commodity data is shown. Figure 1As shown, the computer terminal 10 (or mobile device 10) may include one or more processors 102 (shown as 102a, 102b, ..., 102n in the figure) 102 (processor 102 may include, but is not limited to, a microprocessor MCU or a programmable logic device FPGA, etc.), a memory 104 for storing data, and a transmission device 106 for communication functions. In addition, it may also include: a display, an input / output interface (I / O interface), a universal serial bus (USB) port (which may be included as one of the ports of a BUS bus), a network interface, a power supply, and / or a camera. Those skilled in the art will understand that... Figure 1 The structure shown is for illustrative purposes only and does not limit the structure of the aforementioned electronic device. For example, computer terminal 10 may also include... Figure 1 The more or fewer components shown, or having the same Figure 1 The different configurations shown.

[0040] It should be noted that the aforementioned one or more processors 102 and / or other data processing circuits are generally referred to herein as "data processing circuits". These data processing circuits may be embodied, in whole or in part, in software, hardware, firmware, or any other combination thereof. Furthermore, the data processing circuits may be a single, independent processing module, or may be integrated, in whole or in part, into any other element within the computer terminal 10 (or mobile device). As involved in the embodiments of this application, the data processing circuits serve as a processor control mechanism (e.g., selection of a variable resistor termination path connected to an interface).

[0041] The memory 104 can be used to store software programs and modules of application software, such as the program instructions / data storage device corresponding to the commodity data processing method in this embodiment of the invention. The processor 102 executes various functional applications and data processing by running the software programs and modules stored in the memory 104, thereby realizing the commodity data processing method described above. The memory 104 may include high-speed random access memory, and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory 104 may further include memory remotely located relative to the processor 102, and these remote memories can be connected to the computer terminal 10 via a network. Examples of such networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0042] The transmission device 106 is used to receive or send data via a network. Specific examples of the network described above may include a wireless network provided by the communication provider of the computer terminal 10. In one example, the transmission device 106 includes a Network Interface Controller (NIC), which can connect to other network devices via a base station to communicate with the Internet. In another example, the transmission device 106 may be a Radio Frequency (RF) module, used for wireless communication with the Internet.

[0043] The display can be, for example, a touchscreen liquid crystal display (LCD) that allows the user to interact with the user interface of the computer terminal 10 (or mobile device).

[0044] It should be noted here that, in some optional embodiments, the above... Figure 1 The computer device (or mobile device) shown may include hardware elements (including circuitry), software elements (including computer code stored on a computer-readable medium), or a combination of both hardware and software elements. It should be noted that... Figure 1 This is only one instance of a specific particular instance and is intended to illustrate the types of components that may exist in the aforementioned computer device (or mobile device).

[0045] exist Figure 1 Under the operating environment shown, this application provides the following: Figure 2 The product data processing method shown is illustrated. It should be noted that the product data processing method in this embodiment is based on... Figure 1 The mobile terminal in the illustrated embodiment is executed.

[0046] Figure 2 This is a flowchart of a product data processing method according to an embodiment of the present invention. Figure 2 As shown, the method may include the following steps:

[0047] Step S202: Collect product data of the product object.

[0048] In the technical solution provided by step S202 of the present invention, the product data may include at least one of the following: product images, product videos, and statements used to describe the product.

[0049] In this embodiment, after the user operates the client and enters the settings page, they can collect product data of the product object in step S202. This can be done by selecting to use the client's camera or other image acquisition device to capture an image of the product object, or by directly selecting a pre-stored image of the product object and a description of the product in the client. The product object image can include product pictures and videos, thereby collecting product data. Optionally, the product pictures and videos may also include descriptions of the product.

[0050] Optionally, as an embodiment, step S202, acquiring an image of the product object, includes: providing a settings page with a shooting option. Based on triggering the shooting option, a shooting component is invoked to capture an image of the product object, for example, the image of the product object is an image of a cup.

[0051] Optionally, a shooting option can be provided in the client's settings page. When the user triggers the shooting option, the client invokes a shooting component (such as a camera) to capture an image of the product object. In another example, when the user triggers the shooting option, the interface of the shooting component corresponding to the photo album application can also be invoked, allowing the user to select a pre-shot image of the product object from the photo album application.

[0052] Step S204: Identify product data and generate product information for the product object.

[0053] In the technical solution provided in step S204 of the present invention, after collecting the product data of the product object, the user can operate the client to call the data recognition algorithm, and input the collected product data into the data recognition model. In the data recognition model, the collected product data is recognized by the data recognition algorithm to obtain the product information of the product object. Optionally, the above-mentioned data recognition model can be trained by a pre-collected product dataset.

[0054] In this embodiment, when the product data is an image, the obtained product information can be the product category, product attribute information, and appearance feature information of the product object, etc.; when the product data is a video, the obtained product information can be the product category, product three-dimensional structure, product attribute information, and appearance feature information of the product object, etc.; when the product data is a statement used to describe the product, the obtained product information can be basic information such as the product name, type, and specifications.

[0055] Optionally, the product information in this embodiment includes category (furniture and daily necessities), style (Chinese style), popular elements (solid color), material (plastic), popular tags (new and unused plastic cup), and frequently used options (new).

[0056] Step S206: Based on the product information of the product object, search for target products similar to the product object.

[0057] In the technical solution provided by step S206 of the present invention, after obtaining the product information of the product object, a target product similar to the product object can be searched based on the obtained product information. For example, the user can search based on the attribute information of the product object (general attribute information, personalized attribute information, etc.), and the obtained attribute information is used as the attribute information of the target product. In this way, a target product similar to the product object can be determined.

[0058] In this embodiment, the user can pre-establish an information database. Each time the user searches based on the product information of a product object and obtains the target product, the product information of the target product can be stored in the database, allowing the database to be updated in real time. This way, when the user makes the next search, the target product can be matched more accurately. This avoids the problem of low accuracy of product information due to the inability to accurately match the product information of the product object, thus solving the technical problem of low accuracy of product information and achieving the technical effect of improving the accuracy of product information.

[0059] Step S208: Analyze the target product and return the product data of the adjusted product object based on the analysis results.

[0060] In the technical solution provided by step S208 of the present invention, after obtaining the target product, the target product can be analyzed to obtain the analysis results, and based on the analysis results, product data for adjusting the product object can be obtained. Optionally, the user's product object can be adjusted according to the product data of the product object, so as to guide the user to modify the product information of the product object, so that the product object can be distinguished from the target product to the greatest extent, thereby reducing the competitiveness of the user's product object.

[0061] Optionally, the product data used to adjust the product object can be the same product data between the user's product object and the target product after the target product has been analyzed.

[0062] In related technologies, information on similar products is usually matched by product categories and attributes to help users improve the quality of their content and obtain better data feedback. However, this method results in low accuracy of product information because product categories cannot be accurately matched.

[0063] However, through steps S202 to S208 of this application, after obtaining the product data of the product object, it is necessary to identify the product data, generate product information, and then search based on this product information to obtain target products similar to the product object. Then, the target products are analyzed, and product data for adjusting the product object is generated based on the analysis results. Adjusting the product object based on this product data can accurately match the product object and the target product. This avoids the inaccurate matching of product information and low information accuracy caused by matching information of similar products through product classification and attributes. It also avoids the inaccurate matching of product information caused by keyword stuffing when matching information of the same product through text parsing. Thus, it solves the technical problem of low product information accuracy and achieves the technical effect of improving the accuracy of product information.

[0064] The method described in this embodiment will be further explained below.

[0065] As an optional implementation, step S206, based on the product information of the product object, searches for target products similar to the product object, including: extracting product content from the product information, wherein the product content includes product attributes and / or product features, and the product attributes include: general attributes and personalized attributes; and searching from the product library based on the product content to obtain target products similar to the product object.

[0066] In this embodiment, after obtaining the product information of a product object, product content is extracted from the product information. Then, based on this product content, a search is performed in the product database to obtain target products similar to the product object. The product content may include product attributes and / or product features. Product attributes may include general attributes and personalized attributes, etc. Optionally, the aforementioned product database can be a pre-established collection containing a large number of product images, product videos, and statements describing products. Furthermore, after each acquisition of a product similar to the product object, the product data of that product can be added to the product database to ensure that the database is updated in real time. This allows for more accurate matching of target products, avoiding the problem of low information accuracy due to the inability to accurately match the product information of the product object, thus solving the technical problem of low product information accuracy and achieving the technical effect of improving the accuracy of product information.

[0067] The following section further describes the method of searching the product database based on product content to obtain target products similar to the product object in this embodiment.

[0068] As an optional embodiment, based on product content, a search is performed from a product library to obtain target products similar to the product object. This includes: when the product data is a product image, the product library consists of an image library containing products. The image content obtained by identifying the product image is compared with the image objects in the image library to calculate similarity and to find target images similar to the image content. These target images are used to display target products similar to the product object. The image content is obtained by using an artificial intelligence algorithm to identify the content of any area in the product image.

[0069] In this embodiment, when the product data is a product image, an artificial intelligence algorithm can be used to identify the content of any area in the product image to obtain the image content. Then, based on the obtained image content, a search is performed in the product database. The similarity between the image objects retrieved from the image database and the obtained image content is calculated to obtain the target image with the highest similarity to the image content. The product corresponding to this target image is then taken as the target product. The aforementioned product database consists of an image library containing products. This embodiment, by employing an artificial intelligence algorithm to perform content recognition on product images, can accurately and efficiently obtain the image content of product images. This allows for more precise matching of product images with target images in the product database, thus accurately obtaining the target product most similar to the product object. This solves the technical problem of not being able to accurately obtain the target product and achieves the technical effect of accurately obtaining the target product.

[0070] As an optional embodiment, based on product content, a search is performed from a product library to obtain target products similar to the product object, including: when the product data is a product video, the product library consists of a video library containing products, wherein the similarity calculation is performed between the video content obtained by identifying the product video and the video object in the video library, and a target video similar to the video content is searched to obtain the target video used to display the target product similar to the product object, wherein an artificial intelligence algorithm is used to identify the content of any frame of the product video.

[0071] In this embodiment, when the product data is a product video, any frame of the product video can be captured first. Then, an artificial intelligence algorithm is used to identify the captured frame image in the product video to obtain the frame image content. At this time, based on the obtained frame image content, a search is performed in the product library. The similarity between the video object searched from the product library and the obtained frame image content is calculated to obtain the target video with the highest similarity to the frame image content. The product corresponding to the target video is then taken as the target product. The product library is composed of a video library containing products.

[0072] Optionally, searching for video objects in the product library based on the obtained frame image content can be achieved by processing the videos of products in the product library to obtain a large number of video object frame images. Then, the frame images of the video objects are searched based on the obtained product video frame images to obtain the target video, and then the target product is obtained through the target video. This embodiment uses artificial intelligence algorithms to perform content recognition on the frame images of product videos, which can accurately and efficiently obtain the video content of product videos. This allows for more accurate matching of product videos with target videos in the product library, thus accurately obtaining the target product most similar to the product object. This solves the technical problem of not being able to accurately obtain the target product and achieves the technical effect of accurately obtaining the target product.

[0073] As an optional embodiment, based on product content, a search is performed from a product library to obtain target products similar to the product object. This includes: when the product data is a statement used to describe the product, the product library consists of a library containing statements describing the product; wherein, the semantics obtained from identifying the statement are compared with the statement objects in the statement library to calculate similarity, and a target statement similar to the statement used to describe the product is searched. The target statement is used to describe the target product similar to the product object, wherein an artificial intelligence algorithm is used to identify the semantics of the statement.

[0074] In this embodiment, when the product data consists of statements describing the product, an artificial intelligence algorithm is first used to identify the statements to obtain semantics. Then, based on the obtained semantics, a search is performed in the product database to obtain statement objects. An artificial intelligence algorithm is then used to identify these statement objects to obtain their semantics. Finally, a similarity calculation is performed between the semantics of the statement objects and the semantics of the statements describing the product to obtain the target statement with the highest similarity. The product corresponding to this target statement is then designated as the target product. The product database consists of a database of statements describing products. This embodiment, by employing an artificial intelligence algorithm to perform semantic recognition on statements describing products, can accurately and efficiently obtain the semantic content of these statements. This allows for more precise matching of the statements describing products with target statements in the product database, thus accurately obtaining the target product most similar to the product object. This solves the technical problem of not being able to accurately obtain target products and achieves the technical effect of accurately obtaining target products.

[0075] As an optional embodiment, analyzing the target product and returning adjusted product information based on the analysis results includes: using an analysis model to analyze the target product and obtaining analysis results, wherein the analysis model is a model that includes analytical factors for analyzing product competitiveness, and the analytical factors include at least one of the following: page views, clicks, purchase frequency, and title; obtaining modification data based on the analysis results; and using the modification data to update the product information of the product object and generate new product information for the product object.

[0076] In this embodiment, after obtaining a target product similar to the product object, an analysis model can be used to analyze the target product to obtain the analysis results. Then, based on the analysis results, modification data for adjusting the product object is obtained, and the product information of the product object is updated using the modification data to obtain the new product information of the product object. At this time, the product object containing the new product information can be distinguished from the target product to the greatest extent, which can reduce the competitiveness of the user's product object.

[0077] Optionally, the above-mentioned analysis model is a model that includes analytical factors for analyzing product competitiveness. It can be trained using analytical factor data, and these analytical factors may include at least one of the following: page views, clicks, purchase frequency, and title, etc. This embodiment analyzes the target product to modify the product object, which can greatly differentiate the product object from the target product, thereby reducing the competitiveness of the user's product object. This solves the technical problem of not being able to reduce the competitiveness of the user's product object and achieves the technical effect of reducing the competitiveness of the user's product object.

[0078] As an optional embodiment, analyzing the target product and returning adjusted product data for the product object based on the analysis results includes: comparing the product data of the target product with the product data of the current product object to obtain an analysis result consisting of the comparison result, wherein the analysis result includes content in the product data of the product object that does not meet the publishing conditions; and updating the product data of the product object.

[0079] In this embodiment, after obtaining the target product, it needs to be analyzed. This involves comparing the target product's data with the current product object's data to obtain comparison results. After obtaining multiple sets of comparison results, these results are combined to form an analysis result. Based on this analysis result, the product object's data is then updated. Optionally, the analysis result may include content in the product object's data that does not meet the publishing conditions. This embodiment, by analyzing the target product to update the product object's data, can significantly differentiate between the product object and the target product, thereby reducing the competitiveness of the user's product object and solving the technical problem of not being able to reduce the competitiveness of the user's product object, achieving the technical effect of reducing the competitiveness of the user's product object.

[0080] As an optional embodiment, updating the product information of a product object includes at least one of the following: cropping and replacing parts of a product image that do not meet the publishing conditions; cropping and replacing parts of a product video that do not meet the publishing conditions; deleting and replacing parts of statements used to describe the product that do not meet the publishing conditions.

[0081] In this embodiment, when the product data is a product image, updating the product information of the product object can be achieved by using an artificial intelligence algorithm to identify parts of the product image that do not meet the publishing conditions, and then cropping and replacing these parts to obtain a product object with updated product information. When the product data is a product video, any frame of the product video can be captured first, and then an artificial intelligence algorithm can be used to identify any frame that does not meet the publishing conditions. These frames can then be cropped and replaced to obtain a product object with updated product information. When the product data is a statement describing the product, an artificial intelligence algorithm can be used to identify parts of the statement that do not meet the publishing conditions, and then these parts can be deleted and replaced to obtain a product object with updated product information.

[0082] Optionally, the above-mentioned cropping, deletion, and replacement of the parts of the product data that do not meet the publishing conditions can be achieved by using artificial intelligence algorithms to identify the parts that meet the publishing conditions in a pre-established product library, and then using this data to fill the product data of the cropped and deleted parts that do not meet the publishing conditions. Alternatively, the product data that does not meet the publishing conditions can be directly deleted, and then the product data that meets the publishing conditions can be identified in the product library and replaced with product data that meets the publishing conditions. The choice here depends on the user's needs. The product library is a pre-established product library containing product data that meets the publishing conditions.

[0083] As an optional embodiment, when the product data is a statement used to describe the product, the geographical location of the product object is obtained, and the statement used to describe the product is updated based on at least one of the following methods: determining the expression of the statement in the local area based on the geographical location and replacing the statement, and deleting invalid words and trending words, and using recommended words.

[0084] In this embodiment, when the product data consists of statements describing the product, the geographical location of the product object can be obtained. Based on the obtained geographical location of the product object, the content expressed in the local context of the statements describing the product can be determined. Then, the statements describing the product can be replaced accordingly based on this content. Alternatively, after obtaining the geographical location of the product object, invalid and trending words in the statements describing the product can be deleted based on this geographical location. Then, recommended words with corresponding semantics can be obtained from the product database, and these recommended words can be used for the corresponding replacements. In this way, it is possible to adapt to different dialects in different geographical locations, satisfy users in various places, solve the technical problem of not being able to accurately recommend products, and achieve the technical effect of accurately recommending products.

[0085] As an optional embodiment, after returning the product data of the adjusted product object based on the analysis results, the method further includes: using dynamic bullet comments to display the updated product data of the product object.

[0086] In this embodiment, after updating the product data of the product object based on the obtained analysis results, the updated product data of the product object can be displayed by using dynamic pop-up messages. This allows for immediate viewing of the updated product information, achieving the goal of intuitively viewing the updated product data of the product object. This solves the technical problem of low efficiency in updating product data of the product object and achieves the technical effect of improving the efficiency of updating product data of the product object.

[0087] As an optional embodiment, after collecting product data of the product object, the method further includes: segmenting the frame images of the product image and / or product video to extract the product image; replacing the product image with a white background image; and automatically uploading the white background image to the corresponding recommendation backend, wherein the white background image is the image with the highest priority when adjusting the product data of the product object.

[0088] In this embodiment, since users may need white background images as product materials when publishing products on the platform, after collecting product data of the product object, if the product data is product images and / or product videos, the frame images of the product images and / or product videos can be segmented to extract product images. Then, the extracted product images are replaced with white background product images, and the white background product images are automatically uploaded to the corresponding recommendation backend. The white background image is the product image with the highest priority when adjusting the product data of the product object.

[0089] For example, the platform requires a product image to have a white background and a transparent background (a common product material) to make the product details more obvious. When a user needs a white background image, they can simply place the product image on a white background. Since the product details are more clearly displayed on the white background image, the resulting white background image can be recommended by the platform as an important image. In other words, the white background image has a higher recommendation level. This allows the platform to prioritize recommending white background images when adjusting the product data of a product image.

[0090] Optionally, the white background image can be placed in the merchant's recommended position or in the platform's traffic entry point.

[0091] This invention also provides another method for processing product data from the perspective of human-computer interaction.

[0092] Figure 3 This is a flowchart of another method for processing product data according to an embodiment of the present invention. Figure 3 As shown, the method may include the following steps:

[0093] Step S302: Display the collected product data of the product object on the operation interface, wherein the product data includes at least one of the following: product image, product video, and statement used to describe the product.

[0094] In the technical solution provided by step S302 of the present invention, after collecting the product data of the product object, the collected product data can be displayed on the operation interface. By displaying the collected product data on the operation interface, the collected product data can be viewed more intuitively, making it convenient for users to perform operations on the collected product data in real time, such as deletion or modification. Optionally, the product data may include at least one of the following: product images, product videos, and statements used to describe the product.

[0095] Step S304: Display the product information of the product object on the operation interface, wherein the product information of the product object is generated by recognizing product data.

[0096] In the technical solution provided by step S304 of the present invention, after obtaining the commodity data, the obtained commodity data can be identified to generate commodity information of the commodity object, and the generated commodity information of the commodity object can be displayed on the operation interface.

[0097] In this embodiment, when the product data is a product image, the obtained product information can include the product category, product attribute information, and appearance feature information of any part of the product object; when the product data is a product video, the obtained product information can include the product category, product three-dimensional structure, product attribute information, and appearance feature information of any part of the product object; when the product data is a statement used to describe the product, the obtained product information can include basic information such as the product name, type, and specifications. This embodiment, by displaying the obtained product information of the product object on the operation interface, allows for a more intuitive viewing of the acquired product information, facilitating immediate operation by the user.

[0098] Step S306: Display the target products that are similar to the product object obtained from the search on the operation interface.

[0099] In the technical solution provided by step S306 of the present invention, after obtaining the product information of the product object, a search can be performed in the product library based on the obtained product information to obtain target products similar to the product object, and the obtained target products are displayed on the operation interface. Optionally, the product library may consist of an image library containing products, a video library containing products, and a statement library containing descriptions of products. This embodiment, by displaying the obtained target products similar to the product object on the operation interface, allows for a more intuitive viewing of the obtained target products similar to the product object, facilitating users to perform operations on the obtained target products similar to the product object in real time.

[0100] Step S308: Display the product data of the product object to be adjusted on the adjustment page of the operation interface, wherein the product data of the product object to be adjusted is generated by analyzing the target product.

[0101] In the technical solution provided by step S308 of the invention, after obtaining the target product, the target product can be analyzed to obtain analysis results. Based on the analysis results, product data for adjusting the product object can be obtained. Then, the obtained product data for adjusting the product object is displayed on the adjustment page of the operation interface. Optionally, the user's product object can be adjusted according to the product data of the adjusted product object. This guides the user to modify the product information of the product object, so that the product object can be differentiated from the target product to the greatest extent, thereby reducing the competitiveness of the user's product object. This embodiment, by displaying the obtained product data of the adjusted product object on the operation interface, allows for a more intuitive view of the obtained product data of the adjusted product object, facilitating the user to operate on the obtained product data of the adjusted product object in real time.

[0102] The method described in this embodiment will be further described below.

[0103] As an optional embodiment, in step S306, after displaying the target product similar to the product object obtained from the search on the operation interface, the method further includes: popping up guidance information on the operation interface, wherein the guidance information includes defect information of the product information; and displaying adjustment information generated based on the guidance information on the operation interface.

[0104] In this embodiment, after displaying the target products similar to the searched product on the user interface, guidance information containing defect information about the product can pop up on the user interface. Then, adjustment information for the product can be generated based on this guidance information and displayed on the user interface. This embodiment analyzes the product information to obtain defect information, generating guidance information containing this defect. The adjustment information generated from this guidance allows for adjustments to the product, maximizing its differentiation from the target product and reducing the competitiveness of the user's product. By displaying the adjustment information generated based on the guidance information on the user interface, this embodiment provides a more intuitive view of the adjustment information and facilitates immediate action by the user.

[0105] This invention also provides another method for processing product data from the perspective of human-computer interaction.

[0106] Figure 4 This is a flowchart of another method for processing product data according to an embodiment of the present invention. Figure 4 As shown, the method may include the following steps:

[0107] Step S402: Display the product data of the product object collected by the shooting device on the operation interface, wherein the product data includes at least one of the following: product image, product video and statement used to describe the product.

[0108] In the technical solution provided by step S402 of the present invention, after collecting product data of the product object through the shooting device, the collected product data of the product object can be displayed on the operation interface. By displaying the collected product data on the operation interface, the collected product data can be viewed more intuitively. Optionally, the product data of the product object collected by the shooting device includes at least one of the following: product images, product videos, and statements describing the product. The shooting device can identify the statements describing the product in the product images or videos, convert them into text information, and display them on the operation interface.

[0109] Step S404: If the resolution displayed on the operation interface is lower than the predetermined resolution, adjust the resolution of the result displayed on the operation interface.

[0110] In the technical solution provided by step S404 of the present invention, the display resolution of the operation interface can be determined first. When the display resolution on the operation interface is lower than the predetermined resolution, the display resolution on the operation interface needs to be adjusted in order to better display the results. Optionally, the above display resolution is the resolution of the display results on the operation interface.

[0111] Step S406: If the resolution of the displayed result is higher than the predetermined resolution, identify the product data and generate product information for the product object.

[0112] In the technical solution provided by step S406 of the present invention, after determining that the display resolution on the operation interface is higher than the predetermined resolution, the product data of the product object collected by the shooting device is identified, and product information of the product object is generated.

[0113] In this embodiment, when the product data is a product image, the obtained product information can be the product category, product attribute information, and appearance feature information of any part of the product object; when the product data is a product video, the obtained product information can be the product category, product three-dimensional structure, product attribute information, and appearance feature information of any part of the product object; when the product data is a statement used to describe the product, the obtained product information can be basic information such as the product name, type, and specifications.

[0114] Step S408: Display the target products that are similar to the product object obtained from the search on the operation interface.

[0115] In the technical solution provided by step S408 of the present invention, after obtaining the product information of the product object, a search can be performed in the product library based on the obtained product information to obtain target products similar to the product object, and the obtained target products are displayed on the operation interface. Optionally, the product library may consist of an image library containing products, a video library containing products, and a statement library containing descriptions of products. This embodiment, by displaying the obtained target products similar to the product object on the operation interface, allows for a more intuitive viewing of the obtained target products similar to the product object, facilitating users to perform operations on the obtained target products similar to the product object in real time.

[0116] Step S410: Analyze the target product and display the product data of the adjusted product object based on the analysis results on the operation interface.

[0117] In the technical solution provided by step S410 of the present invention, after obtaining the target product, the target product can be analyzed to obtain analysis results. Based on the analysis results, product data for adjusting the product object can be obtained, and then the obtained product data for adjusting the product object can be displayed on the operation interface. Optionally, the user's product object can be adjusted according to the product data of the adjusted product object. This can guide the user to modify the product information of the product object, so that the product object can be distinguished from the target product to the greatest extent, thereby reducing the competitiveness of the user's product object. This embodiment, by displaying the obtained product data of the adjusted product object on the operation interface, allows for a more intuitive view of the obtained product data of the adjusted product object, facilitating the user to operate on the obtained product data of the adjusted product object in real time.

[0118] This invention also provides another method for processing product data from the perspective of human-computer interaction.

[0119] Figure 5 This is a flowchart of another method for processing product data according to an embodiment of the present invention. Figure 5 As shown, the method may include the following steps:

[0120] Step S502: Enter product data of the product object on the input page of the operation interface. The product data includes at least one of the following: product image, product video, and statement used to describe the product.

[0121] In the technical solution provided by step S502 of the present invention, product data of a product object can be entered into the input page of the operation interface. The product data includes at least one of the following: product images, product videos, and statements describing the product. Optionally, the product data can be product images or videos captured by an image acquisition device, or statements describing product information. Optionally, entering the product data of a product object into the input page of the operation interface can involve entering at least one piece of product data of the product object into the input page of the operation interface.

[0122] In this embodiment, by entering product data on the input page of the operation interface, the entered product data can be operated more intuitively. For example, after entering the product data, if it is found that the product data entered on the input page is incorrect, the incorrect product data can be directly modified on the input page, which can achieve the purpose of preliminary verification of product data.

[0123] Step S504: Identify product data and search for target products similar to the product object based on the product data.

[0124] In the technical solution provided by step S504 of the present invention, after the product data of the product object is entered into the input page on the operation interface, the entered product data can be identified, and a search can be performed in the product library based on the obtained product data to obtain target products similar to the product object.

[0125] Optionally, the aforementioned product library may consist of an image library containing products, a video library containing products, and a statement library containing descriptions of products.

[0126] Step S506: Display the adjustment results of the product data of the product object on the publishing page of the operation interface. This involves analyzing the target product and returning the adjustment results based on the analysis results.

[0127] In the technical solution provided by step S506 of the present invention, after obtaining a target product similar to the product object, the obtained target product can be analyzed to obtain the analysis result, and the adjustment result of the product data of the product object can be obtained based on the analysis result. Then, the adjustment result of the obtained product data of the product object is displayed on the publishing page of the operation interface.

[0128] Optionally, the user's product object can be adjusted based on the adjustment results of the product object's product data. This guides the user to modify the product information of the product object, maximizing the differentiation between the product object and the target product, thereby reducing the competitiveness of the user's product object. This embodiment displays the adjustment results of the obtained product object's product data on the operation interface, allowing for a more intuitive view of the adjustment results. Users can easily perform operations on the adjusted product data in real time, such as deletion or modification, thus enabling real-time updates of the product object's product data. This solves the technical problem of being unable to update product object data and achieves the technical effect of enabling real-time updates of product object's product data.

[0129] In related technologies, for products published on e-commerce platforms, information on similar products is typically matched using product categories and attributes to help users improve the quality of their content and obtain better data feedback. However, this method suffers from low information accuracy due to the inability to accurately match product categories. This application, after obtaining the product data of the product object, identifies the product data, generates product information, and then searches for similar target products based on this information. The target products are then analyzed, and product data for adjusting the product object is generated based on the analysis results. Adjusting the product object based on this product data allows for accurate matching of the product object and target products, avoiding the inaccurate matching and low information accuracy caused by matching similar product information through product categories and attributes. This solves the technical problem of low product information accuracy and achieves the technical effect of improving product information accuracy.

[0130] Furthermore, in related technologies, text parsing can be used to match information about similar products, helping users improve the quality of their content and data feedback. However, this method requires preparing text for similar products in advance, and many merchants in the market stuff keywords, making accurate matching impossible through text parsing. This application, however, pre-establishes a product database and uses artificial intelligence algorithms to search and identify product images, videos, and descriptions within the database. Then, it calculates the similarity between the product object and the target product to obtain the most similar target product. This avoids the inaccurate matching caused by pre-prepared text for similar products and keyword stuffing when matching information about similar products through text parsing, thus solving the technical problem of low product information accuracy and achieving the technical effect of improving product information accuracy.

[0131] Example 2

[0132] The method for processing the commodity data described above in this embodiment of the invention will be further described below with reference to preferred embodiments.

[0133] Figure 6 This is a flowchart of another method for processing product data according to an embodiment of the present invention. Figure 6 As shown, this embodiment can use artificial intelligence to identify product images or videos, thereby searching for similar target images or videos and obtaining product information of similar target products. This allows for comparison and analysis of the competitiveness of the target product. The method may include the following steps:

[0134] Step S602: Upload product images or videos in the product publishing backend.

[0135] In the technical solution provided by step S602 of this embodiment, users can upload product images or videos that need to be processed in the product publishing backend.

[0136] Optionally, users can upload a single product image or product video in the product publishing backend, or they can upload multiple product images or product videos at the same time, depending on the user's needs.

[0137] Step S604: Perform artificial intelligence recognition on the product images or videos uploaded by the user to obtain product information.

[0138] In the technical solution provided by step S604 of this embodiment, after the user uploads product images or product videos, artificial intelligence methods are used to identify the uploaded product images or product videos to obtain product information. Optionally, the use of artificial intelligence methods to identify the uploaded product images or product videos can be to use artificial intelligence recognition algorithms to identify the uploaded product images or product videos.

[0139] In this embodiment, when the product data is a product image, the obtained product information can be the product category, product attribute information, and appearance feature information of any part of the product object; when the product data is a product video, the obtained product information can be the product category, product three-dimensional structure, product attribute information, and appearance feature information of any part of the product object.

[0140] Step S606: Based on the product information, search for similar target images or target videos.

[0141] In the technical solution provided by step S606 of this embodiment, after obtaining product information by recognizing product images or videos through artificial intelligence, similar target images or videos can be searched based on the product information, and then the product corresponding to the target image or video can be obtained, and the product can be used as the target product similar to the product object.

[0142] Optionally, the aforementioned product information may be attribute information of the product provided through product images or videos, such as general attributes and personalized attributes.

[0143] In this embodiment, the user can pre-establish an information database. Each time the user searches based on the product information of a product object and obtains the target product, the product information of the target product can be stored in the database, allowing the database to be updated in real time. This way, when the user makes the next search, the target product can be matched more accurately, avoiding the problem of low information accuracy due to the inability to accurately match the product information of the product object, thus solving the technical problem of low product information accuracy and achieving the technical effect of improving the accuracy of product information.

[0144] Step S608: Based on the target image or target video, obtain the target product and return the product information of the target product.

[0145] In the technical solution provided by step S608 of this embodiment, after obtaining the target product, the target product can be analyzed to obtain the product information of the target product, and the product information of the target product can be returned so as to compare it with the product information of the product object.

[0146] Step S610: Based on the returned product information of the target product, compare and analyze the product competitiveness of the product objects.

[0147] In the technical solution provided by step S610 of this embodiment, after obtaining the product information of the returned target product, the product information of the returned target product can be input into the analysis model, and analyzed by the analysis method to obtain the product competitiveness information of the product object. When the product competitiveness of the product object is large, the guidance information obtained by the analysis method for the returned target product information is used to guide the user to modify the product information of the product object, and the product information of the product object is modified based on the guidance information to improve the quality of the product object and reduce the competitiveness of the product object.

[0148] In steps S602 to S610 above, product images or videos are uploaded to the product publishing backend and subjected to artificial intelligence recognition to obtain product information. Then, based on the product information, target products similar to the product object are searched and analyzed to reduce the product object's competitiveness, thereby improving the product object's sales data. This achieves the goal of accurately matching the product object and the target product, avoiding the inability to reduce the product object's competitiveness due to the inability to accurately match the product object and the target product. Thus, it solves the technical problem of being unable to reduce the product object's competitiveness and achieves the technical effect of reducing the product object's competitiveness.

[0149] The method for processing the commodity data described in this embodiment of the invention will be further described below with reference to another preferred embodiment.

[0150] Figure 7 This is a flowchart of another method for processing product data according to an embodiment of the present invention. Figure 7 As shown, this embodiment achieves the goal of prioritizing the recommendation of product images and videos with white backgrounds by replacing the background color of the product images and videos with white. The method may include the following steps:

[0151] Step S702: Upload product images or videos in the product publishing backend.

[0152] In the technical solution provided by step S702 of this embodiment, users can upload product images or videos that need to be processed in the product publishing backend.

[0153] Optionally, users can upload a single product image or product video in the product publishing backend, or they can upload multiple product images or product videos at the same time, depending on the user's needs.

[0154] Step S704: Perform artificial intelligence segmentation on the uploaded product images or videos to extract product images.

[0155] In the technical solution provided by step S704 of this embodiment, after uploading product images or videos, artificial intelligence segmentation can be performed on the uploaded product images or videos to extract the product images. This embodiment avoids the incompleteness of manual segmentation of product images or videos, which leads to the inability to extract the required parts of the product image. It also avoids the inefficiency and high cost of manual methods, solving the technical problem of low efficiency in extracting product images and achieving the technical effect of improving the efficiency of product image extraction.

[0156] Optionally, when performing AI segmentation on product videos to extract product images, the product video can be captured first, and then the product images can be extracted from the captured frames.

[0157] Step S706: Recognize the product image and replace the background color of the product image with white to generate a white background image.

[0158] In the technical solution provided by step S706 of this embodiment, after extracting the product image, artificial intelligence recognition is performed on the product image to identify the background color of the product image, and then the background color is replaced with white, thus generating a white background image. This embodiment avoids the high cost caused by users needing to prepare a background in advance by using artificial intelligence to replace the product image with a white background image, and also avoids the inefficiency caused by using other graphic design software to create white background images. It solves the technical problem of low efficiency in obtaining white background images and achieves the technical effect of improving the efficiency of obtaining white background images.

[0159] Step S708: Automatically upload the white background image to the corresponding recommendation backend.

[0160] In the technical solution provided by step S708 of this embodiment, after obtaining the white background image, it can be automatically uploaded to the corresponding recommendation backend, such as a merchant's recommendation slot or a platform's traffic entry point. Since the white background image clearly shows product details, it can be recommended by the platform as an important object; that is, the white background image has a higher recommendation level. This allows for priority recommendation of the white background image when adjusting product data. This embodiment improves the recommendation rate of product objects and reduces their competitiveness by uploading the white background image to the corresponding recommendation backend.

[0161] In steps S702 to S708 above, product images or videos are uploaded to the product publishing backend, and artificial intelligence segmentation is used to extract the product image. Then, the background color of the product image is changed to white to obtain a white-background image, which is automatically uploaded to the corresponding recommendation backend. Because the white-background image shows product details more clearly, it can be recommended by the platform as an important object, meaning it has a higher recommendation level. This allows for priority recommendation of white-background images when adjusting product data. This embodiment improves the recommendation rate of product objects and reduces their competitiveness by uploading white-background images to the corresponding recommendation backend, thus solving the technical problem of not being able to reduce the competitiveness of product objects and achieving the technical effect of reducing the competitiveness of product objects.

[0162] The following section will further describe the above-mentioned product data processing method of the present invention in the context of a specific product data processing scenario.

[0163] Figure 8 This is a schematic diagram illustrating a scenario of processing product data according to an embodiment of the present invention. Figure 8 As shown, the computing device collects product data of a product object, wherein the product data includes at least one of the following: product images, product videos, and statements used to describe the product, and then inputs the product data into the computing device.

[0164] In this embodiment, a recognition model is installed in the computer device. This recognition model can be trained using a pre-collected product dataset. The recognition model trained on the data can efficiently and accurately identify almost all the data to be identified using a recognition algorithm.

[0165] In this embodiment, the recognition model can be an artificial neural network model or a convolutional neural network model, and the recognition algorithm can be an artificial intelligence recognition algorithm or a convolutional neural network intelligent recognition algorithm.

[0166] In this embodiment, a recognition algorithm is used in the computing device to identify the collected product data and output product information. When the product data is an image, the obtained product information can include product classification, product attribute information, and product appearance features. When the product data is a video, the obtained product information can include product classification, product three-dimensional structure, product attribute information, and product appearance features. When the product data is a statement describing the product, the obtained product information can include basic information such as the product name, type, and specifications. Based on this product information, a target product similar to the product object is searched, and then the product information of the product object is adjusted according to the target product to reduce the competitiveness of the product object and improve its sales data.

[0167] In this embodiment, an artificial intelligence method is used in a computing device to segment product data to identify product images. After identifying the background color of the product image, the background color is replaced with white, thus generating a white background image. Because the product details are more clearly displayed in the white background image, it can be recommended by the platform as an important object, meaning it has a higher recommendation level. This allows for prioritizing the recommendation of white background images when adjusting product data, thereby improving the sales data of that product.

[0168] In relevant algorithms, for products published on e-commerce platforms, information on similar products is typically matched based on product categories and attributes. However, this method suffers from low accuracy due to the inability to precisely match product categories. Furthermore, matching information on identical products through text parsing requires pre-prepared text for the same product, and many merchants in the market stuff keywords, making precise matching impossible through text parsing. This embodiment, however, analyzes the product information of the product object and searches based on this information to obtain target products similar to the product object. Then, it adjusts the product object according to the target product's information, achieving precise matching between the product object and the target product. Additionally, this embodiment can also improve the recommendation rate by replacing the product image of the product object with a white background image. This embodiment avoids the inaccurate matching and low information accuracy caused by matching similar product information through product categories and attributes, and also avoids the inaccurate matching caused by pre-prepared text for the same product and keyword stuffing when matching information on identical products through text parsing. Therefore, it solves the technical problem of low product information accuracy and achieves the technical effect of improving product information accuracy.

[0169] It should be noted that, for the sake of simplicity, the foregoing method embodiments are all described as a series of actions. However, those skilled in the art should understand that the present invention is not limited to the described order of actions, because according to the present invention, some steps can be performed in other orders or simultaneously. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are preferred embodiments, and the actions and modules involved are not necessarily essential to the present invention.

[0170] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods according to the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) and includes several instructions to cause a terminal device (which may be a mobile phone, computer, server, or network device, etc.) to execute the methods described in the various embodiments of the present invention.

[0171] Example 3

[0172] According to an embodiment of the present invention, a product data processing apparatus for implementing the above-described product data processing method is also provided. It should be noted that the product data processing apparatus of this embodiment can be used to execute embodiments of the present invention. Figure 2The method for processing product data is shown.

[0173] Figure 9 This is a schematic diagram of a product data processing apparatus according to an embodiment of the present invention. Figure 9 As shown, the product data processing device 90 may include: a collection unit 91, a first identification unit 92, a search unit 93, and a first analysis unit 94.

[0174] The acquisition unit 91 is used to acquire product data of the product object, wherein the product data includes at least one of the following: product image, product video, and statement used to describe the product.

[0175] The first identification unit 92 is used to identify product data and generate product information for the product object.

[0176] Search unit 93 is used to search for target products similar to the product object based on the product information of the product object.

[0177] The first analysis unit 94 is used to analyze the target product and return product data for adjusting the product object based on the analysis results.

[0178] It should be noted that the aforementioned acquisition unit 91, first identification unit 92, search unit 93, and first analysis unit 94 correspond to steps S202 to S208 in Embodiment 1. The four units and their corresponding steps implement the same instances and application scenarios, but are not limited to the content disclosed in Embodiment 1. It should also be noted that the aforementioned units, as part of the device, can run on the computer terminal 10 provided in Embodiment 1.

[0179] According to an embodiment of the present invention, another product data processing apparatus for implementing the above-described product data processing method is also provided. It should be noted that the product data processing apparatus of this embodiment can be used to execute embodiments of the present invention. Figure 3 The method for processing product data is shown.

[0180] Figure 10 This is a schematic diagram of another product data processing apparatus according to an embodiment of the present invention. Figure 10 As shown, the product data processing device 100 may include: a first display unit 101, a first display unit 103, a second display unit 105, and a third display unit 107.

[0181] The first display unit 101 is used to display the product data of the collected product objects on the operation interface, wherein the product data includes at least one of the following: product images, product videos, and statements used to describe the product.

[0182] The first display unit 103 is used to display product information of a product object on the operation interface, wherein the product information of the product object is generated by recognizing product data.

[0183] The second display unit 105 is used to display the target product that is similar to the product object obtained from the search on the operation interface.

[0184] The third display unit 107 is used to display the product data of the product object to be adjusted on the adjustment page of the operation interface, wherein the product data of the product object to be adjusted is generated by analyzing the target product.

[0185] It should be noted that the first display unit 101, the first display unit 103, the second display unit 105, and the third display unit 107 mentioned above correspond to steps S302 to S308 in Embodiment 1. The four units and the corresponding steps implement the same examples and application scenarios, but are not limited to the content disclosed in Embodiment 1. It should be noted that the above units, as part of the device, can run in the computer terminal 10 provided in Embodiment 1.

[0186] According to an embodiment of the present invention, another product data processing apparatus for implementing the above-described product data processing method is also provided. It should be noted that the product data processing apparatus of this embodiment can be used to execute embodiments of the present invention. Figure 4 The method for processing product data is shown.

[0187] Figure 11 This is a schematic diagram of another product data processing apparatus according to an embodiment of the present invention. Figure 11 As shown, the product data processing device 11 may include: a fourth display unit 111, an adjustment unit 112, a second identification unit 113, a fifth display unit 114, and a second analysis unit 115.

[0188] The fourth display unit 111 is used to display product data of a product object collected by a shooting device on an operation interface, wherein the product data includes at least one of the following: product image, product video, and statement describing the product.

[0189] The adjustment unit 112 is used to adjust the resolution of the results displayed on the operation interface when the resolution displayed on the operation interface is lower than the predetermined resolution.

[0190] The second identification unit 113 is used to identify product data and generate product information of the product object when the resolution of the displayed result is higher than the predetermined resolution.

[0191] The fifth display unit 114 is used to display the target product that is similar to the product object obtained from the search on the operation interface.

[0192] The second analysis unit 115 is used to analyze the target product and display the product data of the adjusted product object based on the analysis results on the operation interface.

[0193] It should be noted that the fourth display unit 111, adjustment unit 112, second identification unit 113, fifth display unit 114, and second analysis unit 115 mentioned above correspond to steps S402 to S410 in Embodiment 1. The five units and their corresponding steps implement the same examples and application scenarios, but are not limited to the content disclosed in Embodiment 1. It should be noted that the above units, as part of the device, can run in the computer terminal 11 provided in Embodiment 1.

[0194] According to an embodiment of the present invention, another product data processing apparatus for implementing the above-described product data processing method is also provided. It should be noted that the product data processing apparatus of this embodiment can be used to execute embodiments of the present invention. Figure 5 The method for processing product data is shown.

[0195] Figure 12 This is a schematic diagram of another product data processing apparatus according to an embodiment of the present invention. Figure 12 As shown, the product data processing device 120 may include: an input unit 121, a third identification unit 122, and a second display unit 123.

[0196] The input unit 121 is used to input product data of a product object on the input page of the operation interface, wherein the product data includes at least one of the following: product image, product video, and statement used to describe the product.

[0197] The third identification unit 122 is used to identify product data and search for target products similar to the product object based on the product data.

[0198] The second display unit 123 is used to display the adjustment results of the product data of the product object on the publishing page of the operation interface, wherein the target product is analyzed and the adjustment results are returned based on the analysis results.

[0199] It should be noted that the above-mentioned input unit 121, third identification unit 122, and second display unit 123 correspond to steps S502 to S506 in Embodiment 1. The three units and their corresponding steps implement the same examples and application scenarios, but are not limited to the content disclosed in Embodiment 1. It should be noted that the above-mentioned units, as part of the device, can run in the computer terminal 10 provided in Embodiment 1.

[0200] In the product data processing device of this embodiment, after obtaining the product data of the product object, it is necessary to identify the product data, generate product information, and then search based on this product information to obtain target products similar to the product object. Then, the target products are analyzed, and product data for adjusting the product object is generated based on the analysis results. Adjusting the product object based on this product data can accurately match the product object and the target product, avoiding the inaccurate matching of product information and low information accuracy caused by matching information of similar products through product classification and attributes. It also avoids the inaccurate matching of product information caused by keyword stuffing when matching information of the same product through text parsing, thereby solving the technical problem of low product information accuracy and achieving the technical effect of improving product information accuracy.

[0201] Example 4

[0202] Embodiments of the present invention may provide a computer terminal, which can be installed in the commodity data processing system of the present invention. The computer terminal may be any one of the computer terminal devices in a group of computer terminals. Optionally, in this embodiment, the computer terminal may also be replaced by a mobile terminal or other terminal device.

[0203] Optionally, in this embodiment, the computer terminal may be located in at least one of a plurality of network devices in a computer network.

[0204] In this embodiment, the computer terminal described above can execute the program code for the following steps in the application vulnerability detection method: collecting product data of a product object, wherein the product data includes at least one of the following: product images, product videos, and statements used to describe the product; identifying the product data and generating product information of the product object; searching for target products similar to the product object based on the product information of the product object; analyzing the target products and returning adjusted product data of the product object based on the analysis results.

[0205] Optionally, Figure 13 This is a structural block diagram of a computer terminal according to an embodiment of the present invention. Figure 13 As shown, the mobile terminal A may include one or more (only one is shown in the figure) processors 1302, memory 1304, and transmission devices 1306.

[0206] The memory can be used to store software programs and modules, such as the program instructions / modules corresponding to the security vulnerability detection method and apparatus in this embodiment of the invention. The processor executes various functional applications and data processing by running the software programs and modules stored in the memory, thereby realizing the above-mentioned commodity data processing method. The memory may include high-speed random access memory, and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory may further include memory remotely located relative to the processor, and these remote memories can be connected to terminal A via a network. Examples of the above-mentioned networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.

[0207] The processor can invoke information and application programs stored in the memory via a transmission device to perform the following steps: collecting product data of a product object, wherein the product data includes at least one of the following: product images, product videos, and statements describing the product; identifying the product data and generating product information of the product object; searching for target products similar to the product object based on the product information of the product object; analyzing the target products and returning adjusted product data of the product object based on the analysis results.

[0208] Optionally, the processor may also execute program code that performs the following steps: extracting product content from product information, wherein the product content includes product attributes and / or product features, and the product attributes include: general attributes and personalized attributes; and searching the product library based on the product content to obtain target products similar to the product object.

[0209] Optionally, the processor may also execute program code for the following steps: when the product data is a product image, the product library consists of an image library containing products, wherein the image content obtained by recognizing the product image is compared with the image objects in the image library to calculate the similarity, and a target image similar to the image content is searched. This target image is used to display the target product similar to the product object, wherein an artificial intelligence algorithm is used to recognize the content of any area in the product image to obtain the image content.

[0210] Optionally, the processor may also execute program code for the following steps: when the product data is a product video, the product library consists of a video library containing products, wherein the similarity calculation is performed between the video content obtained by recognizing the product video and the video objects in the video library, and a target video similar to the video content is searched for. The target video is used to display target products similar to the product objects, wherein an artificial intelligence algorithm is used to recognize the content of any frame of the product video.

[0211] Optionally, the processor may also execute program code with the following steps: when the product data is a statement used to describe the product, the product library consists of a library of statements that describe the product, wherein the semantics obtained by recognizing the statement are compared with the statement objects in the statement library to calculate the similarity, and a target statement similar to the statement used to describe the product is searched. The target statement is used to describe the target product similar to the product object, wherein an artificial intelligence algorithm is used to recognize the semantics of the statement.

[0212] Optionally, the processor may also execute program code for the following steps: using an analysis model to analyze the target product and obtain analysis results, wherein the analysis model is a model that includes analytical factors for analyzing product competitiveness, and the analytical factors include at least one of the following: page views, clicks, purchase frequency, and title; based on the analysis results, obtaining modified data; using the modified data to update the product information of the product object and generate new product information for the product object.

[0213] Optionally, the processor may also execute program code that performs the following steps: compares the product data of the target product with the product data of the current product object to obtain an analysis result consisting of the comparison result, wherein the analysis result includes the content in the product data of the product object that does not meet the publishing conditions; and updates the product data of the product object.

[0214] Optionally, the processor may also execute program code that performs the following steps: updating the product information of the product object, including at least one of the following: cropping and replacing parts of the product image that do not meet the publishing conditions; cropping and replacing parts of the product video that do not meet the publishing conditions; deleting and replacing parts of the statement used to describe the product that do not meet the publishing conditions.

[0215] Optionally, the processor may also execute program code that performs the following steps: when the product data is a statement used to describe the product, obtain the geographical location of the product object, and update the statement used to describe the product based on at least one of the following methods: determine the expression of the statement in the local area based on the geographical location, replace the statement, delete invalid words and trending words, and use recommended words.

[0216] Optionally, the processor may also execute program code that performs the following steps: after returning adjusted product data for the product object based on the analysis results, uses dynamic bullet comments to display the updated product data for the product object.

[0217] Optionally, the processor may also execute program code that performs the following steps: after collecting product data of the product object, segmenting the frame images of the product image and / or product video to extract the product image; replacing the product image with a white background image; and automatically uploading the white background image to the corresponding recommendation backend, wherein the white background image is the image with the highest priority when adjusting the product data of the product object.

[0218] As an alternative example, the processor can invoke information and applications stored in the memory via a transmission device to perform the following steps: displaying the collected product data of a product object on an operating interface, wherein the product data includes at least one of the following: product images, product videos, and statements describing the product; displaying product information of the product object on the operating interface, wherein the product information of the product object is generated by recognizing the product data; displaying target products similar to the product object obtained through searching on the operating interface; and displaying the product data of the adjusted product object on an adjustment page on the operating interface, wherein the product data of the adjusted product object is generated by analyzing the target product.

[0219] Optionally, the processor may also execute program code that performs the following steps: after displaying the target product similar to the product object found in the search on the operation interface, popping up guidance information on the operation interface, wherein the guidance information includes defect information of the product information; and displaying adjustment information generated based on the guidance information on the operation interface.

[0220] As another alternative example, the processor can invoke information and applications stored in the memory via a transmission device to perform the following steps: displaying product data of a product object captured by a camera on an operating interface, wherein the product data includes at least one of the following: product images, product videos, and statements describing the product; adjusting the resolution of the display result on the operating interface if the resolution of the display result is lower than a predetermined resolution; identifying the product data and generating product information of the product object if the resolution of the display result is higher than the predetermined resolution; displaying target products similar to the product object obtained through searching on the operating interface; analyzing the target products and displaying adjusted product data of the product object returned based on the analysis results on the operating interface.

[0221] As another alternative example, the processor can invoke information and applications stored in the memory via a transmission device to perform the following steps: entering product data of a product object on the input page of the operation interface, wherein the product data includes at least one of the following: product images, product videos, and statements describing the product; identifying the product data and searching for target products similar to the product object based on the product data; displaying the adjustment results of the product data of the product object on the publishing page of the operation interface, wherein the target product is analyzed and the adjustment results are returned based on the analysis results.

[0222] This invention provides a method for processing product data. After obtaining product data for a product object, the product data needs to be identified to generate product information. Then, based on this product information, a search is performed to obtain target products similar to the product object. The target products are then analyzed, and based on the analysis results, product data for adjusting the product object is generated. Adjusting the product object based on this product data allows for accurate matching of the product object and the target product. This avoids the inaccurate matching and low accuracy of information caused by matching information of similar products through product classification and attributes. It also avoids the inaccurate matching of product information caused by keyword stuffing when matching information of the same product through text parsing. Therefore, this solves the technical problem of low product information accuracy and achieves the technical effect of improving the accuracy of product information.

[0223] Those skilled in the art will understand that Figure 13 The structure shown is for illustrative purposes only. Mobile terminal A can also be a smartphone (such as an Android phone, iOS phone, etc.), tablet computer, mobile internet device (MID), PAD, and other terminal devices. Figure 13 This does not limit the structure of the mobile terminal A described above. For example, mobile terminal A may also include components that are more... Figure 13 The more or fewer components shown (such as network interfaces, display devices, etc.), or having the same Figure 13 The different configurations shown.

[0224] Those skilled in the art will understand that all or part of the steps in the various methods of the above embodiments can be implemented by a program instructing the hardware related to the terminal device. The program can be stored in a computer-readable storage medium, which may include: flash drive, read-only memory (ROM), random access memory (RAM), disk or optical disk, etc.

[0225] Example 5

[0226] Embodiments of the present invention also provide a computer-readable storage medium. Optionally, in this embodiment, the computer-readable storage medium can be used to store the program code executed by the product data processing method provided in Embodiment 1.

[0227] Optionally, in this embodiment, the computer-readable storage medium may be located in any computer terminal in a group of computer terminals in a computer network, or in any mobile terminal in a group of mobile terminals.

[0228] Optionally, in this embodiment, the computer-readable storage medium is configured to store program code for performing the following steps: collecting product data of a product object, wherein the product data includes at least one of the following: product images, product videos, and statements describing the product; identifying the product data and generating product information of the product object; searching for target products similar to the product object based on the product information of the product object; analyzing the target products and returning adjusted product data of the product object based on the analysis results.

[0229] Optionally, the computer-readable storage medium is further configured to store program code for performing the following steps: extracting product content from product information, wherein the product content includes product attributes and / or product characteristics, and the product attributes include: general attributes and personalized attributes; and searching from a product library based on the product content to obtain target products similar to the product object.

[0230] Optionally, the computer-readable storage medium is further configured to store program code for performing the following steps: when the product data is a product image, the product library consists of a library of images containing products, wherein the image content obtained by recognizing the product image is compared with the image objects in the image library to calculate similarity, and a target image similar to the image content is searched for. This target image is used to display target products similar to the product objects, wherein an artificial intelligence algorithm is used to recognize the content of any region in the product image to obtain the image content.

[0231] Optionally, the computer-readable storage medium is further configured to store program code for performing the following steps: when the product data is a product video, the product library consists of a video library containing products, wherein the similarity calculation is performed between the video content obtained by identifying the product video and the video objects in the video library, and a target video similar to the video content is searched for, the target video is used to display the target product similar to the product object, wherein an artificial intelligence algorithm is used to identify the content of any frame of the image in the product video.

[0232] Optionally, the computer-readable storage medium is further configured to store program code for performing the following steps: when the product data is a statement used to describe the product, the product library consists of a library containing statements describing the product, wherein the semantics obtained by identifying the statement are compared with the statement objects in the statement library to calculate similarity, and a target statement similar to the statement used to describe the product is searched for, the target statement being used to describe the target product similar to the product object, wherein an artificial intelligence algorithm is used to identify the semantics of the statement.

[0233] Optionally, the computer-readable storage medium is further configured to store program code for performing the following steps: analyzing a target product using an analytical model to obtain analytical results, wherein the analytical model is a model that includes analytical factors for analyzing the competitiveness of the product, the analytical factors including at least one of the following: page views, clicks, purchase frequency, and title; obtaining modified data based on the analytical results; updating the product information of the product object using the modified data, and generating new product information for the product object.

[0234] Optionally, the computer-readable storage medium is further configured to store program code for performing the following steps: comparing the product data of the target product with the product data of the current product object to obtain an analysis result consisting of the comparison result, wherein the analysis result includes content in the product data of the product object that does not meet the publishing conditions; and updating the product data of the product object.

[0235] Optionally, the computer-readable storage medium is further configured to store program code for performing the following steps: updating product information of a product object, including at least one of the following: cropping and replacing portions of a product image that do not meet the publishing conditions; cropping and replacing portions of a product video that do not meet the publishing conditions; deleting and replacing portions of statements used to describe the product that do not meet the publishing conditions.

[0236] Optionally, the computer-readable storage medium is also configured to store program code for performing the following steps: when the product data is a statement describing the product, obtaining the geographical location of the product object, and updating the statement describing the product based on at least one of the following methods: determining the local expression of the statement based on the geographical location and replacing the statement, and deleting invalid words and trending words, and using recommended words.

[0237] Optionally, the computer-readable storage medium is also configured to store program code for performing the following steps: after returning adjusted product data for a product object based on the analysis results, using dynamic bullet comments to display the updated product data for the product object.

[0238] Optionally, the computer-readable storage medium is further configured to store program code for performing the following steps: after collecting product data of a product object, segmenting the frame images of product pictures and / or product videos to extract product images; replacing the product images with a white background image; and automatically uploading the white background image to the corresponding recommendation backend, wherein the white background image is the image with the highest priority when adjusting the product data of the product object.

[0239] As an optional example, the computer-readable storage medium is also configured to store program code for performing the following steps: displaying product data of a collected product object on an operating interface, wherein the product data includes at least one of the following: product images, product videos, and statements describing the product; displaying product information of the product object on the operating interface, wherein the product information of the product object is generated by identifying product data; displaying target products similar to the product object obtained through searching on the operating interface; and displaying product data of the adjusted product object on an adjustment page on the operating interface, wherein the product data of the adjusted product object is generated by analyzing the target products.

[0240] Optionally, the computer-readable storage medium is further configured to store program code for performing the following steps: after displaying the target product similar to the product object obtained from the search on the operation interface, popping up guidance information on the operation interface, wherein the guidance information includes defect information of the product information; and displaying adjustment information generated based on the guidance information on the operation interface.

[0241] As another alternative example, the computer-readable storage medium is also configured to store program code for performing the following steps: displaying product data of a product object acquired by a camera on an operating interface, wherein the product data includes at least one of the following: product images, product videos, and statements describing the product; adjusting the resolution of the display result on the operating interface if the resolution of the display result is lower than a predetermined resolution; identifying the product data and generating product information of the product object if the resolution of the display result is higher than the predetermined resolution; displaying target products similar to the product object obtained through searching on the operating interface; analyzing the target products and displaying adjusted product data of the product object returned based on the analysis results on the operating interface.

[0242] As another alternative example, the computer-readable storage medium is also configured to store program code for performing the following steps: entering product data of a product object on an input page of the user interface, wherein the product data includes at least one of the following: product images, product videos, and statements describing the product; identifying the product data and searching for target products similar to the product object based on the product data; and displaying the adjustment results of the product data of the product object on a publishing page of the user interface, wherein the adjustment results are returned by analyzing the target product and based on the analysis results.

[0243] The sequence numbers of the above embodiments of the present invention are for descriptive purposes only and do not represent the superiority or inferiority of the embodiments.

[0244] In the above embodiments of the present invention, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0245] In the several embodiments provided in this application, it should be understood that the disclosed technical content can be implemented in other ways. The device embodiments described above are merely illustrative; for example, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the displayed or discussed mutual coupling, direct coupling, or communication connection may be through some interfaces; the indirect coupling or communication connection between units or modules may be electrical or other forms.

[0246] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0247] Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0248] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, read-only memory (ROM), random access memory (RAM), portable hard drives, magnetic disks, or optical disks.

[0249] The above description is only a preferred embodiment of the present invention. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A method for processing commodity data, characterized in that, include: Collect product data of the product object, wherein the product data includes at least one of the following: product images, product videos, and statements used to describe the product; Identify the product data and generate product information for the product object; Based on the product information of the product object, target products similar to the product object are searched and obtained; Analyze the target product and return adjusted product data based on the analysis results; The method further includes, after collecting product data of the product object, segmenting the product data to obtain a product image of the product object; replacing the product image with a white background image of the product object, wherein the white background image is the image with the highest priority used to adjust the product data; and uploading the white background image as product material to the recommendation backend, wherein the white background image is placed in the recommendation backend at the traffic entrance and the merchant's recommendation position. Analyzing the target product and returning adjusted product data for the product object based on the analysis results includes: using an analysis model to analyze the target product and obtaining the analysis results, wherein the analysis model is a model that includes analytical factors for analyzing product competitiveness, and the analytical factors include at least one of the following: page views, clicks, purchase frequency, and title; the analysis results include content in the product data of the product object that does not meet the publishing conditions; based on the analysis results, obtaining modified data for adjusting the product object; using the modified data to update the product data of the product object and generating new product data for the product object, wherein the new product data is used to distinguish the product object from the target product.

2. The method according to claim 1, characterized in that, Based on the product information of the product object, target products similar to the product object are searched and obtained, including: Product content is extracted from the product information, wherein the product content includes product attributes and / or product features, and the product attributes include: general attributes and personalized attributes; Based on the product content, a search is performed in the product database to obtain the target product that is similar to the product object.

3. The method according to claim 2, characterized in that, Based on the product content, a search is performed in the product database to obtain target products similar to the product object, including: When the product data is the product image, the product library consists of a library of product images, wherein... The image content obtained by recognizing the product image is compared with the image objects in the image library to calculate the similarity, and a target image similar to the image content is searched. The target image is used to display target products similar to the product object. The image content is obtained by recognizing the content of any area in the product image using an artificial intelligence algorithm.

4. The method according to claim 2, characterized in that, Based on the product content, a search is performed in the product database to obtain target products similar to the product object, including: When the product data is a product video, the product library consists of a video library containing products, wherein... The similarity calculation is performed between the video content obtained by identifying the product video and the video objects in the video library to search for target videos similar to the video content. The target videos are used to display target products similar to the product objects. Artificial intelligence algorithms are used to identify the content of any frame in the product video.

5. The method according to claim 2, characterized in that, Based on the product content, a search is performed in the product database to obtain target products similar to the product object, including: When the product data consists of statements used to describe the product, the product database comprises a database of statements describing the product, wherein... The semantics obtained from the identified statement are compared with the statement objects in the statement library to calculate similarity, and a target statement similar to the statement used to describe the product is searched. The target statement is used to describe a target product similar to the product object. Artificial intelligence algorithms are used to identify the semantics of the statement.

6. The method according to any one of claims 1 to 5, characterized in that, Analyze the target product and return adjusted product data based on the analysis results, including: The product data of the target product is compared with the product data of the current product object to obtain the analysis result composed of the comparison result, wherein the analysis result includes the content in the product data of the product object that does not meet the publishing conditions; Update the product data of the product object.

7. The method according to claim 6, characterized in that, Updating the product information of the product object includes at least one of the following: The parts of the product images that do not meet the publishing conditions are cropped and replaced; The portions of the product video that do not meet the publishing conditions are cropped and replaced; The portions of the statements describing the products that do not meet the publishing conditions are deleted and replaced.

8. The method according to claim 7, characterized in that, When the product data is the statement used to describe the product, the geographical location of the product object is obtained, and the statement used to describe the product is updated based on at least one of the following methods: determining the local expression of the statement based on the geographical location and replacing the statement, as well as deleting invalid words and trending words, and using recommended words.

9. The method according to claim 1, characterized in that, After returning adjusted product data for the product object based on the analysis results, the method further includes: Use dynamic bullet comments to display the updated product data for the product object.

10. The method according to claim 1, characterized in that, After collecting the product data of the product object, the method further includes: If the product data consists of product images and / or product videos, the frames of the product images and / or product videos are segmented to obtain the product images.

11. A method for processing commodity data, characterized in that, include: The collected product data is displayed on the operation interface, wherein the product data includes at least one of the following: product images, product videos, and statements describing the product; The product information of the product object is displayed on the operation interface, wherein the product information of the product object is generated by recognizing the product data; The interface displays target products similar to the product object obtained through the search. The adjustment page on the operation interface displays the product data of the product object to be adjusted. The product data of the product object is updated using the modified data used to adjust the product object, generating new product data for the adjusted product object. The modified data is obtained based on analysis results, which include content in the product data of the product object that does not meet the publishing conditions. The analysis results are obtained by analyzing the target product using an analysis model. The analysis model includes analytical factors for analyzing product competitiveness, including at least one of the following: page views, clicks, purchase frequency, and title. The new product data is used to distinguish between the product object and the target product. The method further includes, after displaying the collected product data of the product object on the operation interface, segmenting the product data to obtain the product image of the product object; replacing the product image with a white background image of the product object, wherein the white background image is the image with the highest priority used to adjust the product data; and uploading the white background image as product material to the recommendation backend, wherein the white background image is placed in the recommendation backend at the traffic entrance and the merchant's recommendation position.

12. The method according to claim 11, characterized in that, After displaying the target products similar to the product object obtained from the search on the user interface, the method further includes: A guidance message pops up on the operation interface, wherein the guidance message includes information on defects in the product information; The adjustment information generated based on the guidance information is displayed on the user interface.

13. A method for processing commodity data, characterized in that, include: The user interface displays product data of the product object collected by the camera, wherein the product data includes at least one of the following: product images, product videos, and statements describing the product; If the resolution displayed on the operation interface is lower than the predetermined resolution, adjust the resolution of the result displayed on the operation interface. If the resolution of the displayed result is higher than the predetermined resolution, the product data is identified, and product information of the product object is generated; The interface displays target products similar to the product object obtained through the search. Analyze the target product and display product data for adjusting the product object based on the analysis results on the operation interface; The method further includes, after displaying the product data of the product object collected by the camera on the operation interface, the product data is segmented to obtain the product image of the product object; the product image is replaced with a white background image of the product object, wherein the white background image is the image with the highest priority used to adjust the product data; the white background image is uploaded to the recommendation backend as product material, wherein the white background image is placed in the recommendation backend as a traffic entry point and a merchant's recommendation position; The process involves analyzing the target product and displaying adjusted product data based on the analysis results on the user interface. This includes using an analysis model to analyze the target product, obtaining the analysis results, and displaying these results on the user interface. The analysis model incorporates analytical factors for analyzing product competitiveness, including at least one of the following: page views, clicks, purchase frequency, and title. The analysis results include content in the product data that does not meet the publishing criteria. Based on the analysis results, modified data for adjusting the product is obtained. The modified data is then used to update the product data of the product, generating new product data for the product, which is then displayed on the user interface. This new product data distinguishes the product from the target product.

14. A method for processing commodity data, characterized in that, include: Enter product data for a product object on the input page of the operation interface, wherein the product data includes at least one of the following: product image, product video, and statements describing the product; Identify the product data, and search for target products similar to the product object based on the product data; The adjustment results of the product data of the product object are displayed on the publishing page of the operation interface. The adjustment results are returned based on the analysis results of the target product. The method further includes, after obtaining the product data of the product object, segmenting the product data to obtain the product image of the product object; replacing the product image with a white background image of the product object, wherein the white background image is the image with the highest priority used to adjust the product data; and uploading the white background image of the product object as product material to the recommendation backend, wherein the white background image is placed in the recommendation backend at the traffic entry point and the merchant's recommendation position.

15. A device for processing commodity data, characterized in that, include: The data acquisition unit is used to acquire product data of a product object, wherein the product data includes at least one of the following: product images, product videos, and statements describing the product; The first identification unit is used to identify the product data and generate product information for the product object; The search unit is used to search for target products similar to the product object based on the product information of the product object; The first analysis unit is used to analyze the target product and return product data for adjusting the product object based on the analysis results; The acquisition unit is further configured to segment the product data to obtain a product image of the product object; replace the product image with a white background image of the product object, wherein the white background image is the image with the highest priority for adjusting the product data; and upload the white background image of the product object as product material to the recommendation backend, wherein the white background image is placed in the recommendation backend at the traffic entrance and the merchant's recommendation position. The first analysis unit is configured to analyze the target product by performing the following steps, and return adjusted product data for the product object based on the analysis results: analyzing the target product using an analysis model to obtain the analysis results, wherein the analysis model is a model that includes analytical factors for analyzing product competitiveness, the analytical factors including at least one of the following: page views, clicks, purchase frequency, and title; the analysis results include content in the product data of the product object that does not meet the publishing conditions; based on the analysis results, obtaining modified data for adjusting the product object; updating the product data of the product object using the modified data to generate new product data for the product object, wherein the new product data is used to distinguish the product object from the target product.

16. A device for processing commodity data, characterized in that, include: The first display unit is used to display the product data of the collected product objects on the operation interface, wherein the product data includes at least one of the following: product images, product videos, and statements describing the product; The first display unit is used to display the product information of the product object on the operation interface, wherein the product information of the product object is generated by recognizing the product data; The second display unit is used to display target products that are similar to the product object obtained through the search on the operation interface; The third display unit is used to display the product data of the product object being adjusted on the adjustment page of the operation interface. The product data of the product object is updated using the modified data used to adjust the product object, generating new product data for the adjusted product object. The modified data is obtained based on analysis results, which include content in the product data of the product object that does not meet the publishing conditions. The analysis results are obtained by analyzing the target product using an analysis model. The analysis model includes analytical factors for analyzing product competitiveness, including at least one of the following: page views, clicks, purchase frequency, and title. The new product data is used to distinguish between the product object and the target product. The first display unit is further configured to segment the product data to obtain a product image of the product object; replace the product image with a white background image of the product object, wherein the white background image is the image with the highest priority used to adjust the product data; and upload the white background image of the product object as product material to the recommendation backend, wherein the white background image is placed in the recommendation backend as a traffic entry point and a merchant's recommendation position.

17. A device for processing commodity data, characterized in that, include: The fourth display unit is used to display product data of a product object collected by a camera on the operation interface, wherein the product data includes at least one of the following: product images, product videos, and statements describing the product; An adjustment unit is used to adjust the resolution of the results displayed on the operation interface when the resolution displayed on the operation interface is lower than a predetermined resolution; The second identification unit is used to identify the product data and generate product information of the product object when the resolution of the displayed result is higher than the predetermined resolution; The fifth display unit is used to display, on the operation interface, target products that are similar to the product object obtained through the search; The second analysis unit is used to analyze the target product and display product data that is adjusted based on the analysis results on the operation interface. The fourth display unit is further configured to segment the product data to obtain a product image of the product object; replace the product image with a white background image of the product object, wherein the white background image is the image with the highest priority used to adjust the product data; and upload the white background image as product material to the recommendation backend, wherein the white background image is placed in the recommendation backend at the traffic entrance and the merchant's recommendation position. The second analysis unit is configured to analyze the target product by performing the following steps, and display the product data of the product object adjusted based on the analysis results on the operation interface: Analyzing the target product using an analysis model to obtain the analysis results, and displaying the analysis results on the operation interface, wherein the analysis model is a model that includes analytical factors for analyzing product competitiveness, and the analytical factors include at least one of the following: page views, clicks, purchase frequency, and title; the analysis results include content in the product data of the product object that does not meet the publishing conditions; obtaining modification data for adjusting the product object based on the analysis results; updating the product data of the product object using the modification data to generate new product data for the product object, and displaying the new product data on the operation interface, wherein the new product data is used to distinguish the product object from the target product.

18. A device for processing commodity data, characterized in that, include: The input unit is used to input product data of a product object on the input page of the operation interface, wherein the product data includes at least one of the following: product image, product video, and statement for describing the product; The third identification unit is used to identify the product data and search for target products similar to the product object based on the product data; The second display unit is used to display the adjustment results of the product data of the product object on the publishing page of the operation interface, wherein the adjustment results are returned based on the analysis results of the target product. The input unit is further configured to segment the product data to obtain a product image of the product object; replace the product image with a white background image of the product object, wherein the white background image is the image with the highest priority for adjusting the product data; and upload the white background image as product material to the recommendation backend, wherein the white background image is placed in the recommendation backend at the traffic entrance and the merchant's recommendation position.

19. A computer-readable storage medium, characterized in that, The computer-readable storage medium includes a stored program, wherein, when the program is executed, it controls the device on which the computer-readable storage medium is located to perform the method for processing commodity data according to any one of claims 1 to 14.

20. A processor, characterized in that, The processor is used to run a program, wherein the program executes the commodity data processing method according to any one of claims 1 to 14 when it runs.

21. A commodity data processing system, characterized in that, include: processor; as well as A memory, connected to the processor, is used to provide the processor with instructions to process the following steps: acquiring product data of a product object, wherein the product data includes at least one of the following: product images, product videos, and statements describing the product; identifying the product data and generating product information of the product object; searching for target products similar to the product object based on the product information of the product object; analyzing the target products and returning adjusted product data of the product object based on the analysis results; After collecting product data for a product object, the system further performs the following steps: segmenting the product data to obtain a product image of the product object; replacing the product image with a white background image of the product object, wherein the white background image is the image with the highest priority for adjusting the product data; and uploading the white background image as product material to the recommendation backend, wherein the white background image is placed in the recommendation backend at the traffic entry point and the merchant's recommendation position. Analyzing the target product and returning adjusted product data for the product object based on the analysis results includes: using an analysis model to analyze the target product and obtaining the analysis results, wherein the analysis model is a model that includes analytical factors for analyzing product competitiveness, and the analytical factors include at least one of the following: page views, clicks, purchase frequency, and title; the analysis results include content in the product data of the product object that does not meet the publishing conditions; based on the analysis results, obtaining modified data for adjusting the product object; using the modified data to update the product data of the product object and generating new product data for the product object, wherein the new product data is used to distinguish the product object from the target product.

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