Cross-border e-commerce full-automatic product selection and shelving method, system and device based on multiple platforms

Abstract

The application is suitable for the cross-border e-commerce technical field, and particularly relates to a cross-border e-commerce full-automatic product selection and listing method, system and device based on multiple platforms, which comprises the following steps: obtaining target information; wherein the target information comprises a target region and a target platform; obtaining preselected product information based on the target information; wherein the preselected product information comprises at least one preselected product name; obtaining listing product information based on the preselected product information and the target platform; wherein the listing product information comprises at least one listing product information, and the listing product information comprises a listing product name, a listing product picture and a listing product price. The cross-border e-commerce full-automatic product selection and listing method, system and device based on multiple platforms can improve the problem that the analysis, product selection and listing are performed by manual work, the listing period is long, and it is difficult to capture dynamic market demand, which may miss the market opportunity.

Description

TECHNICAL FIELD

[0001] The application belongs to the technical field of cross-border e-commerce, and particularly relates to a cross-border e-commerce full-automatic product selection and listing method, system and device based on multiple platforms. BACKGROUND

[0002] Cross-border e-commerce refers to a kind of international business activity in which transaction subjects in different jurisdictions reach a transaction through an e-commerce platform, make payment and settlement, deliver goods through cross-border logistics, and complete the transaction.

[0003] In the related art, when selecting a product to be listed on an overseas shopping platform, a user usually analyzes, selects and lists the product manually, which leads to a long listing period and makes it difficult to capture dynamic market demand, possibly missing the market opportunity. SUMMARY

[0004] The embodiments of the application provide a cross-border e-commerce full-automatic product selection and listing method, system and device based on multiple platforms, which can improve the problem that manual analysis, selection and listing of products lead to a long listing period and make it difficult to capture dynamic market demand, possibly missing the market opportunity.

[0005] In a first aspect, the embodiments of the application provide a cross-border e-commerce full-automatic product selection and listing method based on multiple platforms, which includes the following steps.

[0006] Obtaining target information; wherein the target information includes a target region and a target platform, the target region reflects a region in which a user sells a product, and the target platform is an e-commerce platform on which the product is listed;

[0007] Obtaining preselected product information based on the target information; wherein the preselected product information includes at least one preselected product name;

[0008] Obtaining listing product information based on the preselected product information and the target platform; wherein the listing product information includes at least one listing product information, and the listing product information includes a listing product name, a listing product picture and a listing product price.

[0009] The technical solution described above in the embodiments of the application has at least the following technical effects:

[0010] The method for automatically selecting and listing products of cross-border e-commerce based on multiple platforms provided by the embodiments of the present application comprises the following steps: obtaining target information including a target region and a target platform, and determining the direction of product selection and listing, so as to provide basic data for subsequent steps; obtaining preselected product information based on the target information, combining regional demand and platform characteristics to preliminarily screen potential hot-selling products, and filtering irrelevant products to improve market response speed; obtaining listing product information based on the preselected product information and the target platform, ensuring that the products meet the advantages of the supply chain, accurately pricing to adapt to the target platform, and generating product pictures that can attract users to shorten the product selection and listing cycle.

[0011] In a second aspect, the embodiments of the present application provide a system for automatically selecting and listing products of cross-border e-commerce based on multiple platforms, comprising:

[0012] An obtaining unit is configured to obtain target information, wherein the target information comprises a target region and a target platform, the target region reflects a region in which a user sells products, and the target platform is an e-commerce platform on which the products are listed;

[0013] A preselecting unit is configured to obtain preselected product information based on the target information, wherein the preselected product information comprises at least one preselected product name;

[0014] A listing unit is configured to obtain listing product information based on the preselected product information and the target platform, wherein the listing product information comprises at least one listing product information, and the listing product information comprises a listing product name, a listing product picture, and a listing product price.

[0015] In a third aspect, the embodiments of the present application provide a device for automatically selecting and listing products of cross-border e-commerce based on multiple platforms, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the method of any one of the first aspect.

[0016] In a fourth aspect, the embodiments of the present application provide a computer readable storage medium, wherein the computer readable storage medium stores a computer program, and the computer program is executable by a processor to implement the method of any one of the first aspect.

[0017] In a fifth aspect, the embodiments of the present application provide a computer program product, which, when executed on a device for automatically selecting and listing products of cross-border e-commerce based on multiple platforms, causes the device for automatically selecting and listing products of cross-border e-commerce based on multiple platforms to execute the method for automatically selecting and listing products of cross-border e-commerce based on multiple platforms of any one of the first aspect.

[0018] It can be understood that the beneficial effects of the above-mentioned second aspect to the fifth aspect can be referred to the related description in the above-mentioned first aspect, which will not be repeated here. BRIEF DESCRIPTION OF DRAWINGS

[0019] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed to be used in the embodiments or prior art description will be briefly introduced as follows. Obviously, the drawings in the following description only some embodiments of the present application, and for those skilled in the art, other drawings can also be obtained without creative labor on the basis of these drawings.

[0020] Figure 1 is a process schematic diagram of a multi-platform-based cross-border e-commerce full-automatic product selection and listing method provided by an embodiment of the present application;

[0021] Figure 2 is a process schematic diagram of step S200 in the multi-platform-based cross-border e-commerce full-automatic product selection and listing method provided by an embodiment of the present application;

[0022] Figure 3 is a process schematic diagram of step S300 in the multi-platform-based cross-border e-commerce full-automatic product selection and listing method provided by an embodiment of the present application;

[0023] Figure 4 is a structure schematic diagram of a multi-platform-based cross-border e-commerce full-automatic product selection and listing system provided by an embodiment of the present application;

[0024] Figure 5 is a structure schematic diagram of a multi-platform-based cross-border e-commerce full-automatic product selection and listing device provided by an embodiment of the present application. DETAILED DESCRIPTION

[0025] In the following description, specific details such as specific system structures, techniques, etc. are presented in order to provide a thorough understanding of the embodiments of the present application. However, it should be clear to those skilled in the art that the present application can also be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits and methods are omitted in order not to obscure the description of the present application with unnecessary details.

[0026] It should be understood that when used in the specification and the appended claims of the present application, the term "comprising" indicates the presence of the described features, integers, steps, operations, elements, and / or components, but does not exclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and / or sets thereof.

[0027] It should also be understood that the term "and / or" as used herein refers to and encompasses any and all possible combinations of one or more of the associated listed items, and that the term "at least one of' as used herein refers to and encompasses any and all possible combinations of one or more of the associated listed items.

[0028] As used in the description of the application and the appended claims, the term "if' can be interpreted to mean "when" or "upon" or "in response to determining" or "in response to detecting," depending on the context. Similarly, the phrase "if it is determined" or "if [a described condition or event] is detected" can be interpreted to mean "upon determining" or "in response to determining" or "upon detecting [the described condition or event]" or "in response to detecting [the described condition or event]," depending on the context.

[0029] In addition, the terms "first", "second", "third", etc. as used in the description of the application and the appended claims are only used to distinguish descriptions, and cannot be understood as indicating or implying relative importance.

[0030] Reference in the specification to "one embodiment" or "some embodiments" means that a particular feature, structure, or characteristic described in connection with the embodiment is included in at least one embodiment of the application. The appearances of the phrases "in one embodiment", "in some embodiments", "in other embodiments", "in additional embodiments", etc. in various places in the specification are not necessarily all referring to the same embodiment, although they can. The terms "comprising", "including", "having" and their variants, mean "including but not limited to", unless otherwise expressly specified, and are not excluding additional, unrecited elements or method steps.

[0031] Cross-border e-commerce refers to a kind of international business activity in which transaction subjects belonging to different jurisdictions reach a transaction through an e-commerce platform, make payment and settlement, deliver goods through cross-border logistics, and complete the transaction.

[0032] In the related art, when selecting the goods uploaded on the overseas shopping platform, the user usually analyzes, selects and uploads the goods manually, which results in a long uploading period and makes it difficult to capture dynamic market demand, which may miss the market opportunity.

[0033] To solve the above problems, the embodiment of the present application provides a cross-border e-commerce full-automatic product selection and listing method, system and device based on multiple platforms. In the method, the target information including the target area and the target platform is obtained first, and the direction of product selection and listing is determined, providing basic data for subsequent steps. Then, the preselected product information is obtained based on the target information, and the potential hot-selling products are preliminarily screened in combination with the regional demand and platform characteristics, irrelevant products are filtered, and the market response speed is improved. Then, the listing product information is obtained based on the preselected product information and the target platform, ensuring that the goods meet the supply chain advantage, accurately pricing to adapt to the target platform, and generating product pictures that can attract users, shortening the product selection and listing cycle.

[0034] The cross-border e-commerce full-automatic product selection and listing method based on multiple platforms provided by the embodiment of the present application can be applied to a cross-border e-commerce full-automatic product selection and listing device based on multiple platforms. At this time, the cross-border e-commerce full-automatic product selection and listing device based on multiple platforms is the execution subject of the cross-border e-commerce full-automatic product selection and listing method based on multiple platforms provided by the embodiment of the present application. The embodiment of the present application does not make any limitation on the specific type of the cross-border e-commerce full-automatic product selection and listing device based on multiple platforms.

[0035] For example, the cross-border e-commerce full-automatic product selection and listing device based on multiple platforms can be a desktop computer, a notebook computer, a palm computer, a cloud server, and other computing devices.

[0036] In order to better understand the cross-border e-commerce full-automatic product selection and listing method based on multiple platforms provided by the embodiment of the present application, the specific implementation process of the cross-border e-commerce full-automatic product selection and listing method based on multiple platforms provided by the embodiment of the present application is exemplarily introduced below.

[0037] Figure 1 The embodiment of the present application provides a cross-border e-commerce full-automatic product selection and listing method based on multiple platforms, and a schematic flowchart of the cross-border e-commerce full-automatic product selection and listing method based on multiple platforms is shown. The cross-border e-commerce full-automatic product selection and listing method based on multiple platforms includes:

[0038] S100, obtaining target information; wherein the target information includes a target area and a target platform, the target area reflects the area where the user sells goods, and the target platform is an e-commerce platform for listing goods.

[0039] It can be understood that the target area reflects the region where the user wants to sell goods, or the region where the goods are sold. The target platform is a shopping platform that can provide e-commerce services for the target area. The way to obtain the target information can be to receive the data transmitted by the user, or to obtain the hot-selling area and platform trend data in the industry report through the standardized interface (such as REST API), to provide the user with recommended options, etc., but not limited to this. Obtaining the target information can determine the direction of product selection and listing, and provide basic data for subsequent steps.

[0040] S200, obtaining pre-selected commodity information based on the target information; wherein the pre-selected commodity information comprises at least one pre-selected commodity name.

[0041] It can be understood that the way of obtaining pre-selected commodity information based on the target information can be collecting hot search words of mainstream search engines (such as Google and Yandex) in the target area in real time, combining topic tag data of social media (such as Facebook and Twitter) to build a hot word pool, and connecting target platform APIs (such as Amazon MWS and eBay Trading API) to obtain commodity data of the top 1000 sales in the past 7 days, including fields such as commodity title, category, sales, rating, etc. Then, by analyzing the hot word pool and the commodity data, the commodity title of the commodity with a sales of more than a preset sales in the past 7 days corresponding to the keyword with a daily average search number of more than 1000 times in the hot word pool is confirmed as the pre-selected commodity name. It can also be that the search words with a daily average search number of more than 1000 times and the top 1000 sales in the past 7 days are sent to the user, and then the data transmitted by the user is received, but not limited to this. Obtaining pre-selected commodity information based on target information can combine regional demand and platform characteristics to preliminarily screen potential hot-selling commodities and filter irrelevant commodities, thereby improving market response speed.

[0042] In a possible implementation, please refer to Figure 2 , S200, obtaining pre-selected commodity information based on the target information, comprising:

[0043] S210, obtaining hot word information based on the target area; wherein the hot word information comprises at least one hot word, and the hot word reflects an object of interest of a user in the target area.

[0044] It can be understood that the way of obtaining hot word information based on the target area can be collecting hot search words of mainstream search engines (such as Google and Yandex) in the target area, combining topic tag data of social media (such as Facebook and Twitter) to build a hot word pool, and then screening the data in the hot word pool through data cleaning and language recognition (to ensure that the keywords in the hot word pool are consistent with the language of the target area), and confirming the keywords with a frequency of ≥500 times per day as hot words. It can also be that the data transmitted by the user is received, but not limited to this. Obtaining hot word information based on the target area can quickly capture sudden market demand (such as holiday promotion and influencer sales), thereby providing a basis for subsequent steps.

[0045] In a possible implementation, please refer to Figure 2 , S210, obtaining hot word information based on the target area, comprising:

[0046] S211, obtain the search set of users in the target area within a preset time period; wherein the search set includes at least one search term, and the number of searches for the search term is greater than the preset number of searches.

[0047] It is understandable that the preset time period can be the past 5 days, or a user-defined time period, but it is not limited to these. The preset number of searches can be 500, 1000, or a user-defined value, but it is not limited to these. The search set of users within the target area within the preset time period can be obtained by acquiring the search keywords of mainstream search engines in the target area within the preset time period and identifying the search keywords with a search frequency greater than the preset number of searches as the search set; alternatively, it can be obtained by using interfaces such as the Twitter API or Instagram Graph API to identify hashtags that appear more frequently than the preset number of searches within the preset time period as the search set, but it is not limited to these methods. Obtaining the search set of users within the target area within the preset time period provides a basis for subsequent steps.

[0048] S212, determine whether each search term in the search set matches the basic attributes of the product. If the search term matches the basic attributes of the product, then the search term is confirmed as a hot word.

[0049] As we can understand it, determining whether a search term matches the basic attributes of a product is equivalent to determining whether the search term can be sold as a product (for example, natural phenomena such as holidays and weather cannot be products, while digital products such as mobile phones and computers can). If a search term matches the basic attributes of a product, it means that the search term can be sold as a product. Identifying search terms that match the basic attributes of a product as hot keywords provides a basis for subsequent steps.

[0050] S213, confirm all hot words as hot word information.

[0051] It is understandable that identifying all trending words as trending word information can provide a basis for subsequent steps.

[0052] S220, obtain popular product information based on the target platform; wherein, popular product information includes at least one best-selling product.

[0053] It can be understood that the hot commodity information based on the target platform can be obtained by the API interface of the target platform to obtain commodities with sales greater than or equal to a preset sales in a preset time period and confirm them as hot commodities, or can be that a user selects a commodity type (for example, kitchen supplies, digital products, etc.), obtains the sales of commodities in the commodity type selected by the user in a preset time period through the API interface of the target platform, and confirms commodities with sales greater than or equal to a preset sales in the preset time period as hot commodities, but is not limited thereto. The hot commodity information based on the target platform can achieve accurate identification of hot commodities on the target platform and provide a basis for subsequent steps.

[0054] In a possible implementation, please refer to Figure 2 S220, obtaining hot commodity information based on the target platform, comprising:

[0055] S221, obtaining a sales analysis table of hot commodities with sales greater than a preset sales on the target platform in a preset time period; wherein the time nodes on the horizontal axis of the sales analysis table are in units of days, the vertical axis is the sales of the hot commodities, and the sales analysis table reflects the relationship between the sales of the hot commodities and time.

[0056] It can be understood that the preset time period can be 5 days, 7 days, etc., or a value defined by a user, but is not limited thereto. The preset sales can be 1000 pieces, 1500 pieces, or a value defined by a user, but is not limited thereto. The sales analysis table reflects the sales of the hot commodities in each day. The way of obtaining the sales analysis table can be to obtain the sales of each commodity in each day in a preset time period through the API interface of the target platform, or can be to receive data transmitted by a user, but is not limited thereto. Obtaining the sales analysis table can provide a basis for subsequent steps.

[0057] S222, obtaining prediction information corresponding to the hot commodities corresponding to each sales analysis table based on each sales analysis table; wherein the prediction information includes information reflecting whether the sales of the hot commodities can continue to remain or continue to grow.

[0058] It can be understood that the way of obtaining the prediction information corresponding to the hot commodities corresponding to each sales analysis table based on each sales analysis table can be to analyze the trend of the line in the sales analysis table (whether there is an inflection point, the slope change of the line, etc.), or can be to send each sales analysis table to a user and receive data transmitted by the user, but is not limited thereto. Obtaining the prediction information corresponding to the hot commodities corresponding to each sales analysis table based on each sales analysis table can provide a reference for the user to consider whether to list the same type of commodities.

[0059] In a possible implementation, please refer to Figure 2, S222, obtaining, based on each sales analysis table, prediction information corresponding to the hot-selling goods corresponding to each sales analysis table, including:

[0060] S2221, analyzing each sales analysis table respectively, taking the sales volume corresponding to the smallest time node on the sales analysis table as the initial sales volume, and taking the sales volume corresponding to the largest time node on the sales analysis table as the final sales volume.

[0061] It can be understood that, assuming that the preset time period is 5 days and the analysis time is December 6, the smallest time node on the sales analysis table is December 2, and the largest time node on the sales analysis table is December 6. Confirming the initial sales volume and the final sales volume can provide a basis for subsequent steps.

[0062] S2222, confirming the number of days reflected by the preset time period as the analysis days, confirming the sum of the sales volumes corresponding to each time node on the sales analysis table as the total sales volume, and then confirming the value obtained by dividing the total sales volume by the analysis days as the average sales volume.

[0063] It can be understood that confirming the sum of the sales volumes corresponding to each time node on the sales analysis table as the total sales volume, and then confirming the value obtained by dividing the total sales volume by the analysis days as the average sales volume can provide a basis for subsequent steps.

[0064] For example, assuming that the preset time period is 5 days, the sales volume on the first day is 100, the sales volume on the second day is 200, the sales volume on the third day is 300, the sales volume on the fourth day is 400, and the sales volume on the fifth day is 500, then the analysis days are 5, the total sales volume = 100+200+300+400+500 = 1500, and the average sales volume = 1500 / 5 = 500.

[0065] S2223, confirming the value obtained by adding the final sales volume to the average sales volume as the judgment value.

[0066] It can be understood that confirming the value obtained by adding the final sales volume to the average sales volume as the judgment value can provide a basis for subsequent steps.

[0067] For example, assuming that the final sales volume is 500 and the average sales volume is 400, then the judgment value = 500+400 = 900.

[0068] S2224, if the initial sales volume is greater than or equal to the final sales volume and less than the judgment value, obtaining prediction information reflecting that the sales volume of the hot-selling goods can continue to maintain; if the initial sales volume is greater than or equal to the judgment value, obtaining prediction information reflecting that the sales volume of the hot-selling goods can continue to grow.

[0069] It can be understood that if the initial sales volume is greater than or equal to the final sales volume and less than the judgment value, it represents that the sales growth rate of the hot-selling commodity gradually decreases but still exists in the sales market, and the heat of the hot-selling commodity may decrease; if the initial sales volume is greater than or equal to the judgment value, it represents that the sales growth rate of the hot-selling commodity remains unchanged or increases, and the heat of the hot-selling commodity increases or remains unchanged.

[0070] In S223, the hot-selling commodity corresponding to the prediction information reflecting that the sales volume of the hot-selling commodity can continue to remain or continue to grow is confirmed as the popular commodity information.

[0071] It can be understood that confirming the hot-selling commodity corresponding to the prediction information reflecting that the sales volume of the hot-selling commodity can continue to remain or continue to grow as the popular commodity information is to collect commodities that can maintain sales volume in a future period of time, thereby providing a basis for subsequent steps.

[0072] In S230, each hot word is matched with each hot-selling commodity, and it is judged whether the matched hot word is associated with the hot-selling commodity. If the hot word is associated with the hot-selling commodity, the commodity name corresponding to the hot-selling commodity is confirmed as a preselected commodity name.

[0073] It can be understood that matching each hot word with each hot-selling commodity is to judge whether the hot-selling commodity is driven by the goods or events reflected by the hot word (for example, portable power banks drive the sales volume of power banks, and star water cups drive the sales volume of water cups). The way to judge whether the hot word matches the hot-selling commodity can be to generate a domain-specific word vector space containing 500,000 words based on Word2Vec and BERT pre-training models for cross-border e-commerce field data, and then calculate semantic similarity. It can also be to send each hot word and each hot-selling commodity to the user and then receive the data transmitted by the user after the user judges, but is not limited thereto. The hot word is associated with the hot-selling commodity, which represents that the commodity with increased sales volume is associated with the behavior of consumers in the target region, excluding abnormal data generated by operations such as brushing. Confirming the commodity name corresponding to the hot-selling commodity as a preselected commodity name can provide a basis for subsequent steps.

[0074] In S240, all preselected commodity names are confirmed as preselected commodity information.

[0075] It can be understood that confirming all preselected commodity names as preselected commodity information can provide a basis for subsequent steps.

[0076] In S300, based on the preselected commodity information and the target platform, the listing product information is obtained; wherein the listing product information includes at least one listing commodity information, and the listing commodity information includes a listing commodity name, a listing commodity picture, and a listing commodity price.

[0077] It can be understood that the way of obtaining the listing product information based on the pre-selected commodity information and the target platform can be searching the average price of the pre-selected commodity name on the target platform according to the pre-selected commodity name, listing the pre-selected commodity name with the average price within the expected price as the listing commodity name, confirming the average price as the listing commodity price, generating the listing commodity picture according to the listing commodity name through AI, or sending the pre-selected commodity information and the target platform to the user and receiving the data transmitted by the user, but not limited to this. Obtaining the listing product information based on the pre-selected commodity information and the target platform can ensure that the commodity meets the supply chain advantage, accurately price to adapt to the target platform, and generate a commodity picture that can attract users, shorten the product selection and listing period.

[0078] In a possible implementation, please refer to Figure 3 , S300, obtaining the listing product information based on the pre-selected commodity information and the target platform, comprising:

[0079] S310, respectively analyzing each pre-selected commodity name to determine whether the commodity reflected by the pre-selected commodity name belongs to the advantage supply chain, and if the commodity reflected by the pre-selected commodity name belongs to the advantage supply chain, confirming the pre-selected commodity name as the listing commodity name; wherein the advantage supply chain is the raw material supply chain that the user can provide.

[0080] It can be understood that determining whether the commodity reflected by the pre-selected commodity name belongs to the advantage supply chain is to determine whether the user has an advantage in the cost of producing the commodity reflected by the pre-selected commodity name. If the commodity reflected by the pre-selected commodity name belongs to the advantage supply chain, it means that the user can produce the commodity reflected by the pre-selected commodity name at a lower price.

[0081] For example, assuming that the user can buy latex at a lower price, and the pre-selected commodity name is a latex pillow, then the latex pillow belongs to the advantage supply chain.

[0082] S320, respectively obtaining the listing commodity price corresponding to each listing commodity name based on each listing commodity name and the target platform.

[0083] It can be understood that the way of obtaining the listing commodity price corresponding to each listing commodity name based on each listing commodity name and the target platform can be searching the average price of the commodity reflected by the listing commodity name on the target platform according to the listing commodity name, or sending the listing commodity name and the target platform to the user and receiving the data transmitted by the user, but not limited to this. Obtaining the listing commodity price based on the listing commodity name and the target platform can provide a reference for the user to judge the gross profit margin and his own competitiveness, and provide a basis for the subsequent steps.

[0084] In a possible implementation, please refer to Figure 3S320, obtaining, respectively based on each listing commodity name and the target platform, a listing commodity price corresponding to each listing commodity name, including:

[0085] S321, respectively searching each listing commodity name in the target platform to obtain a plurality of price sets respectively corresponding to each listing commodity name; wherein the price set includes a plurality of commodity prices corresponding to the listing commodity name, and each commodity price in the price set is arranged in ascending order.

[0086] It can be understood that the corresponding price set obtained by searching the listing commodity name in the target platform is to collect the prices of the same commodity in the target platform. Obtaining the price set corresponding to each listing commodity name and arranging the commodity prices in each set in ascending order can provide a basis for the subsequent steps.

[0087] S322, multiplying the number of commodity prices in the price set by a preset proportion to obtain a value, and confirming the value as a front cutoff point, and subtracting the front cutoff point from the number of commodity prices in the price set to obtain a value, and confirming the value as a rear cutoff point.

[0088] It can be understood that the preset proportion can be 30%, 35%, or a value defined by the user, etc., but is not limited thereto. Obtaining the front cutoff point and the rear cutoff point by calculation can provide a basis for the subsequent steps.

[0089] For example, assuming that the number of commodity prices in the price set is 100, and the preset proportion is 30%, then the front cutoff point = 100*0.3 = 30, and the rear cutoff point = 100-30 = 70.

[0090] S323, deleting all commodity prices from the starting position to the front cutoff point and deleting commodity prices from the rear cutoff point to the end position in the price set in order of commodity prices, and then dividing the sum of the remaining commodity prices in the price set by the number of the remaining commodity prices in the price set to obtain a value, and confirming the value as an analysis price.

[0091] It can be understood that deleting all commodity prices from the starting position to the front cutoff point and deleting commodity prices from the rear cutoff point to the end position can remove most of the abnormal prices (prices that are too high or too low), ensuring the reliability of the analysis price and providing a reference for user pricing.

[0092] For example, assuming that there are ten commodity prices in the price set, respectively 10, 20, 21, 48, 49, 50, 51, 52, 80, and 85, the front cutoff point is 3, and the rear cutoff point is 7, then the analysis price = (48+49+50+51+52) / 5 = 50.

[0093] S324, respectively judge whether each analysis price is in the preset price range, and confirm the analysis price in the preset price range as the on-shelf commodity price.

[0094] It can be understood that the preset price range can be 45-55, 40-60, or a value defined by the user according to the user's own situation, etc., but is not limited thereto. Confirming the analysis price in the preset price range as the on-shelf commodity price can meet the user's economic situation and provide a basis for subsequent steps.

[0095] S330, based on the hot word information and each on-shelf commodity name, obtaining an on-shelf commodity picture corresponding to each on-shelf commodity name.

[0096] It can be understood that the way of obtaining an on-shelf commodity picture corresponding to each on-shelf commodity name based on the hot word information and each on-shelf commodity name can be to combine each hot word in the hot word information with each on-shelf commodity name to judge whether the semantics of the combined word after combination is smooth, and input the combined word with smooth semantics to the image generation AI or video generation AI to obtain the on-shelf commodity picture, or can be to send the hot word information and each on-shelf commodity name to the user, and receive the image data transmitted by the user, etc., but is not limited thereto. Obtaining an on-shelf commodity picture corresponding to each on-shelf commodity name based on the hot word information and each on-shelf commodity name can be in line with the consumer's focus and attract the consumer's attention.

[0097] In one possible implementation, please refer to Figure 3 S330, based on the hot word information and each on-shelf commodity name, obtaining an on-shelf commodity picture corresponding to each on-shelf commodity name, comprising:

[0098] S331, extracting each adjective in the hot word information and marking each adjective as a matching word, respectively, combining each matching word with each on-shelf commodity name to obtain a plurality of combined words corresponding to each on-shelf commodity name, respectively.

[0099] It can be understood that the way of extracting the adjectives in each hot word in the hot word information can be to perform part-of-speech tagging on the hot words through the NLTK (Natural Language Toolkit), spaCy, etc. natural language processing library, or can be to extract the adjectives in the hot words through regular expression matching, etc., but is not limited thereto. Obtaining a plurality of combined words corresponding to each on-shelf commodity name, respectively, can provide a basis for subsequent steps.

[0100] It is exemplary. Assuming that there are two matching words "red" and "passionate", and two on-shelf commodity names "power bank" and "raincoat", then the combined words obtained after combination are "red power bank", "red raincoat", "passionate power bank", and "passionate raincoat".

[0101] S332, step a, respectively judge the semantic rationality of each combined word.

[0102] It can be understood that the way to judge the semantic rationality of the combined word can be to parse the syntax structure of the combined word through a natural language processing tool (such as NLTK, spaCy), or to use a large amount of combined word data labeled with semantic rationality to construct a training set, and then use a semantic analysis model obtained by training a machine learning algorithm (such as support vector machine, random forest, neural network, etc.) to judge, etc., but not limited to. The semantic rationality of the combined word is to judge whether the product described by the combined word can be produced.

[0103] S333, step b, if there are both semantically reasonable and semantically unreasonable combined words in each combined word, or the semantics of each combined word are reasonable, then delete the combined words with unreasonable semantics, and then combine each combined word with the combined word corresponding to the same name of the listed goods to obtain at least one combined word corresponding to each listed goods name, and then repeat steps a and b; if there is no semantically reasonable combined word in each combined word, then based on each combined word before combination, obtain the listed goods pictures corresponding to each listed goods name.

[0104] It can be understood that if there is a semantically reasonable combined word in each combined word, it means that the semantically reasonable combined word can be further added with a limiting word (adjective), so that the produced product further fits the consumer's preference (for example, "red power bank" can be added with the adjective "portable" to become "portable red power bank", etc.), and if there is no semantically reasonable combined word in each combined word, it means that the combined word cannot be further added with an adjective. The way to obtain the listed goods pictures corresponding to each listed goods name based on each combined word before combination can be to input each combined word into an image generation AI (Stable Diffusion, Midjourney, etc.) or a video generation AI (Sora, Runway, etc.) to obtain the listed goods pictures corresponding to the combined word, or to send the combined word to the user and receive the data transmitted by the user, etc., but not limited to.

[0105] For example, assuming that there are 1, 2, 3, 4 four matching words, there are A, B, C three product names, after the first combination, 1A, 2A, 3A, 4A, 1B, 2B, 3B, 4B, 1C, 2C, 3C, 4C, a total of 12 combination words are obtained, after deleting the combination words with unreasonable semantics, there are 2A, 3A, 4A, 1B, 3B, 4B, 1C, 2C, 3C, a total of 9 combination words, then after the second combination, 23A, 24A, 34A, 13B, 14B, 34B, 12C, 13C, 23C, a total of 9 combination words are obtained, if the semantics of 23A, 24A, 34A, 13B, 14B, 34B, 12C, 13C, 23C are all unreasonable, then based on 2A, 3A, 4A, 1B, 3B, 4B, 1C, 2C, 3C, the product pictures corresponding to A, B, and C are obtained respectively (the product pictures corresponding to A are obtained by 2A, 3A, 4A, the product pictures corresponding to B are obtained by 1B, 3B, 4B, and the product pictures corresponding to C are obtained by 1C, 2C, 3C); if 23A, 13B, 12C in 23A, 24A, 34A, 13B, 14B, 34B, 12C, 13C, 23C are not reasonable, then 23A, 13B, 12C are deleted, and 24A, 34A, 14B, 34B, 13C, 23C are combined again, 234A, 134B, 123C are obtained, and the combination and judgment of semantic rationality are repeated.

[0106] S340, after confirming each product name and the product picture and product price corresponding to the product name as product information, confirming all product information as product information.

[0107] It can be understood that confirming all product information as product information can ensure that the product meets the supply chain advantage, accurately prices to adapt to the target platform, and generates product pictures that can attract users, shortening the product selection and listing period.

[0108] For example, after confirming all product information as product information, each product information in the product information can be directly listed on the target platform, or the product information can be sent to the user, and the user can select the product information to be listed for listing, etc., but not limited thereto.

[0109] It should be understood that the size of the serial number of each step in the above embodiments does not mean the order of execution, and the execution order of each process should be determined according to its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0110] Corresponding to the multi-platform-based cross-border e-commerce full-automatic product selection and listing method described in the above embodiments, the embodiments of the present application also provide a multi-platform-based cross-border e-commerce full-automatic product selection and listing system. Each unit of the system can implement each step of the multi-platform-based cross-border e-commerce full-automatic product selection and listing method. Figure 4 A structural block diagram of the multi-platform-based cross-border e-commerce full-automatic product selection and listing system provided by the embodiments of the present application is shown. For ease of illustration, only the parts related to the embodiments of the present application are shown.

[0111] Referring to Figure 4 The system comprises:

[0112] An acquisition unit is configured to acquire target information. The target information comprises a target region and a target platform. The target region reflects a region in which the user sells goods, and the target platform is an e-commerce platform on which the goods are listed.

[0113] A pre-selection unit is configured to obtain pre-selected product information based on the target information. The pre-selected product information comprises at least one pre-selected product name.

[0114] A listing unit is configured to obtain listing product information based on the pre-selected product information and the target platform. The listing product information comprises at least one listing product information. The listing product information comprises a listing product name, a listing product picture, and a listing product price.

[0115] It should be noted that the information interaction, execution process, etc. between the above units are based on the same concept as the method embodiments of the present application. For specific functions and technical effects brought by them, please refer to the method embodiments part, which will not be repeated here.

[0116] Those skilled in the art can clearly understand that, for the convenience and brevity of description, only the division of the above functional units and modules is exemplified. In actual application, the above functions can be completed by different functional units and modules according to needs, i.e. the internal structure of the system is divided into different functional units or modules to complete all or part of the above-described functions. Each functional unit or module in the embodiments can be integrated in one processing unit, or each unit can exist physically, or two or more units can be integrated in one unit. The integrated unit can be realized in the form of hardware or software. In addition, the specific names of each functional unit or module are only for easy distinction, and do not limit the protection scope of the present application. The specific working process of the units and modules in the system can refer to the corresponding process in the foregoing method embodiments, which will not be repeated here.

[0117] The embodiments of the present application also provide a multi-platform-based cross-border e-commerce full-automatic product selection and listing device, Figure 5This is a structural diagram of a multi-platform, fully automated product selection and listing device for cross-border e-commerce, provided as an embodiment of this application. Figure 5 As shown, the fully automated product selection and listing equipment for cross-border e-commerce based on multiple platforms in this embodiment includes a control device 6. The control device 6 includes at least one processor 60. Figure 5 Only one is shown in the image), at least one memory 61 ( Figure 5 (Only one is shown in the image) and a computer program 62 stored in the at least one memory 61 and executable on the at least one processor 60. When the processor 60 executes the computer program 62, it causes the multi-platform cross-border e-commerce fully automated product selection and listing device to implement the steps in any of the above embodiments of the multi-platform cross-border e-commerce fully automated product selection and listing method, or causes the multi-platform cross-border e-commerce fully automated product selection and listing device to implement the functions of each unit in the above system embodiments.

[0118] For example, the computer program 62 may be divided into one or more modules / units, which are stored in the memory 61 and executed by the processor 60 to complete this application. The one or more modules / units may be a series of computer program instruction segments capable of performing a specific function, which describe the execution process of the computer program 62 in the control device 6.

[0119] The control device 6 can be a computing device such as a desktop computer, laptop, handheld computer, or cloud server. The control device 6 may include, but is not limited to, a processor 60 and a memory 61. Those skilled in the art will understand that... Figure 5 This is merely an example of a fully automated product selection and listing device for cross-border e-commerce based on multiple platforms. It does not constitute a limitation on fully automated product selection and listing devices for cross-border e-commerce based on multiple platforms. It may include more or fewer components than shown in the figure, or combine certain components, or different components. For example, it may also include input / output devices, network access devices, buses, etc.

[0120] The processor 60 can be a central processing unit (CPU), and can also be other general-purpose processors, a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field-programmable gate array (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or the processor can also be any conventional processor.

[0121] The memory 61 can be an internal storage unit of the control device 6 in some embodiments, for example, a hard disk or a memory of the control device 6. The memory 61 can also be an external storage device of the control device 6 in other embodiments, for example, a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc. Further, the memory 61 can include both an internal storage unit and an external storage device of the control device 6. The memory 61 is used to store an operating system, an application program, a boot loader, data, and other programs, for example, program codes of the computer program, etc. The memory 61 can also be used to temporarily store data that has been output or is to be output.

[0122] The embodiments of the present application further provide a computer readable storage medium, which stores a computer program. The computer program is executed by a processor to implement the steps in any of the above method embodiments.

[0123] The embodiments of the present application provide a computer program product. When the computer program product is run on the multi-platform based cross-border e-commerce full-automatic product selection and shelving device, the multi-platform based cross-border e-commerce full-automatic product selection and shelving device implements the steps in any of the above method embodiments.

[0124] The integrated unit, if implemented in the form of a software function unit and sold or used as an independent product, can be stored in a computer readable storage medium. Based on such understanding, the present application can implement all or part of the processes in the above-mentioned embodiment methods through a computer program to instruct relevant hardware, and the computer program can be stored in a computer readable storage medium. When the computer program is executed by a processor, the steps of each method embodiment described above can be implemented. The computer program includes computer program code, which can be in the form of source code, object code, executable files or some intermediate forms. The computer readable medium can at least include any entity or device capable of carrying the computer program code to the cross-border e-commerce full-automatic product selection and listing device based on multiple platforms, recording medium, computer memory, read-only memory (ROM), random access memory (RAM), electrical carrier signal, telecommunication signal and software distribution medium. For example, U disk, mobile hard disk, magnetic disk or optical disk, etc. In some jurisdictions, according to legislation and patent practice, the computer readable medium can not be an electrical carrier signal and a telecommunication signal.

[0125] In the above embodiments, the description of each embodiment has its own focus, and the parts not described or recorded in detail in a certain embodiment can be referred to the relevant description of other embodiments.

[0126] Those skilled in the art can appreciate that the units and algorithm steps of the examples described in combination with the embodiments disclosed herein can be implemented in electronic hardware or a combination of computer software and electronic hardware. Whether the functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Professional technicians can use different methods for each specific application to implement the described functions, but such implementation should not be considered beyond the scope of the present application.

[0127] In the embodiments provided in the present application, it should be understood that the disclosed cross-border e-commerce full-automatic product selection and listing system, device and method based on multiple platforms can be implemented in other ways. For example, the cross-border e-commerce full-automatic product selection and listing system and device embodiments described above are only illustrative, for example, the division of the modules or units is only a logical function division, and actual implementation can have another division method, for example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the coupling or direct coupling or communication connection between the displayed or discussed each other can be indirect coupling or communication connection through some interfaces, devices or units, which can be electrical, mechanical or other forms.

[0128] The units described as separate components may or may not be physically separate, and the components displayed as units may or may not be physical units, that is, may be located in one place, or may also be distributed to multiple network units. Part or all of the units can be selected to achieve the purpose of the embodiment scheme according to actual needs.

[0129] The above embodiments are only used to illustrate the technical solutions of the present application, but not limit them; although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that the technical solutions recorded in the foregoing embodiments can still be modified, or some technical features can be replaced by equivalents; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present application, and should be included in the protection scope of the present application.

Claims

1. A fully automated product selection and listing method for cross-border e-commerce based on multiple platforms, characterized in that, include: Obtain target information; wherein, the target information includes target region and target platform, the target region reflects the region where the user sells goods, and the target platform is the e-commerce platform where the goods are listed; Based on the target information, pre-selected product information is obtained; wherein, the pre-selected product information includes at least one pre-selected product name; Based on the pre-selected product information and the target platform, the product information to be listed is obtained; wherein, the product information to be listed includes at least one product information, the product information to be listed includes the product name, product image and product price; The process of obtaining pre-selected product information based on the target information includes: Hot word information is obtained based on the target area; wherein, the hot word information includes at least one hot word, and the hot word reflects the items or events that users in the target area are interested in; Popular product information is obtained based on the target platform; wherein, the popular product information includes at least one best-selling product; Each of the hot words is matched with each of the best-selling products, and it is determined whether the matched hot words are associated with the best-selling products. If the hot words are associated with the best-selling products, the product name corresponding to the best-selling products is confirmed as the pre-selected product name. Confirm all of the pre-selected product names as the pre-selected product information; The process of obtaining the product information to be listed based on the pre-selected product information and the target platform includes: Each of the pre-selected product names is analyzed to determine whether the product reflected by the pre-selected product name belongs to the advantageous supply chain. If the product reflected by the pre-selected product name belongs to the advantageous supply chain, then the pre-selected product name is confirmed as the product name to be listed. The advantageous supply chain is the raw material supply chain that the user can provide. The price of each listed product is obtained based on each listed product name and the target platform; Based on the hot word information and the names of each of the listed products, images of the listed products corresponding to each of the listed product names are obtained; After confirming each of the listed product names, the corresponding listed product images, and the listed product prices as the listed product information, all of the listed product information is confirmed as the listed product information.

2. The fully automated product selection and listing method for cross-border e-commerce based on multiple platforms as described in claim 1, characterized in that, The process of obtaining hot word information based on the target region includes: Obtain a search set of users within the target area within a preset time period; wherein the search set includes at least one search term, and the number of searches for the search term is greater than a preset number of searches; Each search term in the search set is determined to match the basic attributes of the product. If the search term matches the basic attributes of the product, the search term is identified as the hot word. All of the aforementioned hot words are confirmed as hot word information.

3. The fully automated product selection and listing method for cross-border e-commerce based on multiple platforms as described in claim 1, characterized in that... The process of obtaining popular product information based on the target platform includes: Obtain a sales analysis table of best-selling products on the target platform whose sales volume exceeds a preset sales volume within a preset time period; wherein, the time nodes on the horizontal axis of the sales analysis table are in days, and the vertical axis is the sales volume of the best-selling products, and the sales analysis table reflects the relationship between the sales volume of the best-selling products and time. Based on each of the aforementioned sales analysis tables, forecast information corresponding to the best-selling products for each of the aforementioned sales analysis tables is obtained; wherein, the forecast information includes information reflecting whether the sales volume of the best-selling products can continue to be maintained or continue to grow; The best-selling products corresponding to the forecast information that reflects the continued or sustained growth of sales of the best-selling products are identified as the popular product information.

4. The fully automated product selection and listing method for cross-border e-commerce based on multiple platforms as described in claim 3, characterized in that, The step of obtaining forecast information for best-selling products corresponding to each of the sales analysis tables includes: Each of the aforementioned sales analysis tables is analyzed separately, and the sales volume corresponding to the smallest time node in the sales analysis table is taken as the initial sales volume, and the sales volume corresponding to the largest time node in the sales analysis table is taken as the final sales volume. The number of days reflected in the preset time period is confirmed as the number of analysis days, the sum of the sales corresponding to each time node on the sales analysis table is confirmed as the total sales, and the value obtained by dividing the total sales by the number of analysis days is confirmed as the average sales. The value obtained by adding the final sales volume to the average sales volume is confirmed as the judgment value. If the initial sales volume is greater than or equal to the final sales volume and less than the judgment value, then the prediction information reflecting that the sales volume of the hot-selling product can continue to be maintained is obtained; if the initial sales volume is greater than or equal to the judgment value, then the prediction information reflecting that the sales volume of the hot-selling product can continue to grow is obtained.

5. The fully automated product selection and listing method for cross-border e-commerce based on multiple platforms as described in claim 1, characterized in that, The step of obtaining the price of the listed product corresponding to each of the listed product names based on each of the listed product names and the target platform includes: After searching each of the listed product names on the target platform, multiple price sets corresponding to each of the listed product names are obtained; wherein, each price set includes multiple product prices corresponding to the listed product names, and the product prices in the price set are arranged in ascending order; The value obtained by multiplying the number of commodity prices in the price set by a preset ratio is determined as the front cutoff point, and the value obtained by subtracting the front cutoff point from the number of commodity prices in the price set is determined as the back cutoff point. After deleting all commodity prices from the starting position to the first cutoff point and from the second cutoff point to the end position in the price set according to the order of commodity prices, the sum of the remaining commodity prices in the price set is divided by the number of remaining commodity prices in the price set, and the resulting value is confirmed as the analysis price. Each analyzed price is determined to be within a preset price range, and the analyzed price within the preset price range is confirmed as the price of the listed product.

6. The fully automated product selection and listing method for cross-border e-commerce based on multiple platforms as described in claim 1, characterized in that, The step of obtaining product images corresponding to each of the listed product names based on the hot word information and each of the listed product names includes: After extracting each adjective from the hot word information and marking them as collocations, each collocation is combined with each of the listed product names to obtain multiple combination words corresponding to each of the listed product names. Step a: Determine the semantic rationality of each of the combined words; Step b: If each of the combined words contains both semantically reasonable and semantically unreasonable combined words, or if all of the combined words are semantically reasonable, then delete the semantically unreasonable combined words, and then perform a secondary combination of each of the combined words with the corresponding combined words of the listed product name to obtain at least one combined word corresponding to each of the listed product names, and then repeat steps a and b; if none of the combined words contain semantically reasonable combined words, then obtain the listed product image corresponding to each of the listed product names based on the combined words before combination.

7. A fully automated product selection and listing system for cross-border e-commerce based on multiple platforms, characterized in that, The system for implementing the method as described in any one of claims 1 to 6 includes: An acquisition unit is used to acquire target information; wherein, the target information includes a target region and a target platform, the target region reflects the region where the user sells goods, and the target platform is the e-commerce platform where the goods are listed; A pre-selection unit is used to obtain pre-selected product information based on the target information; wherein the pre-selected product information includes at least one pre-selected product name; The listing unit is used to obtain listing product information based on the pre-selected product information and the target platform; wherein, the listing product information includes at least one listing product information, and the listing product information includes the listing product name, listing product image and listing product price.

8. A fully automated product selection and listing device for cross-border e-commerce based on multiple platforms, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the method as described in any one of claims 1 to 6.

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