Multi-seller product matching method for malls

Abstract

To provide a multi-seller product matching method for a mall that improves matching efficiency. The method includes the steps of: constructing a standard database containing a plurality of standard products; obtaining a first product list consisting of products requested by a user and a second product list consisting of products offered by sellers on the mall based on the standard database; and obtaining a seller combination based on the first product list and the second product list. The seller combination is intended to provide all of the products in the first product list, and each seller in the seller combination has at least one product in the first product list.

Description

[Technical Field]

[0001] TECHNICAL FIELD Embodiments of the present application relate to the field of mall matching technology, and more particularly to a multi-merchant product matching method for malls. [Background technology]

[0002] With the rapid development of e-commerce, the number of merchants on shopping malls is increasing, and the product lineup is becoming more and more diverse. When shopping, users usually need to purchase multiple types of products, which may be distributed across different merchants. How to efficiently match users with a combination of merchants that can provide all the products they need has become an important issue in shopping mall operations. Conventional product matching methods have drawbacks such as low matching efficiency and low accuracy of matching results, and are unable to meet users' needs for quick and accurate purchases of multiple types of products. Summary of the Invention [Problem to be solved by the invention]

[0003] The embodiment of the present application provides a multi-merchant product matching method for a mall, which improves the technical problem in the related art that the matching efficiency of the product matching method is low. [Means for solving the problem]

[0004] To achieve the above object, the embodiments of the present application adopt the following technical solutions.

[0005] The present application provides a multi-seller product matching method for a mall, the method including the steps of: establishing a standard database containing a plurality of standard products; obtaining, based on the standard database, a first product list consisting of products requested by a user and a second product list consisting of products that sellers have listed on the mall; and obtaining a seller combination based on the first product list and the second product list, wherein the seller combination is for providing all the products in the first product list, and each seller in the seller combination has at least one product in the first product list.

[0006] In one possible implementation, the step of obtaining a seller combination based on the first product list and the second product list includes: generating a matching stack based on a preset matching rule and the second product list; obtaining matching sellers that have at least one product in the first product list based on the first product list, the second product list, and the matching stack; and determining a seller combination that has all products in the first product list based on the matching sellers and the first product list.

[0007] In one possible implementation, the preset matching rules include: dividing the products in the second product list into multiple mixed matching stacks including products belonging to multiple categories when the total number of products in the second product list is less than a threshold number; and dividing the high-proportion category products in the second product list solely into multiple first matching stacks and dividing the low-proportion category products into multiple second matching stacks based on the proportion of high-proportion category products in the second product list when the total number of products in the second product list is greater than a threshold number.

[0008] In one possible implementation, the step of obtaining matching sellers based on the first product list, the second product list, and the matching stack includes performing parallel matching for the first product list and each matching stack corresponding to the second product list, obtaining sellers that have products in the first product list, and identifying matching sellers based on the matching results for each matching stack.

[0009] In one possible implementation, the method further includes the steps of: obtaining a matching degree of each of the matching sellers, which indicates a matching degree between the matching seller and the first product list; determining a first recommendation degree of each of the seller combinations based on the matching degree and the number of matching sellers in the seller combination; and determining a seller combination to recommend based on the first recommendation degree.

[0010] In one possible implementation, the step of obtaining a matching degree of each of the matching sellers includes the steps of obtaining a number of items in the second product list that match with items in the first product list, a total price of the matched items, and a credit score of the seller; and determining a matching degree of the matching seller based on the number of matching items, the total price, the credit score, and a matching degree formula, wherein the matching degree formula is:

number

[0011] In one possible implementation mode, the step of determining a first recommendation degree for each of the seller combinations based on the matching degree and the number of matching sellers in the seller combinations includes the step of determining a first recommendation degree for each of the seller combinations based on the matching degree, the number of matching sellers, and a first recommendation degree formula, wherein the first recommendation degree formula is:

number

[0012] In one possible implementation, the method further includes obtaining the price and delivery time of each product in the first product list from the matching seller, and calculating a second recommendation degree for each of the seller combinations based on a second recommendation degree formula, wherein the second recommendation degree formula is:

number

number

[0013] In one possible implementation aspect, the step of constructing the standard database includes the steps of: acquiring product data for each product, the product data including predefined structured fields, the structured fields including at least one or more of a technical specification parameter set, a functional feature description set, and an international standard certification mark; generating a data entry template used to regulate the consistency of field names, measurement units, and data formats for products in the same category according to product classification rules; generating a standard product based on the data entry template and the product data, and constructing the standard database based on multiple standard products.

[0014] In one possible implementation, the method further includes generating an order set including multiple sub-orders, each sub-order corresponding to a single seller in the seller combination, based on the membership relationships between sellers in the seller combination and products in the first product list, and generating a consolidated payment link based on the order set. [Brief explanation of the drawings]

[0015] [Figure 1] 1 is a schematic flow chart of a matching method provided by some embodiments of the present application; [Figure 2] FIG. 1 is a schematic diagram of a trading card database provided by some embodiments of the present application. [Figure 3] FIG. 3 is a schematic diagram of products listed in the trading card database of FIG. 2. [Figure 4] FIG. 1 is a schematic diagram of a user selecting a trading card from a trading card database, provided by some embodiments. [Figure 5] FIG. 1 is a schematic diagram illustrating a merchant adding products in bulk based on a standard database, provided by some embodiments. [Figure 6] 1 is a schematic diagram of a matching list of merchant combinations recommended by a mall to a user, provided by some embodiments. DETAILED DESCRIPTION OF THE INVENTION

[0016] The following describes the technical solutions in the embodiments of the present application in conjunction with the drawings in the embodiments of the present application, and it is clear that the described embodiments do not include all the embodiments of the present application, but only include some of the embodiments of the present application.

[0017] Hereinafter, the terms "first," "second," etc. are used for descriptive purposes only and should not be understood as indicating or implying relative importance or implicitly specifying the number of technical features presented. Thus, a feature qualified by "first," "second," etc. may explicitly or implicitly include one or more of the feature. In the present description, unless otherwise limited, "plurality" means two or more than two.

[0018] In addition, in this application, directional terms such as "upper," "lower," "left," and "right" include, but are not limited to, definitions based on the orientation of the components in the drawings. It should be understood that these directional terms are relative concepts and are used for relative description and clarity, and may change depending on the orientation of the components in the drawings.

[0019] In this application, unless otherwise clearly specified or limited, the term "connection" should be understood in a broad sense. For example, "connection" may be a fixed connection, a detachable connection, or an integral connection, and may be directly interconnected or indirectly interconnected via an intermediate medium. Furthermore, the term "electrical connection" may refer to an electrical connection method that realizes signal transmission.

[0020] As used herein, "about," "approximately," or "generally" includes a stated value, a reference value that is within an acceptable range of deviation from the specified value, where the acceptable range of deviation would be determined, for example, by one of ordinary skill in the art, taking into account the measurement of interest and the error associated with measuring the particular quantity (i.e., limitations of the measurement system).

[0021] In the examples herein, words such as "by way of example" or "for example" may be used to denote an example, illustration, or explanation. In the examples herein, any embodiment or design described with "by way of example" or "for example" should not be construed as preferred or advantageous over other embodiments or designs. Specifically, words such as "by way of example" or "for example" are used.

[0022] With the rapid development of e-commerce, the number of merchants on shopping malls is increasing, and the product lineup is becoming more and more diverse. When shopping, users usually need to purchase multiple types of products, which may be distributed across different merchants. How to efficiently match users with a combination of merchants that can provide all the products they need has become an important issue in shopping mall operations. Conventional product matching methods have drawbacks such as low matching efficiency and low accuracy of matching results, and are unable to meet users' needs for quick and accurate purchases of multiple types of products.

[0023] The embodiment of the present application provides a multi-merchant product matching method for a mall, which solves the technical problem in the related art that the matching efficiency of the product matching method is low. As shown in Figure 1, the method includes the following steps:

[0024] In step S100, a standard database including a plurality of standard products is constructed. As an example, the procedure for constructing the standard database includes the following steps:

[0025] In step S110, product data of each product is acquired, and the product data is stored in a predefined structure. The structured field includes at least one of a technical specification parameter set, a functional feature description set, and an international standard certification mark. For example, in the case of a smartphone, the structured field of the product data may include technical specification parameters such as screen size, resolution, processor model, memory capacity, storage capacity, camera pixels, battery capacity, and operating system version, functional feature descriptions such as "full screen design," "rear triple camera," and "5G network support," as well as international standard certification marks such as "CE certification" and "FCC certification."

[0026] In step S120, a data entry template is generated according to the product classification rules to regulate the consistency of field names, units of measurement, and data formats for products in the same category. For example, for electronic products, the data entry template specifies that all products should have a screen size field name of "screen_size," a unit of measurement of "inches," a data format of two decimal places, a resolution field name of "resolution," and a data format of "width x height," e.g., "2400 x 1080."

[0027] In step S130, a standard product is generated based on the data entry template and the product data, and the standard database is constructed based on multiple standard products. For example, in the case of a smartphone listed by seller A, the product data is entered according to the data entry template, and after review and verification, standard product information for the smartphone is generated and stored in the standard database. For example, for accurate management and efficient matching, names of each standard database, such as a mobile phone database and a trading card database, can be customized. Figure 2 is an example of a trading card database provided by some embodiments of the present application, and Figure 3 is a schematic diagram of products listed in the trading card database of Figure 2.

[0028] In step S200, a first product list consisting of products requested by the user and a second product list consisting of products that sellers are selling on the mall are obtained based on the standard database.

[0029] As an example, the first product list may consist of products requested by the user. For example, the user may submit a shopping list (first product list) including products A, B, and C on a bulk product addition screen provided by the mall. Figure 4 is a schematic diagram of a user selecting trading cards from a trading card database, provided by some embodiments.

[0030] The second product list consists of products that sellers have listed on the mall. For example, seller 1 lists products A and D, seller 2 lists products B and E, and seller 3 lists products C and F. The figure shows a screen displaying a product list listed by sellers provided in some embodiments of the present application. Sellers can select and list corresponding products from the standard database established by the mall. Figure 5 is a schematic diagram of a seller adding products in bulk based on the standard database.

[0031] In step S300, a seller combination is obtained based on the first product list and the second product list, where the seller combination is for providing all the products in the first product list, and each seller in the seller combination has at least one product in the first product list.

[0032] As an example, a procedure for obtaining a seller combination based on a first product listing and a second product listing includes the following steps:

[0033] In step S310, matching stacks are generated based on a preset matching rule and the second product list. The preset matching rule includes: when the total number of products in the second product list is less than a threshold number, dividing the products in the second product list into a plurality of mixed matching stacks including products belonging to a plurality of categories; and when the total number of products in the second product list is greater than a threshold number, dividing high-proportion category products in the second product list solely into a plurality of first matching stacks and dividing low-proportion category products into a plurality of second matching stacks based on the proportion of high-proportion category products in the second product list.

[0034] For example, if the threshold number is 1,000 and the total number of products in the second product list is 800, these 800 products can be divided into four mixed matching stacks, each containing products from a different category. On the other hand, if the total number of products in the second product list is 2,000, with electronic products accounting for the highest proportion at 40%, followed by clothing products at 30% and household goods products at 30%, the electronic products can be divided into two first matching stacks, each containing only electronic products, and the clothing products and household goods can be divided into three second matching stacks, each containing both clothing products and household goods. In this way, when the number of products is large, it can be ensured that products in high-proportion categories are matched preferentially.

[0035] In step S320, obtain matching sellers that have at least one product in the first product list based on the first product list, the second product list, and the matching stack.

[0036] As an example, parallel matching is performed for the first product list and each matching stack corresponding to the second product list, sellers who have the products in the first product list are obtained, and matching sellers are identified based on the matching results for each matching stack. The parallel matching procedure compares the first product list with the product information in each matching stack and selects sellers who have the products in the first product list. For example, products A, B, and C in the first product list are compared with the product information in each matching stack to be matched. In the first matching stack (electronic products), product A (e.g., a smartphone) listed by seller 1 matches product A in the first product list, product B (e.g., a Bluetooth headset) listed by seller 2 matches product B in the first product list, and in the second matching stack (household goods), product C (e.g., a pillowcase) listed by seller 3 matches product C in the first product list. Parallel matching is performed on each matching stack to identify seller 1, seller 2, and seller 3, which are sellers that have products in the first product list.

[0037] In step S330, a seller combination that includes all the products in the first product list is determined based on the matching sellers and the first product list. For example, seller 1 provides product A (smartphone), seller 2 provides product B (Bluetooth earphones), and seller 3 provides product C (pillowcase). A seller combination can be determined to be seller 1, seller 2, and seller 3, which can provide all the products in the first product list, i.e., product A, product B, and product C.

[0038] In step S400, a matching degree of each matching seller is obtained, which indicates the degree of matching between the matching seller and the first product list. In step S400, in step S410, the number of products in the second product list that match with products in the first product list, the total price of the matched products, and the credit score of the seller are obtained.

[0039] As an example, the procedure for obtaining the degree of matching includes obtaining information such as the number of items in the second product listing that match with items in the first product listing, the total price of the matched items, and the seller's credit score.

[0040] For example, the above information is obtained by comparing the second product list with the first product list and aggregating the number of matching products, total price, and credit score of each matching seller. For example, for matching seller Seller 1, the number of matches is 1, the total price is 3,000 yuan, and the credit score is 80 points.

[0041] In step S420, the matching degree of the matching seller is calculated based on the number of matching products, the total price, the credit score, and a matching degree formula, which is:

number

[0042] In step S500, a first recommendation level for each of the seller combinations is calculated based on the matching level and the number of matching sellers in the seller combination, and a seller combination to be recommended is determined based on the first recommendation level. Step S500 includes the following steps:

[0043] In step S510, a first recommendation degree of each of the seller combinations is calculated based on the matching degree, the number of matching sellers, and a first recommendation degree formula. The first recommendation degree formula is:

number

[0044] When the matching degree and / or recommendation degree are calculated using the above data, the data may first be normalized, and the normalized data may be weighted to calculate the matching degree and / or recommendation degree. For example, a Min-Max normalization method may be used, but the present application is not limited to this, and those skilled in the art may select their own method.

[0045] In step S600, the price and delivery time of each product in the first product list from the matching seller are obtained, and a second recommendation degree of each of the seller combinations is calculated based on a second recommendation degree formula, and a seller combination to be recommended is determined based on the second recommendation degree. The second recommendation degree formula is:

number

number

[0046] In step S700, an order set including multiple sub-orders, each sub-order corresponding to a single seller in the seller combination, is generated based on the belonging relationships between sellers in the seller combination and products in the first product list, and a consolidated payment link is generated based on the order set.

[0047] For example, after selecting a seller combination, the user may select the sellers in the seller combination and the products in the first product list. An order set is generated based on the relationship, and a collective payment link is generated based on the order set. Specifically, the procedure for generating the order set allocates products to suborders of corresponding sellers based on the belonging relationship between the sellers in the seller combination and the products in the first product list. For example, for a seller combination of seller 1, seller 2, and seller 3, seller 1 provides product A (smartphone), seller 2 provides product B (Bluetooth earphones), and seller 3 provides product C (pillowcase). The generated order set includes seller 1's suborder (product A), seller 2's suborder (product B), and seller 3's suborder (product C). A collective payment link is then generated based on each order set, and the user can pay for all the products in one go via the collective payment link.

[0048] As shown in FIG. 6, which is a matching list of merchant combinations recommended to users by the mall, users can select each merchant combination based on this list to make purchases and payments.

[0049] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods of the above embodiments can be realized by adding a required general-purpose hardware platform to software (of course, hardware is also possible, but in many cases the former is a better implementation method). Based on this understanding, the technical solution of the present application, in essence or in part contributing to the related art, can be embodied in the form of a software product. The computer software product can be stored in a storage medium (e.g., ROM / RAM, magnetic disk, optical disk) and includes several instructions for causing a terminal device (which may be a mobile phone, computer, server, network device, etc.) to execute the methods of each embodiment of the present invention.

[0050] In the description of the above embodiments, for convenience and simplicity, examples have been given using the division of each of the above-mentioned functional modules. However, those skilled in the art will clearly understand that in actual applications, the above functions can be allocated as needed and realized by different functional modules, i.e., the internal structure of the device can be divided into different functional modules to realize all or part of the above-mentioned functions.

[0051] It will be understood that the disclosed devices and methods may be implemented in other ways in the embodiments provided herein. For example, the device embodiments described above are merely exemplary, and the division of modules or units is merely a division of logical functions. In actual implementation, other division methods may be used. For example, multiple units or components may be combined or integrated into another device, or some features may be omitted or not implemented. Furthermore, the shown or discussed mutual couplings or direct couplings or communication connections may be indirect couplings or communication connections via some interfaces, devices, or units, which may be electrical, mechanical, or other forms.

[0052] The units described as separate components may or may not be physically separated, and the components shown as units may be one physical unit or multiple physical units, i.e., located in one place or distributed in multiple different locations. Some or all of the units may be selected according to actual needs to achieve the purpose of the proposal of this embodiment.

[0053] Furthermore, each functional unit in each embodiment of the present application may be integrated into one processing unit, each unit may exist physically separately, or two or more units may be integrated into one unit. The integrated unit may be realized in the form of hardware.

[0054] The above content is merely a specific embodiment of the present application, and the scope of protection of the present application is not limited thereto, and any modifications or replacements within the technical scope disclosed in the present application should be included within the scope of protection of the present application. Therefore, the scope of protection of the present application shall be governed by the claims.

Claims

1. 1. A computer-implemented multi-merchant product matching method for a mall, comprising: constructing a standard database containing a plurality of standard products; A step of obtaining a first product list consisting of products requested by a user and a second product list consisting of products that a seller has put up for sale on the mall based on the standard database; obtaining a seller combination based on the first product list and the second product list, the seller combination being for providing all products in the first product list, and sellers in the seller combination having at least one product in the first product list; Including, The step of obtaining a seller combination based on the first product list and the second product list includes: generating a matching stack based on a preset matching rule and the second product list; obtaining matching sellers that have at least one product in the first product list based on the first product list, the second product list, and the matching stack; determining a seller combination that includes all products in the first product list based on the matching sellers and the first product list; The preset matching rule is: If the total number of items in the second product list is less than a threshold number, dividing the items in the second product list into a plurality of mixed matching stacks including items belonging to a plurality of categories; If the total number of products in the second product list is greater than a threshold number, dividing the high proportion category products in the second product list into a plurality of first matching stacks and dividing the low proportion category products into a plurality of second matching stacks based on the proportion of the high proportion category products in the second product list. A multi-seller product matching method for a mall.

2. The step of obtaining a matching seller based on the first product listing, the second product listing, and the matching stack includes: performing parallel matching for the first product list and each matching stack corresponding to the second product list, obtaining sellers that have products in the first product list, and identifying matching sellers based on the matching results for each matching stack.

2. The method for multi-merchant product matching for a mall according to claim 1.

3. obtaining a matching degree of each of the matching sellers, the matching degree indicating a matching degree between the matching seller and the first product listing; calculating a first recommendation degree for each of the seller combinations based on the matching degree and the number of matching sellers in the seller combinations, and determining a seller combination to recommend based on the first recommendation degree; The method of claim 1 further comprising:

4. The step of obtaining the matching degree of each of the matching sellers includes: obtaining a number of items in the second product list that match items in the first product list, a total price of the matched items, and a credit score of the seller; and determining a matching degree of the matching seller based on the number of matching products, the total price, the credit score, and a matching degree formula, wherein the matching degree formula is: [Equation 1] and Here, S ｊ is the matching degree, and M ｊ is the number of matching products, and P ｊ is the total price, and R ｊ is the seller's credit score, and W １ , W ２ and W ３ is the weighting coefficient 4. The method for matching products among multiple sellers for a mall according to claim 3.

5. The step of determining a first recommendation degree for each seller combination based on the matching degree and the number of matching sellers in the seller combination includes: and calculating a first recommendation degree for each of the seller combinations based on the matching degree, the number of matching sellers, and a first recommendation degree formula, wherein the first recommendation degree formula is: [Equation 2] Here, S ｊ is the matching degree, and S Ｎ is the number of matching sellers, and K ２ is the adjustment coefficient for the number of sellers, and K ２ The range of possible values ​​for is 0 to 1.

4. The method for matching products among multiple sellers for a mall according to claim 3.

6. The method further includes obtaining a price and a delivery time of each product in the first product list from the matching seller, and calculating a second recommendation degree of each of the seller combinations based on a second recommendation degree formula, wherein the second recommendation degree formula is: [Equation 3] and where m is the number of matching sellers in the seller combination, F ｊ is the shipping fee for seller j, and p ｉｊ is the price of product i at seller j, and t ｊ is the seller's expected delivery time, λ is the time sensitivity coefficient, k ｊ is the minimum product number threshold, [Equation 4] is 2. The method for multi-merchant product matching for a mall according to claim 1.

7. said step of constructing a normative database comprising: acquiring product data for each product, the product data including predefined structured fields, the structured fields including at least one or more of a technical specification parameter set, a functional feature description set, and an international standard certification mark; generating a data entry template used to regulate the consistency of field names, units of measure, and data formats for products in the same category according to product classification rules; generating standard products based on the data entry template and the product data, and building the standard database based on a plurality of standard products.

2. The method for multi-merchant product matching for a mall according to claim 1.

8. generating an order set including a plurality of sub-orders, each sub-order corresponding to a single seller in the seller combination, based on the membership relationships between sellers in the seller combination and products in the first product list; and generating a consolidated payment link based on the order set. The method for multi-merchant product matching for a mall according to any one of claims 1 to 7.

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