E-commerce Order Management Method, System and Storage Medium

Abstract

The present invention provides an e-commerce order management method, system and storage medium, belonging to the technical field of data processing. Specifically, it includes: determining the commodities of different e-commerce orders based on the parsing results of the order data of the e-commerce orders in the e-commerce platform, determining the historical order data of the commodities and other commodities in the same order and the same user in the e-commerce platform, and combining the types of the commodities to determine the correlation coefficients between the commodities and other commodities and the associated commodities among other commodities, obtaining the associated commodities of the commodities in different e-commerce orders and the correlation coefficients with the associated commodities, and combining the similar orders of the e-commerce orders to determine the probability of the merger processing of the e-commerce orders. According to the probability of the merger processing of different e-commerce orders in the e-commerce platform, the monitoring frequency of the acquisition processing of the e-commerce orders in the e-commerce platform is determined, laying a foundation for reducing the express delivery cost.

Description

Technical Field

[0001] The present invention belongs to the technical field of data processing, and particularly relates to an e-commerce order management method, system and storage medium. Background Art

[0002] In order to implement the handling of the sender of orders on the e-commerce platform, in the prior art solution in CN202211277535.4 "Express Delivery Sending Method, Device, System and Sending Number Book", the target express company is determined through the information input by the sending code and the sending authority, and express delivery is carried out. However, there are the following technical problems:

[0003] For the e-commerce orders of merchants on the e-commerce platform, the situation where the same user places orders repeatedly often occurs. In the prior art solutions, different express delivery numbers are often used for different e-commerce orders, so that the express delivery costs of merchants cannot be effectively controlled.

[0004] In view of the above technical problems, specifically, the present application provides an e-commerce order management method, system and storage medium. Summary of the Invention

[0005] To achieve the object of the present invention, the present invention adopts the following technical solutions:

[0006] According to one aspect of the present invention, an e-commerce order management method is provided.

[0007] An e-commerce order management method specifically includes:

[0008] S1 Based on the acquisition result of the e-commerce orders on the e-commerce platform, determine the similar e-commerce orders in the e-commerce platform. When it is determined that the acquisition process of the e-commerce orders on the e-commerce platform does not need to be carried out at a preset monitoring frequency by using the similar e-commerce orders in the e-commerce platform and the order data of the e-commerce orders, proceed to the next step;

[0009] S2 Based on the parsing result of the order data of the e-commerce orders in the e-commerce platform, determine the commodities of different e-commerce orders, determine the historical order data of the commodities and other commodities in the same order and the same user in the e-commerce platform, and combine the type of the commodities to determine the correlation coefficient between the commodities and other commodities and the associated commodities among other commodities;

[0010] S3 Obtain the associated commodities of the commodities in different e-commerce orders and the correlation coefficients with the associated commodities, and determine the probability of combining the e-commerce orders in combination with the similar orders of the e-commerce orders;

[0011] S4 According to the probability of combining the different e-commerce orders in the e-commerce platform, determine the monitoring frequency of the acquisition process of the e-commerce orders in the e-commerce platform.

[0012] The beneficial effects of the present invention are as follows:

[0013] By using the associated products in different e-commerce orders, the correlation coefficients with the associated products, and the similar orders of the e-commerce orders to determine the probability of merging e-commerce orders, it not only takes into account the differences in the possible probabilities of subsequent order mergers caused by the differences in the degree of association of the associated products in the e-commerce orders, but also takes into account the differences in the possible probabilities of existing e-commerce orders being merged due to the number of similar orders of the e-commerce orders. It realizes the determination of the probability of merging e-commerce orders from multiple perspectives and also lays a foundation for further determining the differentiated monitoring frequency.

[0014] According to the probability of merging different e-commerce orders in the e-commerce platform, determine the monitoring frequency for obtaining and processing the e-commerce orders of the e-commerce platform, and realize the evaluation of the differences in the possibilities of order mergers occurring in the e-commerce platform from the number of e-commerce orders and the probability of merging different e-commerce orders. Thus, on the basis of ensuring the real-time monitoring and processing of e-commerce platforms with a relatively high probability of order mergers, it also reduces the difficulty of monitoring and processing e-commerce orders.

[0015] A further technical solution is that the similar e-commerce orders are e-commerce orders in which any one of the order information and the order account in the e-commerce platform is the same.

[0016] A further technical solution is that determining not to use the preset monitoring frequency for obtaining and processing the e-commerce orders of the e-commerce platform specifically includes:

[0017] Using the order data of the e-commerce orders of the e-commerce platform to determine the number of e-commerce orders of the e-commerce platform;

[0018] Based on the number of similar e-commerce orders in the e-commerce platform, determine the proportion of the number of similar e-commerce orders in the e-commerce orders;

[0019] Based on the number of the e-commerce platform and the proportion of the number of similar e-commerce orders in the e-commerce orders, determine whether to use the preset monitoring frequency for obtaining and processing the e-commerce orders of the e-commerce platform.

[0020] A further technical solution is that based on the number of the e-commerce platform and the proportion of the number of similar e-commerce orders in the e-commerce orders, determining whether to use the preset monitoring frequency for obtaining and processing the e-commerce orders of the e-commerce platform specifically includes:

[0021] Based on the number of the e-commerce platform, determine the preset proportion threshold corresponding to the number of the e-commerce platform;

[0022] Determine whether it is necessary to obtain and process the e-commerce orders of the e-commerce platform using a preset monitoring frequency according to the preset quantity proportion threshold and the quantity proportion of similar e-commerce orders in the e-commerce orders.

[0023] A further technical solution is that the value range of the merging processing probability of the e-commerce orders is between 0 and 1, where the greater the merging processing probability of the e-commerce platform, the greater the probability that the e-commerce orders will be merged in the future.

[0024] A further technical solution is that the method for determining the monitoring frequency of obtaining and processing the e-commerce orders of the e-commerce platform is as follows:

[0025] Based on the merging processing probabilities of different e-commerce orders in the e-commerce platform, determine the e-commerce orders with a merging processing probability greater than a preset probability threshold, and use them as high-probability orders;

[0026] Determine the monitoring frequency of obtaining and processing the e-commerce orders of the e-commerce platform through the quantity of the high-probability orders.

[0027] A further technical solution is that determining the monitoring frequency of obtaining and processing the e-commerce orders of the e-commerce platform through the quantity of the high-probability orders specifically includes:

[0028] Based on the quantity of the high-probability orders, determine the preset monitoring frequency corresponding to the quantity of the high-probability orders;

[0029] Determine the monitoring frequency of obtaining and processing the e-commerce orders of the e-commerce platform through the preset monitoring frequency.

[0030] In a second aspect, the present invention provides a computer system, including: a memory and a processor connected by communication, and a computer program stored on the memory and capable of running on the processor, where when the processor runs the computer program, it executes the above-mentioned e-commerce order management method.

[0031] In a third aspect, the present invention provides a computer storage medium, on which a computer program is stored, and when the computer program is executed in a computer, it causes the computer to execute the above-mentioned e-commerce order management method.

[0032] Other features and advantages will be described in the subsequent description, and the objectives and other advantages of the present invention are achieved and obtained by the structures specifically pointed out in the description and the drawings.

[0033] To make the above-mentioned objectives, features, and advantages of the present invention more obvious and understandable, the following specifically enumerates preferred embodiments and, in conjunction with the accompanying drawings, makes a detailed description as follows. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] The above and other features and advantages of the present invention will become more apparent by describing its exemplary embodiments in detail with reference to the accompanying drawings;

[0035] Figure 1 is a flowchart of a method for managing e-commerce orders;

[0036] Figure 2 is a flowchart for determining that the acquisition process of e-commerce orders on the e-commerce platform does not need to adopt a preset monitoring frequency;

[0037] Figure 3 is a flowchart of a method for determining a correlation coefficient;

[0038] Figure 4 is a flowchart of a method for determining the merging processing probability of e-commerce orders;

[0039] Figure 5 is a framework diagram of a computer system. Specific Embodiments

[0040] In order to enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below with reference to the accompanying drawings in the embodiments of this specification. Obviously, the described embodiments are only a part of the embodiments of this specification, rather than all the embodiments. Based on the embodiments of this specification, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of this specification.

[0041] For the e-commerce orders of merchants on the e-commerce platform, the situation where the same user places repeated orders often occurs. In the existing technical solutions, different courier numbers are often used for different e-commerce orders. Therefore, it is necessary to merge the couriers of the e-commerce orders in the e-commerce platform to reduce the courier cost.

[0042] Determine that the acquisition process of e-commerce orders on the e-commerce platform does not need to adopt a preset monitoring frequency: determine the preset quantity proportion threshold corresponding to the number of e-commerce platforms based on the number of e-commerce platforms. When the quantity proportion of similar e-commerce orders in the e-commerce orders is greater than the preset quantity proportion threshold, it is determined that the acquisition process of e-commerce orders on the e-commerce platform needs to adopt a preset monitoring frequency.

[0043] The correlation coefficient between a product and other products: determine the products that need to be used simultaneously with the product during use and the products with the same usage object as the product based on the type of the product, and use them as basic associated products. Use the historical orders of the product and the basic associated products in the same order and the same user as associated historical orders, and determine the correlation coefficient between the product and the basic associated products according to the proportion of the number of associated historical orders in the number of orders including the product.

[0044] Associated products among other products: Products with a correlation coefficient greater than 0.6 are regarded as associated products.

[0045] Combined processing probability: Determine the similarity combination probability of an e-commerce order based on the ratio of the number of similar orders of the e-commerce order to a preset number. Determine the sum of the weights of the correlation coefficients of different products in the e-commerce order according to the sum of the weights of the correlation coefficients of the associated products of the products in the e-commerce order. After performing normalization summation processing on the sum of the weights of the correlation coefficients of different products, obtain the combined association probability. Use the average value of the similarity combination probability and the combined association probability to determine the combined processing probability of the e-commerce order.

[0046] Monitoring frequency for obtaining and processing e-commerce orders on an e-commerce platform: Based on the combined processing probabilities of different e-commerce orders on the e-commerce platform, determine the e-commerce orders with a combined processing probability greater than a preset probability threshold, and regard them as high-probability orders. Based on the number of high-probability orders, determine the preset monitoring frequency corresponding to the number of high-probability orders, and determine the monitoring frequency for obtaining and processing e-commerce orders on the e-commerce platform through the preset monitoring frequency. Embodiment 1

[0047] To solve the above problems, according to one aspect of the present invention, as Figure 1 shown, the first aspect is provided. The present invention provides an e-commerce order management method, which specifically includes:

[0048] S1 Based on the obtained results of e-commerce orders on the e-commerce platform, determine the similar e-commerce orders in the e-commerce platform. When it is determined that the obtaining and processing of e-commerce orders on the e-commerce platform do not require the use of a preset monitoring frequency by using the similar e-commerce orders on the e-commerce platform and the order data of the e-commerce order, proceed to the next step;

[0049] Furthermore, the similar e-commerce orders are e-commerce orders with the same order information or order account on the e-commerce platform.

[0050] Specifically, as Figure 2 shown, determining that the obtaining and processing of e-commerce orders on the e-commerce platform do not require the use of a preset monitoring frequency specifically includes:

[0051] Use the order data of the e-commerce orders on the e-commerce platform to determine the number of e-commerce orders on the e-commerce platform;

[0052] Based on the number of similar e-commerce orders in the e-commerce platform, determine the proportion of the number of similar e-commerce orders in the e-commerce orders;

[0053] Determine whether it is necessary to obtain and process the e-commerce orders of the e-commerce platform using a preset monitoring frequency based on the number of the e-commerce platforms and the proportion of the number of similar e-commerce orders in the number of the e-commerce orders.

[0054] It can be understood that determining whether it is necessary to obtain and process the e-commerce orders of the e-commerce platform using a preset monitoring frequency based on the number of the e-commerce platforms and the proportion of the number of similar e-commerce orders in the number of the e-commerce orders specifically includes:

[0055] Determine the preset quantity proportion threshold corresponding to the number of the e-commerce platforms based on the number of the e-commerce platforms;

[0056] Determine whether it is necessary to obtain and process the e-commerce orders of the e-commerce platform using a preset monitoring frequency according to the preset quantity proportion threshold and the proportion of the number of similar e-commerce orders in the number of the e-commerce orders.

[0057] Further, when the proportion of the number of the similar e-commerce orders in the number of the e-commerce orders is greater than the preset quantity proportion threshold, it is determined that it is necessary to obtain and process the e-commerce orders of the e-commerce platform using a preset monitoring frequency.

[0058] In another embodiment, determining that it is not necessary to obtain and process the e-commerce orders of the e-commerce platform using a preset monitoring frequency specifically includes:

[0059] Use the order data of the e-commerce orders of the e-commerce platform to determine the number of the e-commerce orders of the e-commerce platform;

[0060] Determine the proportion of the number of the similar e-commerce orders in the number of the e-commerce orders based on the number of the similar e-commerce orders in the e-commerce platforms;

[0061] Divide the e-commerce orders that are similar e-commerce orders into similar order groups, use the similar order groups with the number of orders greater than the preset order quantity as the screened order groups, determine the product ratio according to the product of the proportion of the number of the e-commerce orders of the screened order groups in the number of the e-commerce orders and the proportion of the number of the similar e-commerce orders in the number of the e-commerce orders, and use the product ratio to determine whether it is necessary to obtain and process the e-commerce orders of the e-commerce platform using a preset monitoring frequency.

[0062] In another embodiment, determining that it is not necessary to obtain and process the e-commerce orders of the e-commerce platform using a preset monitoring frequency specifically includes:

[0063] S11 Use the order data of e-commerce orders on the e-commerce platform to determine the number of e-commerce orders on the e-commerce platform, determine the proportion of the number of similar e-commerce orders in the e-commerce orders on the e-commerce platform, and determine the basic monitoring demand coefficient based on the number of e-commerce orders and the proportion of the number of similar e-commerce orders in the e-commerce orders;

[0064] S12 Divide e-commerce orders that are similar to each other into similar order groups, and determine the repetition coefficients of different similar order groups according to the number of orders in different similar order groups;

[0065] S13 Use the basic monitoring demand coefficient and the repetition coefficients of different similar order groups to determine the comprehensive monitoring demand coefficient, and determine whether to obtain and process the e-commerce orders on the e-commerce platform using a preset monitoring frequency according to the comprehensive monitoring demand coefficient.

[0066] Optionally, determining the basic monitoring demand coefficient based on the number of e-commerce orders and the proportion of the number of similar e-commerce orders in the e-commerce orders specifically includes:

[0067] Determine the e-commerce order proportion coefficient by the ratio of the number of e-commerce orders to the preset number of e-commerce orders, and determine the basic monitoring demand coefficient by the product of the proportion of the number of similar e-commerce orders in the e-commerce orders and the e-commerce order proportion coefficient.

[0068] Further, the repetition coefficient of the similar order group is determined according to the preset repetition coefficient corresponding to the number of orders in the similar order group.

[0069] Optionally, the above step S11 includes the following content:

[0070] S111 Use the order data of e-commerce orders on the e-commerce platform to determine the number of e-commerce orders on the e-commerce platform. When the number of e-commerce orders on the e-commerce platform is greater than the order quantity set value, it is determined that the acquisition and processing of e-commerce orders on the e-commerce platform need to use a preset monitoring frequency. When the number of e-commerce orders on the e-commerce platform is not greater than the order quantity set value, it proceeds to step S112;

[0071] S112 When the number of e-commerce orders on the e-commerce platform is within the preset order quantity range, it proceeds to step S113. When the number of e-commerce orders on the e-commerce platform is not within the preset order quantity range, it proceeds to step S114;

[0072] S113 Determine the proportion of the similar e-commerce orders in the e-commerce orders based on the number of similar e-commerce orders in the e-commerce platform. When the proportion is greater than the preset proportion, it is determined that the acquisition process of the e-commerce orders in the e-commerce platform needs to be performed at the preset monitoring frequency. When the proportion is not greater than the preset proportion, proceed to step S114;

[0073] S114 Determine the basic monitoring demand coefficient based on the number of the e-commerce orders and the proportion of the similar e-commerce orders in the e-commerce orders. When the basic monitoring demand coefficient is greater than the preset demand coefficient threshold, it is determined that the acquisition process of the e-commerce orders in the e-commerce platform needs to be performed at the preset monitoring frequency. When the basic monitoring demand coefficient is not greater than the preset demand coefficient threshold, proceed to step S12.

[0074] S2 Determine the products of different e-commerce orders based on the parsing results of the order data of the e-commerce orders in the e-commerce platform, determine the historical order data of the products and other products in the e-commerce platform in the same order and the same user's orders, and determine the correlation coefficient between the products and other products and the associated products among other products in combination with the types of the products;

[0075] Further, the historical order data includes the historical order quantity.

[0076] Specifically, as Figure 3 shown, the method for determining the correlation coefficient is:

[0077] Determine the products that need to be used simultaneously with the product during use and the products with the same usage object as the product based on the type of the product, and use them as the basic associated products;

[0078] Take the historical orders of the product and the basic associated products in the same order and the same user as the associated historical orders;

[0079] Determine the correlation coefficient between the product and the basic associated products according to the number of the associated historical orders.

[0080] Optionally, when the other product does not belong to the basic associated product, it is determined that the correlation coefficient between the other product and the product is 0. When the other product belongs to the basic associated product, the correlation coefficient between the product and the basic associated product is determined by using the preset correlation coefficient corresponding to the number of the associated historical orders.

[0081] Further, when the correlation coefficient between the product and the basic associated product is greater than the preset correlation coefficient, it is determined that the basic associated product is an associated product.

[0082] In another embodiment, the method for determining the correlation coefficient is:

[0083] Determine the products that need to be used simultaneously with the product during use and the products with the same user of the product according to the type of the product, and use them as basic associated products. When the other product does not belong to the basic associated products, it is determined that the other product does not belong to the associated products;

[0084] When the other product belongs to the basic associated products:

[0085] Take the orders of the product and the basic associated products in the same order and the historical orders of the same user as associated historical orders. When the number of the associated historical orders is less than the preset number of associated orders, it is determined that the other product does not belong to the associated products;

[0086] When the number of the associated orders is not less than the preset number of associated orders:

[0087] Determine the basic association coefficient between the basic associated product and the product according to the simultaneous use situation of the basic associated product and the product and the matching situation of the users. When the basic association coefficient between the basic associated product and the product is less than the preset basic coefficient threshold:

[0088] Obtain the number of the product and the basic associated product in the same order and the number of the historical orders of the same user. When both the number of the product and the basic associated product in the same order and the number of the historical orders of the same user are within the preset quantity range, it is determined that the other product does not belong to the associated products;

[0089] When any one of the number of the product and the basic associated product in the same order and the number of the historical orders of the same user is not within the preset quantity range:

[0090] When the number of the same users is less than the preset user quantity threshold, it is determined that the other product does not belong to the associated products;

[0091] When the basic association coefficient between the basic associated product and the product is not less than the preset basic coefficient threshold or the number of the same users is not less than the preset user quantity threshold:

[0092] Determine the order association coefficient according to the associated order quantities of different same users, and determine the association coefficient between the product and the basic associated product in combination with the basic association coefficient between the basic associated product and the product.

[0093] S3 Obtain the associated products of the products in different e-commerce orders and the association coefficients with the associated products, and determine the probability of merging the e-commerce orders in combination with the similar orders of the e-commerce orders;

[0094] Specifically, such as Figure 4As shown, the method for determining the merging processing probability of the e-commerce order is as follows:

[0095] Determine the similarity merging probability of the e-commerce order by the ratio of the number of similar orders of the e-commerce order to a preset number;

[0096] According to the weight sum of the correlation coefficients of the associated products in the e-commerce order, determine the weight sum of the correlation coefficients of different products in the e-commerce order, and after normalizing and summing the weight sums of the correlation coefficients of different products, obtain the correlation merging probability;

[0097] Use the average value of the similarity merging probability and the correlation merging probability to determine the merging processing probability of the e-commerce order.

[0098] Furthermore, the value range of the merging processing probability of the e-commerce order is between 0 and 1. Among them, the greater the merging processing probability of the e-commerce platform, the greater the probability that the e-commerce order will be merged in the future.

[0099] S4 Determine the monitoring frequency of the acquisition processing of the e-commerce orders in the e-commerce platform according to the merging processing probabilities of different e-commerce orders in the e-commerce platform.

[0100] It should be noted that the method for determining the monitoring frequency of the acquisition processing of the e-commerce orders in the e-commerce platform is as follows:

[0101] Based on the merging processing probabilities of different e-commerce orders in the e-commerce platform, determine the e-commerce orders with a merging processing probability greater than a preset probability threshold, and use them as high-probability orders;

[0102] Determine the monitoring frequency of the acquisition processing of the e-commerce orders in the e-commerce platform through the number of the high-probability orders.

[0103] Furthermore, determining the monitoring frequency of the acquisition processing of the e-commerce orders in the e-commerce platform through the number of the high-probability orders specifically includes:

[0104] Based on the number of the high-probability orders, determine the preset monitoring frequency corresponding to the number of the high-probability orders;

[0105] Determine the monitoring frequency of the acquisition processing of the e-commerce orders in the e-commerce platform through the preset monitoring frequency.

[0106] In another embodiment, the method for determining the monitoring frequency of the acquisition processing of the e-commerce orders in the e-commerce platform is as follows:

[0107] Based on the number of e-commerce orders in the e-commerce platform, determine the preset monitoring frequency at the number of the e-commerce orders;

[0108] Based on the merging processing probabilities of different e-commerce orders in the e-commerce platform, determine the average value of the merging processing probabilities of different e-commerce platforms, and use it as the average merging processing probability;

[0109] Determine the monitoring frequency of obtaining and processing e-commerce orders of the e-commerce platform through the preset monitoring frequency and the average merging processing probability.

[0110] Further, determining the monitoring frequency of obtaining and processing e-commerce orders of the e-commerce platform through the preset monitoring frequency and the average merging processing probability specifically includes:

[0111] Based on the ratio of the preset monitoring frequency to the average merging processing probability, determine the monitoring frequency of obtaining and processing e-commerce orders of the e-commerce platform. Embodiment 2

[0112] In a second aspect, as Figure 5 shown, the present invention provides a computer system, including: a memory and a processor connected by communication, and a computer program stored on the memory and capable of running on the processor, and when the processor runs the computer program, it executes the above-mentioned e-commerce order management method.

[0113] Optionally, the above step S12 includes the following content:

[0114] S121 Obtain the number of similar e-commerce orders in the e-commerce platform. When the number of similar e-commerce orders in the e-commerce platform is within the preset similar order quantity range, go to step S122; when the number of similar e-commerce orders in the e-commerce platform is not within the preset similar order quantity range, go to step S123;

[0115] S122 Divide e-commerce orders that are similar to each other into similar order groups. When the number of similar order groups is greater than the preset order group quantity, it is determined that the preset monitoring frequency needs to be used for obtaining and processing e-commerce orders of the e-commerce platform. When the number of similar order groups is not greater than the preset order group quantity, go to step S123;

[0116] S123 Determine the repetition coefficients of different similar order groups according to the order quantities in different similar order groups. When there is a similar order group with a repetition coefficient greater than the preset repetition coefficient, go to step S124; when there is no similar order group with a repetition coefficient not greater than the preset repetition coefficient, go to step S13;

[0117] When the number of groups of similar order groups with a repetition coefficient greater than the preset repetition coefficient does not meet the requirements, it is determined that the acquisition process of e-commerce orders on the e-commerce platform needs to be performed at the preset monitoring frequency. When the number of groups of similar order groups with a repetition coefficient greater than the preset repetition coefficient meets the requirements, it proceeds to step S13. Embodiment III

[0118] In a third aspect, the present invention provides a computer storage medium, on which a computer program is stored. When the computer program is executed on a computer, the computer is made to execute the above-mentioned e-commerce order management method.

[0119] Specifically, the method for determining the monitoring frequency of the acquisition process of e-commerce orders on the e-commerce platform is as follows:

[0120] Obtain the number of e-commerce orders in the e-commerce platform. When the number of e-commerce orders in the e-commerce platform is greater than the preset order quantity, the monitoring frequency of the acquisition process of e-commerce orders on the e-commerce platform is determined using the preset monitoring frequency;

[0121] When the number of e-commerce orders in the e-commerce platform is not greater than the preset order quantity:

[0122] Based on the number of e-commerce orders in the e-commerce platform, when it is determined that the number of e-commerce orders in the e-commerce platform is within the preset order quantity range:

[0123] Obtain the merging processing probabilities of different e-commerce orders. When the average value of the merging processing probabilities of different e-commerce orders is greater than the preset merging probability threshold, the monitoring frequency of the acquisition process of e-commerce orders on the e-commerce platform is determined using the preset monitoring frequency;

[0124] When the number of e-commerce orders in the e-commerce platform is not within the preset order quantity range or the average value of the merging processing probabilities of different e-commerce orders is not greater than the preset merging probability threshold:

[0125] Based on the merging processing probabilities of different e-commerce orders in the e-commerce platform, determine the e-commerce orders with a merging processing probability greater than the preset probability threshold and use them as high-probability orders. When the number of high-probability orders is greater than the preset high-probability order quantity threshold, the monitoring frequency of the acquisition process of e-commerce orders on the e-commerce platform is determined using the preset monitoring frequency;

[0126] When the number of high-probability orders is not greater than the preset high-probability order quantity threshold:

[0127] Determine a preset monitoring frequency at the quantity of e-commerce orders in the e-commerce platform. Based on the merging processing probabilities of different e-commerce orders in the e-commerce platform, determine the average value of the merging processing probabilities of different e-commerce platforms, and use it as the average value of the merging processing probability.

[0128] Determine the monitoring frequency for obtaining and processing e-commerce orders in the e-commerce platform through the preset monitoring frequency and the average value of the merging processing probability.

[0129] Each embodiment in this specification is described in a progressive manner. For the same or similar parts among the embodiments, reference can be made to each other. Each embodiment focuses on the differences from other embodiments. In particular, for the embodiments of the device, equipment, and non-volatile computer storage medium, since they are basically similar to the method embodiments, the description is relatively simple, and the relevant parts can refer to the partial description of the method embodiments.

[0130] The specific embodiments of this specification are described above. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims can be executed in a different order from that in the embodiments and still achieve the desired results. Additionally, the processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In certain embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0131] The above is only one or more embodiments of this specification and is not intended to limit this specification. For those skilled in the art, one or more embodiments of this specification can have various changes and modifications. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of one or more embodiments of this specification shall be included within the scope of the claims of this specification.

Claims

1. An e-commerce order management method, characterized in that, Specifically include: Based on the acquisition result of the e-commerce orders on the e-commerce platform, determine the similar e-commerce orders in the e-commerce platform. When it is determined that the acquisition process of the e-commerce orders on the e-commerce platform does not need to adopt the preset monitoring frequency by using the similar e-commerce orders in the e-commerce platform and the order data of the e-commerce orders, proceed to the next step; Based on the parsing result of the order data of the e-commerce orders in the e-commerce platform, determine the commodities of different e-commerce orders, determine the historical order data of the same order and the same user of the commodity and other commodities in the e-commerce platform, and determine the correlation coefficient between the commodity and other commodities and the associated commodities in other commodities in combination with the type of the commodity; Obtain the associated commodities of the commodities in different e-commerce orders and the correlation coefficients with the associated commodities, and determine the probability of the combined processing of the e-commerce orders in combination with the similar orders of the e-commerce orders; According to the probability of the combined processing of different e-commerce orders in the e-commerce platform, determine the monitoring frequency of the acquisition process of the e-commerce orders on the e-commerce platform; Determining that the acquisition process of the e-commerce orders on the e-commerce platform does not need to adopt the preset monitoring frequency specifically includes: Using the order data of the e-commerce orders on the e-commerce platform, determine the number of the e-commerce orders on the e-commerce platform; Based on the number of the similar e-commerce orders in the e-commerce platform, determine the proportion of the number of the similar e-commerce orders in the e-commerce orders; Based on the number of the e-commerce platform and the proportion of the number of the similar e-commerce orders in the e-commerce orders, determine whether it is necessary to adopt the preset monitoring frequency for the acquisition process of the e-commerce orders on the e-commerce platform; The method for determining the probability of the combined processing of the e-commerce orders is: Determine the similar combination probability of the e-commerce orders based on the ratio of the number of the similar orders of the e-commerce orders and a preset number; According to the sum of the weights of the correlation coefficients of the associated commodities of the commodities in the e-commerce orders, determine the sum of the correlation coefficient weights of different commodities in the e-commerce orders, and obtain the combined correlation probability after performing the normalization summation processing on the sum of the correlation coefficient weights of different commodities; Use the average value of the similar combination probability and the combined correlation probability to determine the probability of the combined processing of the e-commerce orders; The method for determining the monitoring frequency of the acquisition process of the e-commerce orders on the e-commerce platform is: Based on the number of the e-commerce orders in the e-commerce platform, determine the preset monitoring frequency at the number of the e-commerce orders; Based on the probability of the combined processing of different e-commerce orders in the e-commerce platform, determine the average value of the probability of the combined processing of different e-commerce platforms and use it as the average value of the probability of the combined processing; Determine the monitoring frequency of the acquisition process of the e-commerce orders on the e-commerce platform through the preset monitoring frequency and the average value of the probability of the combined processing; 2. The e-commerce order management method according to claim 1, characterized in that The similar e-commerce orders are e-commerce orders with any one of the order information and the order account on the e-commerce platform being the same; 3. The e-commerce order management method according to claim 1, wherein Based on the number of the e-commerce platform and the proportion of the number of the similar e-commerce orders in the e-commerce orders, determine whether it is necessary to adopt the preset monitoring frequency for the acquisition process of the e-commerce orders on the e-commerce platform, specifically including: Determine a preset quantity proportion threshold corresponding to the quantity of the e-commerce platforms based on the quantity of the e-commerce platforms; Determine whether it is necessary to obtain and process the e-commerce orders of the e-commerce platforms at a preset monitoring frequency according to the preset quantity proportion threshold and the quantity proportion of similar e-commerce orders in the e-commerce orders.

4. The e-commerce order management method according to claim 1, wherein When the quantity proportion of the similar e-commerce orders in the e-commerce orders is greater than the preset quantity proportion threshold, it is determined that it is necessary to obtain and process the e-commerce orders of the e-commerce platforms at a preset monitoring frequency.

5. The e-commerce order management method according to claim 1, characterized in that The historical order data includes the historical order quantity.

6. The e-commerce order management method according to claim 1, characterized in that, The method for determining the correlation coefficient is as follows: Determine the products that need to be used simultaneously during the use of the product and the products with the same product usage object based on the type of the product, and use them as basic associated products; Use the historical orders of the product and the basic associated products in the same order and the same user as associated historical orders; Determine the correlation coefficient between the product and the basic associated products according to the quantity of the associated historical orders.

7. The e-commerce order management method according to claim 6, wherein When the other product does not belong to the basic associated products, it is determined that the correlation coefficient between the other product and the product is 0. When the other product belongs to the basic associated products, the correlation coefficient between the product and the basic associated products is determined by using the preset correlation coefficient corresponding to the quantity of the associated historical orders.

8. A computer system, comprising: A memory and a processor connected by communication, and a computer program stored on the memory and capable of running on the processor, wherein: when the processor runs the computer program, it executes an e-commerce order management method according to any one of claims 1-7.

9. A computer storage medium having a computer program stored thereon, characterized in that when the computer program is executed in a computer, Cause a computer to execute an e-commerce order management method according to any one of claims 1-7.

Images