Recommendation method and configuration device for logistics distribution, electronic equipment and storage medium

Abstract

The invention provides a logistics distribution recommendation method and device, electronic equipment and a computer readable storage medium, and relates to the technical field of electronic logistics. The logistics distribution recommendation method comprises the following steps: in response to an obtained product distribution order, detecting whether a sender of the product distribution order is configured with a plurality of special distribution rules; if it is detected that the plurality of special delivery rules are configured, scoring the plurality of special delivery rules based on input parameter elements of the product delivery order; selecting a target special distribution rule from the plurality of special distribution rules based on a scoring result; and recommending a logistics distribution scheme of the matched product distribution order based on the target special distribution rule. Through the technical scheme disclosed by the invention, the personalized distribution appeal of the user can be met, and the order placing experience of the logistics business of the user is improved.

Description

Background Art

[0002] In systems such as the Logistics Transaction Order Center or the Logistics Fulfillment Center (OFC), the order delivery plan is determined in the following ways:

[0003] If the logistics business is relatively simple, the merchant can specify it along with the order. However, in the application scenario where the merchant ships goods from the same warehouse based on 2B (for corporate users) and 2C (for ordinary users) businesses, the merchant cannot specify the delivery products based on the business, and has no perception of the order type in the warehouse.

[0004] If the logistics business is more complicated, it will be classified and determined based on parameters such as weight, volume or priority, so that the merchant will change from demanding a single delivery product to demanding multiple delivery products at the same time, resulting in the merchant having to select products for each order before issuing instructions.

[0005] Therefore, the user experience provided by the current logistics and distribution solutions to merchants needs to be improved.

[0006] It should be noted that the information disclosed in the above background technology section is only used to enhance the understanding of the background of the present disclosure, and therefore may include information that does not constitute prior art known to ordinary technicians in the field. Summary of the Invention

[0007] The purpose of the present disclosure is to provide a logistics distribution recommendation method, logistics distribution recommendation device, electronic device and storage medium, which can at least to some extent improve the problem in related technologies that merchants have poor experience with recommended logistics distribution plans.

[0008] Other features and advantages of the present disclosure will become apparent from the following detailed description, or may be learned in part by practice of the present disclosure.

[0009] According to one aspect of the present disclosure, a method for recommending logistics distribution is provided, comprising: in response to an acquired product distribution order, detecting whether the sender of the product distribution order has configured multiple special distribution rules; if it is detected that the multiple special distribution rules are configured, scoring the multiple special distribution rules based on the input parameter elements of the product distribution order to obtain a scoring result; selecting a target special distribution rule from the multiple special distribution rules based on the scoring result; and recommending a matching logistics distribution plan for the product distribution order based on the target special distribution rule.

[0010] In one embodiment, if it is detected that the special delivery rules are configured, the multiple special delivery rules are scored based on the input elements of the product delivery order, including: if it is detected that the multiple special delivery rules are configured, for each of the special delivery rules, multiple dimensions are configured based on the input elements of the product delivery order, and dimensions to be evaluated are selected from the multiple dimensions based on the configuration rule elements of the special delivery rules; for each of the dimensions to be evaluated, a score is performed based on the relationship between the configuration rule elements and the input elements in the corresponding special delivery rule; and the score is obtained based on the scores of the multiple dimensions to be evaluated.

[0011] In one embodiment, scoring each dimension to be evaluated based on the relationship between the configuration rule element and the input parameter element in the corresponding dedicated delivery rule includes:

[0012] For each dimension to be evaluated, detecting whether the corresponding configuration rule element is empty;

[0013] If the configuration rule element is empty and the value of the input parameter element is empty, it is determined that the configuration rule element and the input parameter element match, so as to score the dimension to be evaluated based on the matching condition; if the configuration rule element is empty, but the value of the input parameter element is not empty, it is determined that the matching condition is met, so as to score the dimension to be evaluated based on the matching condition.

[0014] In one embodiment, it also includes: if the configuration rule element is not empty, but the value of the input parameter element is empty, it is determined that the matching condition is not met, and a negative score is given to the dimension to be evaluated; if the configuration rule element is not empty and the value of the input parameter element is not empty, it is detected whether the value of the input parameter element is within the configuration range of the configuration rule element; if the value of the input parameter element is within the configuration range of the configuration rule element, it is determined that the matching condition is met, and the dimension to be evaluated is scored based on the matching condition and the configuration multiple; if the value of the input parameter element is not within the configuration range of the configuration rule element, it is determined that the matching condition is not met, and a negative score is given to the dimension to be evaluated.

[0015] In one embodiment, the selecting a target dedicated delivery rule from the multiple dedicated delivery rules based on the scoring result includes: determining the dedicated delivery rule with the highest score as the target dedicated delivery rule, wherein if the scoring result is lower than the scoring threshold, processing the product delivery order based on a preset fallback solution.

[0016] In one embodiment, the method further includes: if it is detected that the multiple dedicated delivery rules are not configured, recommending a matching logistics delivery plan for the product delivery order based on the general configuration rules.

[0017] In one embodiment, the logistics distribution plan for the product delivery order that is recommended based on the general configuration rules includes: extracting product type information from the product delivery order; determining the priority dimension that matches the product type information among the multiple dimensions based on the general configuration rules; and determining the logistics distribution plan corresponding to the priority dimension.

[0018] In one embodiment, in response to an acquired product delivery order, before detecting whether the sender of the product delivery order has configured multiple dedicated delivery rules, it also includes: acquiring multiple business scenario information; determining the priority dimension corresponding to each of the business scenario information; configuring the general delivery rule based on the splicing operation of the corresponding priority dimension; and establishing an association relationship between each of the general delivery rules and the corresponding logistics delivery plan.

[0019] In one embodiment, before detecting whether the sender of the product delivery order has configured multiple special delivery rules in response to the acquired product delivery order, it also includes: in response to the acquired special configuration information, configuring a corresponding threshold range for each dimension based on the special configuration information, and / or configuring a corresponding weight for each dimension; generating the special delivery rule based on the configuration result of the threshold range and / or the weight; and establishing an association relationship between each of the special delivery rules and the corresponding logistics delivery plan.

[0020] In one embodiment, the multiple dimensions include at least two of the product merchant dimension, sales platform dimension, business type dimension, document type dimension, order line dimension, product volume dimension, product weight dimension, re-throw ratio dimension, product type dimension and special needs dimension.

[0021] According to another aspect of the present disclosure, a logistics distribution recommendation device is provided, including: a detection module for detecting, in response to an acquired product delivery order, whether the sender of the product delivery order has configured multiple special delivery rules; a scoring module for scoring the multiple special delivery rules based on the input elements of the product delivery order to obtain a scoring result if it is detected that the multiple special delivery rules are configured; a selection module for selecting a target special delivery rule from the multiple special delivery rules based on the scoring result; and a recommendation module for recommending a logistics distribution plan that matches the product delivery order based on the target special delivery rule.

[0022] According to another aspect of the present disclosure, an electronic device is provided, comprising: a processor; and a memory for storing executable instructions of the processor; wherein the processor is configured to execute any one of the above-mentioned logistics distribution recommendation methods by executing the executable instructions.

[0023] According to another aspect of the present disclosure, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the computer program implements any of the above-mentioned methods for recommending logistics distribution.

[0024] The logistics distribution recommendation scheme provided by the embodiment of the present disclosure, when obtaining the user's product delivery order, first detects whether the user has configured multiple personalized special delivery rules, and when it is detected that multiple special delivery rules are configured, scores the multiple special delivery rules based on the input elements in the product delivery order, and performs adaptability evaluation based on the score, so as to select the target special delivery rule that is most suitable for the product delivery order from the multiple special delivery rules based on the scoring result. Furthermore, a matching logistics distribution scheme can be recommended to the user based on the target special delivery rule. On the one hand, since the distribution scheme is determined based on the user's own special delivery rules, it enables the merchant to specify the delivery products according to the business, and is conducive to the user's perception of the order type in the warehouse. On the other hand, for more complex logistics business, since the special configuration rules are pre-configured, when placing an order, by determining the matching target special configuration rules, it is also conducive to simplifying the user's order processing process, and automatically matching the merchant with the appropriate delivery products for the order, thereby meeting the user's personalized delivery demands and improving the user's logistics business ordering experience.

[0025] It is to be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] The accompanying drawings are incorporated into and constitute a part of the specification, illustrate embodiments consistent with the present disclosure, and together with the specification, are used to explain the principles of the present disclosure. Obviously, the drawings described below are only some embodiments of the present disclosure, and those skilled in the art can derive other drawings based on these drawings without inventive effort.

[0027] Figure 1 A schematic diagram showing a recommendation system structure for logistics distribution according to an embodiment of the present disclosure;

[0028] Figure 2 A schematic flow chart showing a recommended method for logistics distribution in an embodiment of the present disclosure;

[0029] Figure 3A schematic flow chart showing another recommended method for logistics distribution in an embodiment of the present disclosure;

[0030] Figure 4 A schematic flow chart showing another recommended method for logistics distribution in an embodiment of the present disclosure;

[0031] Figure 5 A schematic flow chart showing another recommended method for logistics distribution in an embodiment of the present disclosure;

[0032] Figure 6 A configuration interface diagram showing a recommended solution for logistics distribution in an embodiment of the present disclosure;

[0033] Figure 7 A configuration interface diagram showing another recommended solution for logistics distribution according to an embodiment of the present disclosure;

[0034] Figure 8 A schematic flow chart showing another recommended method for logistics distribution in an embodiment of the present disclosure;

[0035] Figure 9 A configuration interface diagram showing another recommended solution for logistics distribution according to an embodiment of the present disclosure is shown;

[0036] Figure 10 A schematic diagram showing a recommended device for logistics distribution according to an embodiment of the present disclosure;

[0037] Figure 11 A schematic diagram showing an electronic device in an embodiment of the present disclosure is shown. DETAILED DESCRIPTION

[0038] Example embodiments will now be described more fully with reference to the accompanying drawings. However, example embodiments can be embodied in many forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided so that this disclosure will be thorough and complete and will fully convey the concepts of the example embodiments to those skilled in the art. The described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments.

[0039] In addition, the accompanying drawings are merely schematic illustrations of the present disclosure and are not necessarily drawn to scale. Identical reference numerals in the figures denote identical or similar parts, and thus repetitive descriptions thereof will be omitted. Some of the block diagrams shown in the accompanying drawings are functional entities that do not necessarily correspond to physically or logically separate entities. These functional entities may be implemented in software, in one or more hardware modules or integrated circuits, or in different networks and / or processor devices and / or microcontroller devices.

[0040] The solution provided by the present application, when obtaining the user's product delivery order, first detects whether the user has configured multiple personalized special delivery rules, and when it is detected that multiple special delivery rules are configured, scores the multiple special delivery rules based on the input elements in the product delivery order, and performs adaptability evaluation based on the score, so as to select the target special delivery rule that is most suitable for the product delivery order from the multiple special delivery rules based on the scoring result. Furthermore, a matching logistics delivery plan can be recommended to the user based on the target special delivery rule. On the one hand, since the delivery plan is determined based on the user's own special delivery rules, it enables the merchant to specify the delivery products according to the business, and is conducive to the user's perception of the order type in the warehouse. On the other hand, for more complex logistics business, since the special configuration rules are pre-configured, when placing an order, by determining the matching target special configuration rules, it is also conducive to simplifying the user's order processing process, and automatically matching the merchant with the appropriate delivery products for the order, thereby meeting the user's personalized delivery demands and improving the user's logistics business ordering experience.

[0041] Figure 1 A structural diagram of a logistics distribution recommendation system according to an embodiment of the present disclosure is shown, which includes multiple terminals 120 and a server cluster 140 .

[0042] The terminal 120 may be a mobile terminal such as a mobile phone, a game console, a tablet computer, an e-book reader, smart glasses, an MP4 (Moving Picture Experts Group Audio Layer IV) player, a smart home device, an AR (Augmented Reality) device, a VR (Virtual Reality) device, or the terminal 120 may also be a personal computer (PC), such as a laptop computer and a desktop computer.

[0043] The terminal 120 may be installed with an application program for providing recommendations on logistics and delivery.

[0044] The terminal 120 is connected to the server cluster 140 via a communication network. Optionally, the communication network is a wired network or a wireless network.

[0045] Server cluster 140 is a single server, or a combination of multiple servers, a virtualization platform, or a cloud computing service center. Server cluster 140 provides backend services for a recommendation application that provides logistics and delivery services. Optionally, server cluster 140 performs primary computing tasks, while terminals 120 handle secondary computing tasks. Alternatively, server cluster 140 handles secondary computing tasks, while terminals 120 handle primary computing tasks. Alternatively, terminals 120 and server cluster 140 utilize a distributed computing architecture for collaborative computing.

[0046] In some optional embodiments, the server cluster 140 is used to store recommendation models for logistics distribution, etc.

[0047] Optionally, the application clients installed in different terminals 120 are the same, or the application clients installed on the two terminals 120 are clients of the same type of application on different control system platforms. Based on the different terminal platforms, the specific form of the application client may also be different. For example, the application client may be a mobile phone client, a PC client, or a World Wide Web (Web) client.

[0048] Those skilled in the art will appreciate that the number of the terminals 120 may be greater or less. For example, there may be only one terminal, or there may be dozens, hundreds, or even more terminals. The embodiments of the present application do not limit the number and device types of the terminals.

[0049] Optionally, the system may further include a management device ( Figure 1 (not shown), the management device is connected to the server cluster 140 via a communication network. Optionally, the communication network is a wired network or a wireless network.

[0050] Optionally, the above-mentioned wireless network or wired network uses standard communication technologies and / or protocols. The network is typically the Internet, but can also be any network, including but not limited to a local area network (LAN), a metropolitan area network (MAN), a wide area network (WAN), a mobile, wired or wireless network, a private network or any combination of a virtual private network). In some embodiments, technologies and / or formats including Hyper Text Mark-up Language (HTML), Extensible Markup Language (XML), etc. are used to represent data exchanged over the network. In addition, conventional encryption technologies such as Secure Socket Layer (SSL), Transport Layer Security (TLS), Virtual Private Network (VPN), Internet Protocol Security (IPsec), etc. can be used to encrypt all or some links. In other embodiments, customized and / or dedicated data communication technologies can also be used to replace or supplement the above-mentioned data communication technologies.

[0051] Below, the recommended method for logistics distribution, the mobile terminal, the writing device and the processing method in this example implementation will be described in more detail with reference to the accompanying drawings and embodiments.

[0052] like Figure 2 As shown, a recommended method for logistics distribution according to an embodiment of the present disclosure includes:

[0053] Step S202 : In response to the acquired product delivery order, detecting whether the sender of the product delivery order has configured multiple dedicated delivery rules.

[0054] Among them, the sender of the product delivery order refers to the product seller, and the dedicated delivery rules refer to the delivery rules configured by the provider of the logistics delivery solution based on the individual characteristics of the product seller.

[0055] In addition, it is detected whether the sender of the product delivery order has configured multiple special delivery rules. Specifically, it is detected that the personal identification library includes the sender's sending identification, and based on the sending identification, the corresponding multiple special delivery rules are extracted from the pre-configured rule library.

[0056] Step S204: If it is detected that multiple dedicated delivery rules are configured, the multiple dedicated delivery rules are scored based on the input parameter elements of the product delivery order to obtain a scoring result.

[0057] Among them, if it is detected that multiple special delivery rules are configured, that is, the corresponding multiple special delivery rules are extracted, then the multiple special delivery rules are scored based on the input elements of the product delivery order to obtain the scoring results, that is, the adaptability of the multiple special delivery rules and the input elements of the product delivery order is detected.

[0058] In addition, the input elements specifically include multiple specific values ​​of product merchants, sales platforms, business types, document types, order routes, product volume, product weight, re-throw ratio, product type and special requirements.

[0059] Step S206: Select a target dedicated delivery rule from the multiple dedicated delivery rules based on the scoring result.

[0060] Among them, a target dedicated delivery rule is selected from multiple dedicated delivery rules, that is, the dedicated delivery rule with the highest adaptability to the product delivery order is selected.

[0061] Step S208: recommending a logistics delivery plan for the matching product delivery order based on the target-specific delivery rules.

[0062] After determining the target-specific delivery rules, further, based on the pre-configured association relationships, a logistics delivery plan for the recommended product delivery order can be determined.

[0063] In this embodiment, when the user's product delivery order is obtained, it is first detected whether the user has configured multiple personalized special delivery rules. When it is detected that multiple special delivery rules are configured, the multiple special delivery rules are scored based on the input elements in the product delivery order, and adaptability evaluation is performed based on the score. Based on the scoring result, the target special delivery rule that is most suitable for the product delivery order is selected from the multiple special delivery rules. Furthermore, a matching logistics delivery plan can be recommended to the user based on the target special delivery rule. On the one hand, since the delivery plan is determined based on the user's own special delivery rules, the merchant can specify the delivery products according to the business, and it is beneficial for the user to perceive the order type in the warehouse. On the other hand, for more complex logistics business, since the special configuration rules are pre-configured, when placing an order, by determining the matching target special configuration rules, it is also beneficial to simplify the user's order processing process, and automatically match the merchant with the appropriate delivery products for the order, thereby meeting the user's personalized delivery demands and improving the user's logistics business ordering experience.

[0064] like Figure 3 As shown, in one embodiment, in step S204, if it is detected that a dedicated delivery rule is configured, multiple dedicated delivery rules are scored based on the input elements of the product delivery order, including:

[0065] In step S302, if it is detected that multiple dedicated delivery rules are configured, for each dedicated delivery rule, multiple dimensions are configured based on the input parameter elements of the product delivery order, and a dimension to be evaluated is selected from the multiple dimensions based on the configured rule elements of the dedicated delivery rule.

[0066] Among them, each input element is used as a dimension to be evaluated. For example, assuming that the input elements include the weight, volume, timeliness requirements, packaging requirements, etc. of the product, the above input elements are used as dimensions to be evaluated and scored.

[0067] Step S304 : For each dimension to be evaluated, scoring is performed based on the relationship between the configuration rule elements and the input parameter elements in the corresponding dedicated delivery rule.

[0068] The relationship between the configuration rule elements and the input parameter elements includes, but is not limited to, whether they are consistent, whether they are within a limited range, whether they are both assigned values ​​or not assigned values, etc.

[0069] Step S306: Determine a rating based on the scores of the multiple dimensions to be evaluated.

[0070] Among them, the specific implementation method of obtaining a score based on the scores of multiple dimensions to be evaluated is to add up the multiple scores to obtain the corresponding score.

[0071] In this embodiment, based on the relationship between the configuration rule elements and the input elements in the corresponding dedicated delivery rules, the dimensions to be evaluated corresponding to each input element are evaluated and scored, so that the target dedicated delivery rule is selected based on the scoring results to ensure the reliability of the selection of the target dedicated configuration rule.

[0072] like Figure 4 As shown, in one embodiment, step S304, for each dimension to be evaluated, a specific implementation method of scoring based on the relationship between the configuration rule element and the input parameter element in the corresponding dedicated delivery rule includes:

[0073] Step S402: for each dimension to be evaluated, detect whether the corresponding configuration rule element is empty.

[0074] Step S404: If the configuration rule element is empty and the value of the input parameter element is empty, determine that the configuration rule element and the input parameter element match, and score the dimension to be evaluated based on the matching condition.

[0075] If the value of the input parameter element is empty and the configuration rule element in the rule is also empty, it means that the dimension is matched successfully. The score for this dimension can be: the weight of the rule configuration element * 1.

[0076] For example, taking volumetric weight as an example, if the volumetric weight is filled in the input element and is not required in the dedicated delivery rule, then in the scoring calculation for this dedicated delivery rule, the score for this dimension is the weight of the rule configuration element * 1.

[0077] Step S406: If the configuration rule element is empty, but the value of the input parameter element is not empty, it is determined that the matching condition is met, and the dimension to be evaluated is scored based on the matching condition.

[0078] Among them, if the configuration rule element in the rule is empty, but the value of the input parameter element is not empty, it means that the condition is met, and the score of this dimension can be: the weight of the rule configuration element * 1.

[0079] In one embodiment, it further includes:

[0080] Step S408: If the configuration rule element is not empty, but the value of the input parameter element is empty, it is determined that the matching condition is not met, and a negative score is given to the evaluation dimension.

[0081] If the rule configuration element is not empty but the value of the input parameter element is empty, it means that the condition is not met and a negative score is calculated for this dimension, with a negative score of -9,999,999,999.

[0082] Step S410: If the configuration rule element is not empty and the value of the input parameter element is not empty, it is detected whether the value of the input parameter element is within the configuration range of the configuration rule element.

[0083] Step S412: If the value of the input parameter element is within the configuration range of the configuration rule element, it is determined that the matching condition is met, and the dimension to be evaluated is scored based on the matching condition and the configuration multiple.

[0084] If the rule configuration element is not empty, the value of the input parameter element is not empty, and the value of the input parameter element is equal to the value of the rule configuration element or is within the configuration range, then the condition is met and the score for the evaluation dimension is the weight of the rule configuration element * 2.

[0085] Step S414: If the value of the input parameter element is not within the configuration range of the configuration rule element, it is determined that the matching condition is not met, and a negative score is given to the dimension to be evaluated.

[0086] Among them, if the rule configuration element is not empty, the value of the input parameter element is not empty, and the input parameter value is not equal to the value of the rule configuration element or is not within the configuration range, it means that the condition is not met, and the dimension is scored negative, negative score = -9,999,999,999.

[0087] In this embodiment, by detecting different relationships between the values ​​of the configuration rule elements and the input parameter elements, and scoring based on the detection results, a score for a dedicated delivery rule can be finally obtained. This detection process is conducive to ensuring the validity of the scoring results.

[0088] In one embodiment, a target dedicated delivery rule is selected from a plurality of dedicated delivery rules based on a scoring result, including: determining the dedicated delivery rule with the highest score as the target dedicated delivery rule, wherein, if the scoring result is lower than a scoring threshold, processing the product delivery order based on a preset fallback solution.

[0089] Among them, the backup plan may include rejecting the order, sending it to the exception management platform for processing, or recommending the default logistics distribution plan.

[0090] In this embodiment, by selecting a highly scored dedicated delivery rule as the target dedicated delivery rule, when selecting a logistics delivery plan for an order based on the target dedicated delivery rule, a high degree of compatibility between the logistics delivery plan and the product delivery order can be ensured.

[0091] In one embodiment, the method further includes: if it is detected that multiple dedicated delivery rules are not configured, recommending a logistics delivery plan for a matching product delivery order based on the general configuration rules.

[0092] Among them, the general configuration rules are the general configuration solutions for delivery orders of this type of products in the logistics industry.

[0093] For example, for clothing, the weight and volume of each order can be increased, and the relevant thresholds can be adjusted. The corresponding general delivery rule is to give priority to weight and volume being within a stable range. For alcoholic beverages, the weight-to-throw ratio of alcoholic beverages is large, but the volume and weight are fixed. The corresponding general delivery rule is to give priority to value-added factors such as fragility. For 3C products, due to the high requirements on timeliness and loss, the corresponding general delivery rule is to give priority to timeliness. For luxury goods, the corresponding general delivery rule is to give priority to packaging, service and other factors.

[0094] In one embodiment, recommending a logistics distribution plan for a matching product delivery order based on a general configuration rule includes: extracting product type information from the product delivery order; determining a priority dimension that matches the product type information among multiple dimensions based on the general configuration rule; and determining a logistics distribution plan corresponding to the priority dimension.

[0095] Among them, product type information includes but is not limited to the above-mentioned clothing, wine, 3C and luxury goods, as well as fresh food, food and furniture.

[0096] In this embodiment, different industries and different products have different type information. By obtaining the type information, the corresponding priority dimensions that need to be given priority in the distribution process can be determined. Since different priority dimensions correspond to different general configuration rules, by determining the corresponding general configuration rules, the required logistics distribution plan can be finally selected.

[0097] like Figure 5 As shown, in one embodiment, before detecting, in response to the acquired product delivery order, whether the sender of the product delivery order has configured multiple dedicated delivery rules, the method further includes:

[0098] Step S502: Acquire multiple business scenario information.

[0099] Step S504: determine the priority dimension corresponding to each business scenario information.

[0100] Step S506 : configuring a general distribution rule based on the splicing operation of the corresponding priority dimensions.

[0101] Step S508: establishing an association relationship between each general distribution rule and the corresponding logistics distribution plan.

[0102] In this embodiment, multiple dimensions of merchants, sales platforms, business types, document types, routes, volumes, weights, weight-to-throw ratios, product categories, special needs, etc., can be used to obtain information on multiple business scenarios to determine the dimensions that need to be prioritized in each scenario, namely, priority dimensions. These priority dimensions are defined and spliced ​​as bricks and tiles for building a house, so as to create industry rules based on business scenarios, which is also the industry's safety net logic.

[0103] like Figure 6 As shown, in the recommended solution for logistics distribution disclosed in the present invention, in order to configure general configuration rules and special general configuration rules, it is necessary to first enter the rule elements, wherein the entry of rule elements includes the input of element name, element description, element description and the selection of element type, etc. The element types include single-choice type, multiple-choice type, text entry type, threshold type and reference type.

[0104] like Figure 7 As shown, in the configuration interface of the general configuration rule, it is necessary to configure the function type, application scope, rule type, and whether it is a general rule, etc. of the rule, and further describe the rule.

[0105] In addition, an association relationship is established between each general distribution rule and the corresponding logistics distribution plan, and configuration is performed based on the correspondence between the input and output in the allocation elements. The input includes document type, business type, commodity code, volume and route range, etc., and the output includes product name and vehicle model, etc.

[0106] like Figure 8 As shown, in one embodiment, before detecting, in response to the acquired product delivery order, whether the sender of the product delivery order has configured multiple dedicated delivery rules, the method further includes:

[0107] Step S802: In response to the acquired dedicated configuration information, a corresponding threshold range is configured for each dimension based on the dedicated configuration information, and / or a corresponding weight is configured for each dimension.

[0108] Step S804: Generate a dedicated delivery rule based on the configuration results of the threshold range and / or weight.

[0109] For example, in the general delivery rule, the configured weight range is 10KG to 15KG, and in the dedicated delivery rule, the weight range is adjusted to 15KG to 18KG.

[0110] Step S806: Establish an association relationship between each dedicated delivery rule and the corresponding logistics delivery plan.

[0111] like Figure 9 As shown, in the configuration interface of the dedicated configuration rules, configuration is performed by selecting and editing rule elements. Furthermore, in the recommendation interface of the logistics distribution product, matching logistics distribution products can be output by importing document information.

[0112] The logistics distribution recommendation scheme based on the present disclosure can tailor-make distribution product recommendation strategies for merchants. Through the above-mentioned configuration interface, it can achieve configurability and intelligence, and use input, matching algorithms, and output logic to build a framework. By abstracting all rule input conditions and output results into elements, all rules are compatible through a collection of elements to automatically match appropriate distribution products for orders, thereby improving merchants' ordering experience, saving merchants' distribution costs, realizing refined management and personalized expansion, meeting the wishes of specific merchants, and enhancing the guiding significance of operational resources.

[0113] In this embodiment, in order to configure special delivery rules, the set general delivery rules can be adjusted, including but not limited to threshold and priority adjustments based on the merchant dimension, to meet the personalized logic of large customers, derive merchant personalized rules based on the general delivery rules, and automatically match merchants with suitable delivery products for orders, thereby meeting users' personalized delivery demands and improving users' logistics business ordering experience.

[0114] In one embodiment, the multiple dimensions include at least two of the product merchant dimension, sales platform dimension, business type dimension, document type dimension, order line dimension, product volume dimension, product weight dimension, re-throw ratio dimension, product type dimension and special needs dimension.

[0115] For example, a merchant configures multiple dedicated delivery rules. The configuration rule elements of the first dedicated delivery rule include merchant, sales platform, business type and order line, and each rule element is assigned a corresponding weight.

[0116] The configuration rule elements of the second dedicated delivery rule include product volume and product weight.

[0117] The configuration rule elements of the third dedicated delivery rule include product type, special requirements and document type.

[0118] The input elements of the obtained product delivery order include specific limitations of product merchants, sales platforms, business types and document types. For the first dedicated delivery rule, the dimensions to be evaluated include merchants, sales platforms, business types, document types and order routes. Based on these dimensions to be evaluated, the score of the first dedicated delivery rule can be obtained.

[0119] The second dedicated delivery rule and the third dedicated delivery rule use the same scoring scheme to determine the dedicated delivery rule with the highest score as the target dedicated delivery rule, and further determine the matching logistics delivery plan.

[0120] It should be noted that the above figures are merely illustrative of the processes included in the method according to exemplary embodiments of the present invention and are not intended to be limiting. It is readily understood that the processes illustrated in the above figures do not indicate or limit the temporal order of these processes. Furthermore, it is readily understood that these processes may be executed synchronously or asynchronously, for example, in multiple modules.

[0121] Those skilled in the art will appreciate that various aspects of the present invention may be implemented as systems, methods, or program products. Therefore, various aspects of the present invention may be implemented in the following forms: a complete hardware implementation, a complete software implementation (including firmware, microcode, etc.), or a combination of hardware and software implementations, which may be collectively referred to herein as "circuits," "modules," or "systems."

[0122] Refer to the following Figure 10 The recommended device 1000 for logistics distribution according to this embodiment of the present invention will be described. Figure 10 The recommended device 1000 for logistics distribution shown is merely an example and should not limit the functions and scope of use of the embodiments of the present invention.

[0123] The logistics and delivery recommendation device 1000 is implemented as a hardware module. The components of the logistics and delivery recommendation device 1000 may include, but are not limited to: a detection module 1002 for detecting, in response to a received product delivery order, whether the sender of the product delivery order has configured multiple dedicated delivery rules; a scoring module 1004 for scoring the multiple dedicated delivery rules based on the input parameters of the product delivery order, if multiple dedicated delivery rules are detected; a selection module 1006 for selecting a target dedicated delivery rule from the multiple dedicated delivery rules based on the scoring result; and a recommendation module 1008 for recommending a logistics and delivery solution for a matching product delivery order based on the target dedicated delivery rule.

[0124] Refer to the following Figure 11 An electronic device 1100 according to this embodiment of the present invention will be described. Figure 11 The electronic device 1100 shown is merely an example and should not limit the functions and scope of use of the embodiments of the present invention.

[0125] like Figure 11 As shown, electronic device 1100 is implemented as a general-purpose computing device. Components of electronic device 1100 may include, but are not limited to, the aforementioned at least one processing unit 1110, the aforementioned at least one storage unit 1120, and a bus 1130 connecting various system components (including storage unit 1120 and processing unit 1110).

[0126] The storage unit stores program codes, which can be executed by the processing unit 1110, so that the processing unit 1110 performs the steps of various exemplary embodiments of the present invention described in the above “Exemplary Method” section of this specification. For example, the processing unit 1110 can perform the following steps: Figure 2 Steps S202 to S208 shown in , and other steps defined in the recommended method for logistics distribution of the present disclosure.

[0127] The storage unit 1120 may include a readable medium in the form of a volatile storage unit, such as a random access memory unit (RAM) 11201 and / or a cache memory unit 11202 , and may further include a read-only memory unit (ROM) 11203 .

[0128] The storage unit 1120 may also include a program / utility 11204 having a set (at least one) of program modules 11205, such program modules 11205 including but not limited to: an operating system, one or more application programs, other program modules, and program data, each of which or some combination may include an implementation of a network environment.

[0129] The bus 1130 may represent one or more of several types of bus structures, including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, a processing unit, or a local bus using any of a variety of bus architectures.

[0130] The electronic device 1100 can also communicate with one or more external devices 1160 (e.g., a keyboard, a pointing device, a Bluetooth device, etc.), one or more devices that enable a user to interact with the electronic device, and / or any device that enables the electronic device 1100 to communicate with one or more other computing devices (e.g., a router, a modem, etc.). Such communication can occur via an input / output (I / O) interface 1150. Furthermore, the electronic device 1100 can also communicate with one or more networks (e.g., a local area network (LAN), a wide area network (WAN), and / or a public network such as the Internet) via a network adapter 1150. As shown, the network adapter 1150 communicates with other modules of the electronic device 1100 via a bus 1130. It should be understood that, although not shown in the figure, other hardware and / or software modules can be used in conjunction with the electronic device, including but not limited to microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.

[0131] Through the description of the above embodiments, it is easy for those skilled in the art to understand that the example embodiments described herein can be implemented by software or by combining software with necessary hardware. Therefore, the technical solution according to the embodiments of the present disclosure can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, a USB flash drive, a mobile hard disk, etc.) or on a network, and includes several instructions to enable a computing device (which can be a personal computer, a server, a terminal device, or a network device, etc.) to execute the method according to the embodiments of the present disclosure.

[0132] In exemplary embodiments of the present disclosure, a computer-readable storage medium is also provided, on which is stored a program product capable of implementing the methods described above. In some possible implementations, various aspects of the present invention may also be implemented in the form of a program product comprising program code that, when executed on a terminal device, causes the terminal device to execute the steps according to various exemplary embodiments of the present invention described in the "Exemplary Methods" section above.

[0133] According to an embodiment of the present invention, a program product for implementing the above-mentioned method can be a portable compact disc read-only memory (CD-ROM) and include program code, and can be run on a terminal device, such as a personal computer. However, the program product of the present invention is not limited thereto. In this document, a readable storage medium can be any tangible medium containing or storing a program, and the program can be used by or in conjunction with an instruction execution system, apparatus, or device.

[0134] A computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, which carries readable program code. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. A readable signal medium may also be any readable medium other than a readable storage medium that can transmit, propagate, or transfer a program for use by or in conjunction with an instruction execution system, apparatus, or device.

[0135] The program code embodied on the readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.

[0136] The program code for performing the operations of the present invention may be written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Java, C++, and the like, as well as conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user computing device, partially on the user device, as a stand-alone software package, partially on the user computing device and partially on a remote computing device, or entirely on a remote computing device or server. In cases involving a remote computing device, the remote computing device may be connected to the user computing device via any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computing device (e.g., via the Internet using an Internet service provider).

[0137] It should be noted that although several modules or units of the device for action execution are mentioned in the detailed description above, this division is not mandatory. In fact, according to the embodiments of the present disclosure, the features and functions of two or more modules or units described above can be concretized in one module or unit. Conversely, the features and functions of one module or unit described above can be further divided into multiple modules or units to be concretized.

[0138] Furthermore, although the steps of the method of the present disclosure are described in a particular order in the accompanying drawings, this does not require or imply that the steps must be performed in this particular order, or that all steps shown must be performed to achieve the desired results. Additionally or alternatively, some steps may be omitted, multiple steps may be combined into one step, and / or one step may be decomposed into multiple steps.

[0139] Through the description of the above embodiments, it is easy for those skilled in the art to understand that the example embodiments described herein can be implemented by software or by combining software with necessary hardware. Therefore, the technical solution according to the embodiments of the present disclosure can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, a USB flash drive, a mobile hard disk, etc.) or on a network, and includes several instructions to enable a computing device (which can be a personal computer, a server, a mobile terminal, or a network device, etc.) to execute the method according to the embodiments of the present disclosure.

[0140] Those skilled in the art will readily appreciate other embodiments of the present disclosure after considering the specification and practicing the invention disclosed herein. This application is intended to cover any variations, uses, or adaptations of the present disclosure that follow the general principles of the present disclosure and include common knowledge or customary techniques in the art not disclosed herein. The description and examples are to be considered as exemplary only, with the true scope and spirit of the present disclosure being indicated by the appended claims.

Claims

1. A method for recommending logistics distribution, characterized in that: include: In response to the acquired product delivery order, detecting whether a sender of the product delivery order has configured a plurality of dedicated delivery rules; If it is detected that the multiple dedicated delivery rules are configured, scoring the multiple dedicated delivery rules based on the input parameter elements of the product delivery order to obtain a scoring result; Selecting a target dedicated delivery rule from the plurality of dedicated delivery rules based on the scoring result; A logistics delivery plan for the matching product delivery order is recommended based on the target-specific delivery rules.

2. The method for recommending logistics distribution according to claim 1, characterized in that: If it is detected that the dedicated delivery rule is configured, scoring the multiple dedicated delivery rules based on the input parameter elements of the product delivery order includes: If it is detected that the plurality of dedicated delivery rules are configured, for each of the dedicated delivery rules, a plurality of dimensions are configured based on the input parameter elements of the product delivery order, and a dimension to be evaluated is selected from the plurality of dimensions based on the configured rule elements of the dedicated delivery rule; For each dimension to be evaluated, scoring is performed based on the relationship between the configuration rule element and the input parameter element in the corresponding dedicated delivery rule; The rating is obtained based on the scores of the multiple dimensions to be evaluated.

3. The method for recommending logistics distribution according to claim 2, characterized in that: For each dimension to be evaluated, scoring is performed based on the relationship between the configuration rule element and the input parameter element in the corresponding dedicated delivery rule, including: For each dimension to be evaluated, detecting whether the corresponding configuration rule element is empty; If the configuration rule element is empty and the value of the input parameter element is empty, determine that the configuration rule element matches the input parameter element, so as to score the dimension to be evaluated based on the matching condition; If the configuration rule element is empty, but the value of the input parameter element is not empty, it is determined that the matching condition is met, so as to score the dimension to be evaluated based on the matching condition.

4. The method for recommending logistics distribution according to claim 3, characterized in that: Also includes: If the configuration rule element is not empty, but the value of the input parameter element is empty, it is determined that the matching condition is not met, and a negative score is given to the dimension to be evaluated; If the configuration rule element is not empty and the value of the input parameter element is not empty, detect whether the value of the input parameter element is within the configuration range of the configuration rule element; If the value of the input parameter element is within the configuration range of the configuration rule element, it is determined that the matching condition is met, and the dimension to be evaluated is scored based on the matching condition and the configuration multiple; If the value of the input parameter element is not within the configuration range of the configuration rule element, it is determined that the matching condition is not met, and a negative score is given to the dimension to be evaluated.

5. The method for recommending logistics distribution according to claim 2, characterized in that: The selecting a target dedicated delivery rule from the plurality of dedicated delivery rules based on the scoring result comprises: determining the dedicated delivery rule with the highest score as the target dedicated delivery rule, Among them, if the scoring result is lower than the scoring threshold, the product delivery order is processed based on the preset fallback plan.

6. The method for recommending logistics distribution according to claim 2, characterized in that: Also includes: If it is detected that the multiple dedicated delivery rules are not configured, a logistics delivery solution for the matching product delivery order is recommended based on the general configuration rules.

7. The method for recommending logistics distribution according to claim 6, characterized in that: The logistics distribution plan for the product distribution order that is recommended to match the general configuration rule includes: extracting product type information from the product delivery order; Determining a priority dimension among the multiple dimensions that matches the product type information based on the general configuration rule; Determine the logistics distribution plan corresponding to the priority dimension.

8. The method for recommending logistics distribution according to claim 2, characterized in that: Before detecting, in response to the acquired product delivery order, whether the sender of the product delivery order has configured a plurality of dedicated delivery rules, the method further includes: Obtain information on multiple business scenarios; Determine the priority dimension corresponding to each of the business scenario information; configuring the general delivery rule based on the splicing operation of the corresponding priority dimensions; and An association relationship is established between each of the general distribution rules and the corresponding logistics distribution plan.

9. The method for recommending logistics distribution according to claim 8, characterized in that: Before detecting, in response to the acquired product delivery order, whether the sender of the product delivery order has configured a plurality of dedicated delivery rules, the method further includes: In response to the acquired dedicated configuration information, configuring a corresponding threshold range for each dimension based on the dedicated configuration information, and / or configuring a corresponding weight for each dimension; generating the dedicated delivery rule based on the configuration result of the threshold range and / or the weight; and An association relationship is established between each of the dedicated delivery rules and the corresponding logistics delivery plan.

10. The method for recommending logistics distribution according to any one of claims 2 to 9, characterized in that: The multiple dimensions include at least two of a product merchant dimension, a sales platform dimension, a business type dimension, a document type dimension, an order line dimension, a commodity volume dimension, a commodity weight dimension, a rethrow ratio dimension, a commodity type dimension, and a special demand dimension.

11. A method for recommending logistics distribution, characterized in that: Applied to the client, including: A detection module, configured to detect, in response to the acquired product delivery order, whether the sender of the product delivery order has configured a plurality of dedicated delivery rules; A scoring module, configured to score the multiple dedicated delivery rules based on the input parameter elements of the product delivery order to obtain a scoring result if it is detected that the multiple dedicated delivery rules are configured; A selection module, configured to select a target dedicated delivery rule from the plurality of dedicated delivery rules based on the scoring result; A recommendation module is used to recommend a logistics delivery solution for the matching product delivery order based on the target-specific delivery rule.

12. An electronic device, characterized in that: include: processor; as well as A memory, configured to store executable instructions of the processor; Wherein, the processor is configured to execute the logistics distribution recommendation method described in any one of claims 1 to 10 by executing the executable instructions.

13. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the method for recommending logistics distribution according to any one of claims 1 to 10 is implemented.

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