CN119539640A - Recommended method, configuration device, electronic device and storage medium for logistics distribution - Google Patents
Recommended method, configuration device, electronic device and storage medium for logistics distribution Download PDFInfo
- Publication number
- CN119539640A CN119539640A CN202311107969.4A CN202311107969A CN119539640A CN 119539640 A CN119539640 A CN 119539640A CN 202311107969 A CN202311107969 A CN 202311107969A CN 119539640 A CN119539640 A CN 119539640A
- Authority
- CN
- China
- Prior art keywords
- distribution
- rule
- dimension
- configuration
- special
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
Classifications
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/08—Logistics, e.g. warehousing, loading or distribution; Inventory or stock management
- G06Q10/083—Shipping
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0637—Strategic management or analysis, e.g. setting a goal or target of an organisation; Planning actions based on goals; Analysis or evaluation of effectiveness of goals
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
- Y02P90/30—Computing systems specially adapted for manufacturing
Landscapes
- Business, Economics & Management (AREA)
- Human Resources & Organizations (AREA)
- Engineering & Computer Science (AREA)
- Economics (AREA)
- Entrepreneurship & Innovation (AREA)
- Strategic Management (AREA)
- Development Economics (AREA)
- Educational Administration (AREA)
- Marketing (AREA)
- Operations Research (AREA)
- Quality & Reliability (AREA)
- Tourism & Hospitality (AREA)
- Physics & Mathematics (AREA)
- General Business, Economics & Management (AREA)
- General Physics & Mathematics (AREA)
- Theoretical Computer Science (AREA)
- Game Theory and Decision Science (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The disclosure provides a recommending method and device for logistics distribution, electronic equipment and a computer readable storage medium, and relates to the technical field of electronic logistics. The logistics distribution recommendation method includes the steps of responding to an obtained product distribution order, detecting whether a sender of the product distribution order configures a plurality of special distribution rules, scoring the special distribution rules based on parameter entering elements of the product distribution order if the sender of the product distribution order is detected to configure the special distribution rules, selecting a target special distribution rule from the special distribution rules based on scoring results, and recommending a matched logistics distribution scheme of the product distribution order based on the target special distribution rule. Through the technical scheme of the disclosure, personalized delivery requirements of the user can be met, and ordering experience of logistics business of the user is improved.
Description
Technical Field
The disclosure relates to the technical field of electronic logistics, and in particular relates to a logistics distribution recommending method, a logistics distribution recommending device, electronic equipment and a computer readable storage medium.
Background
In a system such as a logistics transaction order center or a logistics performance OFC (Order Fulfillment Center, order performance center), the distribution scheme of the order is determined by adopting the following modes:
If the logistics service is simpler, the business can be appointed along with the order, but in the application scene that the business delivers goods in the same warehouse according to the 2B (face-to-face enterprise user) service and the 2C (face-to-face common user) service, the business cannot appoint the delivery products according to the service, and the type of the order in the warehouse is not perceived.
If the logistics business is complex, the sorting determination is carried out according to parameters such as weight, volume or priority, so that the merchant changes the requirement of single delivery product into the requirement of multiple delivery products at the same time, and the merchant needs to select the products for each order and then issue instructions.
Thus, the current logistics distribution scheme is subject to improvement in the use experience for merchants.
It should be noted that the information disclosed in the above background section is only for enhancing understanding of the background of the present disclosure and thus may include information that does not constitute prior art known to those of ordinary skill in the art.
Disclosure of Invention
The disclosure aims to provide a logistics distribution recommending method, a logistics distribution recommending device, electronic equipment and a storage medium, which can at least improve the problem that a merchant experiences poor recommended logistics distribution schemes in the related art to a certain extent.
Other features and advantages of the present disclosure will be apparent from the following detailed description, or may be learned in part by the practice of the disclosure.
According to one aspect of the disclosure, a recommendation method for logistics distribution is provided, which comprises the steps of responding to an obtained product distribution order, detecting whether a sender of the product distribution order configures a plurality of special distribution rules, scoring the special distribution rules based on entry elements of the product distribution order to obtain a scoring result if the sender detects that the special distribution rules are configured, selecting a target special distribution rule from the special distribution rules based on the scoring result, and recommending a matched logistics distribution scheme of the product distribution order based on the target special distribution rule.
In one embodiment, the scoring the plurality of special delivery rules based on the entry elements of the product delivery order if the configuration of the special delivery rules is detected, wherein the scoring comprises configuring a plurality of dimensions based on the entry elements of the product delivery order for each special delivery rule, selecting a dimension to be evaluated from the plurality of dimensions based on the configuration rule elements of the special delivery rules, scoring based on the relationship between the configuration rule elements and the entry elements in the corresponding special delivery rules for each dimension to be evaluated, and obtaining the score based on the scores of the plurality of dimensions to be evaluated.
In one embodiment, the scoring, for each dimension to be evaluated, based on a relationship between a configuration rule element and a parameter entry element in the corresponding dedicated distribution rule, includes:
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 parameter entering element is empty, determining that the configuration rule element and the parameter entering element are matched, and scoring the dimension to be evaluated based on a matching condition; if the configuration rule element is empty, but the value of the parameter entry element is not empty, determining that a matching condition is met, and scoring the dimension to be evaluated based on the matching condition.
In one embodiment, the method further comprises the steps of determining that a matching condition is not met if the configuration rule element is not empty, but the value of the parameter entering element is empty, counting negative points of the dimension to be evaluated, detecting whether the value of the parameter entering element is in the configuration range of the configuration rule element or not if the configuration rule element is not empty, determining that the matching condition is met if the value of the parameter entering element is in the configuration range of the configuration rule element, counting the dimension to be evaluated based on the matching condition and the configuration multiple, and counting negative points of the dimension to be evaluated if the value of the parameter entering element is not in the configuration range of the configuration rule element.
In one embodiment, the selecting a target dedicated delivery rule from the plurality of 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 the product delivery order is processed based on a preset spam scheme if the scoring result is below a scoring threshold.
In one embodiment, the method further comprises recommending a logistics distribution scheme of the matched product distribution order based on a general configuration rule if the plurality of special distribution rules are detected to be not configured.
In one embodiment, the logistics distribution scheme for recommending the matched product distribution order based on the general configuration rule comprises the steps of extracting product type information from the product distribution order, determining a priority dimension matched with the product type information in the plurality of dimensions based on the general configuration rule, and determining the logistics distribution scheme corresponding to the priority dimension.
In one embodiment, before responding to the obtained product delivery order, detecting whether a sender of the product delivery order configures a plurality of special delivery rules, the method further comprises the steps of obtaining a plurality of business scenario information, determining a priority dimension corresponding to each business scenario information, configuring the general delivery rules based on a splicing operation of the corresponding priority dimension, and establishing an association relation between each general delivery rule and the corresponding logistics delivery scheme.
In one embodiment, before responding to the obtained product delivery order, detecting whether a sender of the product delivery order configures a plurality of special delivery rules, the method further comprises responding to the obtained special configuration information, configuring a corresponding threshold range for each dimension and/or configuring a corresponding weight for each dimension based on the special configuration information, generating the special delivery rules based on the threshold range and/or the configuration result of the weights, and establishing an association relation between each special delivery rule and the corresponding logistics delivery scheme.
In one embodiment, the plurality of dimensions includes 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 repeat ratio dimension, a commodity type dimension, and a special demand dimension.
According to another aspect of the disclosure, a recommendation device for logistics distribution is provided, which comprises a detection module, a scoring module and a selection module, wherein the detection module is used for responding to an acquired product distribution order and detecting whether a sender of the product distribution order configures a plurality of special distribution rules, the scoring module is used for scoring the plurality of special distribution rules based on a parameter entering element of the product distribution order to obtain a scoring result if the sender detects that the plurality of special distribution rules are configured, the selection module is used for selecting a target special distribution rule from the plurality of special distribution rules based on the scoring result, and the recommendation module is used for recommending a logistics distribution scheme of the matched product distribution order based on the target special distribution rule.
According to yet another aspect of the present disclosure, there is provided an electronic device comprising a processor and a memory for storing executable instructions of the processor, wherein the processor is configured to perform the recommended method of logistics distribution of any of the above via execution of the executable instructions.
According to yet another aspect of the present disclosure, there is provided a computer readable storage medium having stored thereon a computer program which when executed by a processor implements the recommended method of logistics distribution of any of the above.
According to the logistics distribution recommendation scheme provided by the embodiment of the disclosure, when a product distribution order of a user is obtained, whether the user configures a plurality of personalized special distribution rules is detected, so that when the user detects that the plurality of special distribution rules are configured, the plurality of special distribution rules are scored based on the parameter entering elements in the product distribution order, so that suitability evaluation is performed based on the scoring, and accordingly, a target special distribution rule which is most suitable for the product distribution order is selected from the plurality of special distribution rules based on the scoring result.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the disclosure and together with the description, serve to explain the principles of the disclosure. It will be apparent to those of ordinary skill in the art that the drawings in the following description are merely examples of the disclosure and that other drawings may be derived from them without undue effort.
FIG. 1 is a schematic diagram of a recommendation system architecture for logistics distribution in accordance with an embodiment of the present disclosure;
FIG. 2 illustrates a schematic flow diagram of a method of recommending logistics distribution in an embodiment of the present disclosure;
FIG. 3 illustrates a schematic flow diagram of another method of recommending logistics distribution in an embodiment of the present disclosure;
FIG. 4 illustrates a schematic flow diagram of a recommended method of logistics distribution in an embodiment of the present disclosure;
FIG. 5 illustrates a schematic flow diagram of yet another method of recommending logistics distribution in an embodiment of the present disclosure;
FIG. 6 is a diagram of a configuration interface of a recommendation for logistics distribution in an embodiment of the present disclosure;
FIG. 7 illustrates a configuration interface diagram of another logistics distribution recommendation in an embodiment of the present disclosure;
FIG. 8 illustrates a schematic flow diagram of yet another method of recommending logistics distribution in an embodiment of the present disclosure;
FIG. 9 illustrates a configuration interface diagram of yet another logistics distribution recommendation in an embodiment of the present disclosure;
FIG. 10 is a schematic diagram of a recommendation device for logistics distribution in accordance with an embodiment of the present disclosure;
fig. 11 shows a schematic diagram of an electronic device in an embodiment of the disclosure.
Detailed Description
Example embodiments will now be described more fully with reference to the accompanying drawings. However, the exemplary embodiments may be embodied in many forms and should not be construed as limited to the examples set forth herein, but rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the concept of the exemplary 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.
Furthermore, the drawings are merely schematic illustrations of the present disclosure and are not necessarily drawn to scale. The same reference numerals in the drawings denote the same or similar parts, and thus a repetitive description thereof will be omitted. Some of the block diagrams shown in the figures are functional entities and do not necessarily correspond to physically or logically separate entities. These functional entities may be implemented in software or in one or more hardware modules or integrated circuits or in different networks and/or processor devices and/or microcontroller devices.
According to the scheme provided by the application, when the product delivery order of the user is obtained, whether the user configures a plurality of personalized special delivery rules is detected, so that when the user configures the plurality of special delivery rules, the plurality of special delivery rules are scored based on the parameter entering elements in the product delivery order, so that suitability evaluation is carried out based on the score, a target special delivery rule which is most suitable for the product delivery order is selected from the plurality of special delivery rules based on the scoring result, and further, a matched logistics delivery scheme can be recommended for the user based on the target special delivery rules.
Fig. 1 shows a schematic structural diagram of a recommendation system for logistics distribution in an embodiment of the present disclosure, including a plurality of terminals 120 and a server cluster 140.
The terminal 120 may be a mobile terminal such as a mobile phone, a game console, a tablet computer, an electronic book reader, a smart glasses, an MP4 (Moving Picture Experts Group Audio Layer IV, dynamic image expert compression standard audio plane 4) player, a smart home device, an AR (Augmented Reality) device, a VR (Virtual Reality) device, or the terminal 120 may be a personal computer (Personal Computer, PC) such as a laptop portable computer and a desktop computer, etc.
Wherein the terminal 120 may have installed therein a recommended application for providing logistics distribution.
The terminal 120 is connected to the server cluster 140 through a communication network. Optionally, the communication network is a wired network or a wireless network.
The server cluster 140 is a server, or is composed of several servers, or is a virtualized platform, or is a cloud computing service center. The server cluster 140 is used to provide background services for recommended applications that provide logistics distribution. Optionally, the server cluster 140 performs primary computing, the terminal 120 performs secondary computing, or the server cluster 140 performs secondary computing, the terminal 120 performs primary computing, or a distributed computing architecture is used between the terminal 120 and the server cluster 140.
In some alternative embodiments, server cluster 140 is used to store a recommendation model for logistics distribution, and the like.
Alternatively, the clients of the applications installed in different terminals 120 are the same, or the clients of the applications installed on both terminals 120 are clients of the same type of application of different control system platforms. The specific form of the client of the application program may also be different based on the difference of the terminal platforms, for example, the application program client may be a mobile phone client, a PC client, or a World Wide Web (Web) client.
Those skilled in the art will appreciate that the number of terminals 120 may be greater or lesser. Such as the above-mentioned terminals may be only one, or the above-mentioned terminals may be several tens or hundreds, or more. The embodiment of the application does not limit the number of terminals and the equipment type.
Optionally, the system may further comprise a management device (not shown in fig. 1), which is connected to the server cluster 140 via a communication network. Optionally, the communication network is a wired network or a wireless network.
Alternatively, the wireless network or wired network described above uses standard communication techniques and/or protocols. The network is typically the Internet, but may be any network including, but not limited to, a local area network (Local Area Network, LAN), metropolitan area network (Metropolitan Area Network, MAN), wide area network (Wide Area Network, WAN), mobile, wired or wireless network, private network, or any combination of virtual private networks. In some embodiments, data exchanged over the network is represented using techniques and/or formats including HyperText Mark-up Language (HTML), extensible markup Language (Extensible MarkupLanguage, XML), and the like. All or some of the links may also be encrypted using conventional encryption techniques such as secure sockets layer (Secure Socket Layer, SSL), transport layer security (Transport Layer Security, TLS), virtual private network (Virtual Private Network, VPN), internet protocol security (Internet ProtocolSecurity, IPsec), etc. In other embodiments, custom and/or dedicated data communication techniques may also be used in place of or in addition to the data communication techniques described above.
Next, a recommendation method, a mobile terminal, a writing device, and a processing method for logistics distribution in the present exemplary embodiment will be described in more detail with reference to the accompanying drawings and examples.
As shown in fig. 2, a method for recommending logistics distribution according to one embodiment of the present disclosure includes:
In step S202, in response to the acquired product delivery order, it is detected whether the sender of the product delivery order has configured a plurality of dedicated delivery rules.
The sender of the product delivery order refers to a commodity seller, and the special delivery rule refers to a delivery rule configured by a provider of the logistics delivery scheme based on the individual characteristics of the commodity seller.
In addition, whether a sender of the product delivery order configures a plurality of special delivery rules is detected, specifically, a sending identifier of the sender is detected to be included in the personalized identifier library, and a plurality of corresponding special delivery rules are extracted from a pre-configured rule library based on the sending identifier.
Step S204, if it is detected that a plurality of special delivery rules are configured, scoring the plurality of special delivery rules based on the parameter entry elements of the product delivery order, and obtaining a scoring result.
If it is detected that a plurality of special delivery rules are configured, that is, a plurality of corresponding special delivery rules are extracted, the plurality of special delivery rules are scored based on the parameter entering elements of the product delivery order, and a scoring result is obtained, that is, the adaptation degree of the plurality of special delivery rules and the parameter entering elements of the product delivery order is detected.
In addition, the entry elements specifically include a plurality of specific values of product merchants, sales platforms, service types, document types, order lines, commodity volumes, commodity weights, re-throwing ratios, commodity types and special requirements.
Step S206, selecting a target special delivery rule from the plurality of special delivery rules based on the scoring result.
The target special delivery rule is selected from the special delivery rules, namely, the special delivery rule with the highest degree of adaptation with the product delivery order is selected.
Step S208 recommends a logistics distribution scheme for the matched product distribution order based on the target-specific distribution rule.
After determining the target special delivery rule, further, determining a logistics delivery scheme of the recommended product delivery order based on a pre-configured association relation.
In this embodiment, when a product delivery order of a user is obtained, whether the user configures a plurality of personalized special delivery rules is detected, so that when the user configures the plurality of special delivery rules is detected, the plurality of special delivery rules are scored based on parameter entering elements in the product delivery order, so that suitability evaluation is performed based on the score, a target special delivery rule most suitable for the product delivery order is selected from the plurality of special delivery rules based on a scoring result, and further, a matched logistics delivery scheme can be recommended for the user based on the target special delivery rules.
As shown in fig. 3, in one embodiment, step S204, if it is detected that the dedicated distribution rule is configured, scoring the plurality of dedicated distribution rules based on the entry element of the product distribution order includes:
In step S302, if it is detected that a plurality of dedicated delivery rules are configured, for each dedicated delivery rule, a plurality of dimensions are configured based on the parameter entry element of the product delivery order, and the dimension to be evaluated is selected from the plurality of dimensions based on the configuration rule element of the dedicated delivery rule.
Each of the parameter-entering elements is used as a dimension to be evaluated, and the parameter-entering elements are respectively scored as the dimension to be evaluated on the assumption that the parameter-entering elements comprise weight, volume, timeliness requirement, packaging requirement and the like of the product.
Step S304, scoring is carried out on each dimension to be evaluated based on the relation between the configuration rule element and the parameter entering element in the corresponding special distribution rule.
The relationship between the configuration rule element and the reference element includes, but is not limited to, whether the configuration rule element and the reference element are consistent, whether the configuration rule element and the reference element are within a limited range, whether the configuration rule element and the reference element are assigned values or not assigned values, and the like.
Step S306, determining a score based on the scores of the plurality of dimensions to be evaluated.
The specific implementation mode of scoring based on the scores of the multiple dimensions to be evaluated is that the multiple scores are added to obtain corresponding scores.
In this embodiment, evaluation scoring is performed on the dimension to be evaluated corresponding to each parameter entry element based on the relationship between the configuration rule element and the parameter entry element in the corresponding special distribution rule, so that the target special distribution rule is selected based on the scoring result, and the reliability of the selection of the target special configuration rule is ensured.
As shown in fig. 4, in one embodiment, step S304, for each dimension to be evaluated, a specific implementation of scoring based on a relationship between a configuration rule element and an entry element in a corresponding dedicated distribution rule, includes:
Step S402, for each dimension to be evaluated, detects whether the corresponding configuration rule element is empty.
Step S404, if the configuration rule element is null and the value of the parameter entry element is null, determining that the configuration rule element and the parameter entry element are matched, so as to score the dimension to be evaluated based on the matching condition.
If the value of the parameter entry element is null, the configuration rule element in the rule is null, which represents that the dimension matching is successful, and the dimension score can be that the weight of the rule configuration element is 1.
For example, taking the volume weight as an example, the volume weight in the parameter entry element is filled, and the volume weight in the special delivery rule is not required, and in the scoring calculation of the special delivery rule, the score of the dimension is equal to the weight of the rule configuration element by 1.
In step S406, if the configuration rule element is null, but the value of the parameter entry element is not null, it is determined that the matching condition is satisfied, so as to score the dimension to be evaluated based on the matching condition.
If the configuration rule element in the rule is null, but the value of the parameter entry element is not null, the condition is satisfied, and the dimension score may be that the weight of the rule configuration element is 1.
In one embodiment, further comprising:
step S408, if the configuration rule element is not null, but the value of the parameter element is null, determining that the matching condition is not satisfied, and counting negative points of the dimension to be evaluated.
If the rule configuration element is not null, but the value of the parameter entry element is null, the condition is not satisfied, and the dimension is represented by negative score, negative score= -9,999,999,999.
In step S410, if the configuration rule element is not null and the value of the input element is not null, it is detected whether the value of the input element is within the configuration range of the configuration rule element.
Step S412, if the value of the parameter element is in the configuration range of the configuration rule element, determining that the matching condition is satisfied, and scoring the dimension to be evaluated based on the matching condition and the configuration multiple.
If the rule configuration element is not null and the value of the parameter entering element is not null, and the value of the parameter entering element is equal to the value of the rule configuration element or is within the configuration range, the rule configuration element is satisfied, and scoring of the dimension to be evaluated=weighting of the rule configuration element is 2;
step S414, if the value of the parameter element is not in the configuration range of the configuration rule element, determining that the matching condition is not satisfied, and counting negative points of the dimension to be evaluated.
If the rule configuration element is not null, the value of the parameter entry element is not null, and the parameter entry value is not equal to the value of the rule configuration element or is not in the configuration range, the condition is not satisfied, and the dimension counts negative scores, negative scores= -9,999,999,999.
In this embodiment, by detecting different relationships between the values of the configuration rule element and the parameter entry element and scoring based on the detection result, the score of a specific distribution rule can be obtained finally, and the detection process is beneficial to ensuring the validity of the scoring result.
In one embodiment, selecting a target dedicated delivery rule from a plurality of 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 below the scoring threshold, processing the product delivery order based on a preset spam scheme.
The spam scheme can comprise refusal of a bill, sending to an anomaly management platform for processing or recommending a default logistics distribution scheme.
In this embodiment, by selecting the high-scoring dedicated delivery rule as the target dedicated delivery rule, when selecting the logistics delivery scheme of the order based on the target dedicated delivery rule, it is possible to ensure a higher degree of adaptation between the logistics delivery scheme and the product delivery order.
In one embodiment, the method further comprises recommending a logistics distribution scheme of the matched product distribution order based on the general configuration rule if the plurality of special distribution rules are detected to be not configured.
Wherein the general configuration rules popularity is a general configuration scheme for the distribution orders of the products in the industry.
For example, for clothing, there may be a float per unit weight of volume, and the relevant threshold may be adjusted, where the corresponding general distribution rule prioritizes weight and volume within a stable range, for drinks, where the weight of the drinks is high, but the volume is fixed, where the corresponding general distribution rule prioritizes value-added factors such as brittleness, where for 3C products, due to high aging and wear requirements, the corresponding general distribution rule prioritizes timeliness, and for luxury goods, where the corresponding general distribution rule prioritizes packaging, service, and other factors.
In one embodiment, recommending a logistics distribution scheme of a matched product distribution order based on a general configuration rule comprises extracting product type information from the product distribution order, determining a priority dimension matched with the product type information in a plurality of dimensions based on the general configuration rule, and determining the logistics distribution scheme corresponding to the priority dimension.
Among these, product type information includes, but is not limited to, clothing, drinks, 3C, and luxury items mentioned above, as well as fresh, food, furniture, and the like.
In this embodiment, for different industries, different products have different types of information, and by acquiring the type information, the priority dimension that needs to be prioritized in the distribution process can be determined, and because the general configuration rules corresponding to the different priority dimensions are different, the required logistics distribution scheme can be finally selected by determining the corresponding general configuration rules.
As shown in fig. 5, in one embodiment, before detecting whether a sender of a product delivery order configures a plurality of dedicated delivery rules in response to an acquired product delivery order, the method further includes:
Step S502, a plurality of service scenario information is acquired.
Step S504, determining the priority dimension corresponding to each business scenario information.
Step S506, configuring the general distribution rule based on the splicing operation of the corresponding priority dimension.
Step S508, establishing an association relationship between each general distribution rule and the corresponding logistics distribution scheme.
In this embodiment, the dimensions that need to be considered in priority, that is, priority dimensions, can be determined by acquiring the information of multiple business scenes, where the dimensions are defined and spliced as tiles of the cover room, so as to implement construction of industry rules, that is, industry bottom logic, according to the business scenes.
As shown in fig. 6, in the recommended solution of logistics distribution of the present disclosure, in order to configure the general configuration rule and the special general configuration rule, rule elements need to be entered first, wherein the entry of rule elements includes element names, element descriptions, input of element descriptions, selection of element types, and the like, and element types include single-choice type, multiple-choice type, text entry type, threshold type, and reference type.
As shown in fig. 7, in the configuration interface of the general configuration rule, the function type, the application range, the rule type, whether the general rule is or not, etc. of the configuration rule are required, and the rule is further described.
In addition, an association relationship between each general distribution rule and a corresponding logistics distribution scheme is established, configuration is carried out based on the corresponding relationship of input and output in the distribution elements, the input comprises bill types, business types, commodity codes, volumes, route ranges and the like, and the output comprises product names, vehicle types and the like.
As shown in fig. 8, in one embodiment, before detecting whether a sender of a product delivery order configures a plurality of dedicated delivery rules in response to an acquired product delivery order, the method further includes:
In step S802, in response to the obtained 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 the allocated dimension.
Step S804, generating a dedicated distribution rule based on the configuration result of the threshold range and/or the weight.
Illustratively, in the general delivery rule, the weight range is configured to be 10KG to 15KG, and in the special delivery rule, the weight range is adjusted to be 15KG to 18KG.
Step S806, establishing an association relationship between each special distribution rule and the corresponding logistics distribution scheme.
As shown in fig. 9, in the configuration interface of the special configuration rule, configuration is performed through selection and editing of rule elements, and further, in the recommendation interface of the logistics distribution product, matched logistics distribution products can be output through importing bill information.
Based on the logistics distribution recommendation scheme disclosed by the invention, distribution product recommendation strategies can be customized for the business, configurability and intellectualization can be realized through the configuration interface, a framework is built by utilizing input, matching algorithms and output logic, all rules are abstracted into elements, all rules are compatible through element sets, and proper distribution products are automatically matched for orders, so that the business lower monomer inspection is improved, the business distribution cost is saved, refined management and personalized expansion are realized, the will of a specific business is met, and the guiding significance on operation side resources is improved.
In this embodiment, in order to configure a special delivery rule, the set general delivery rule may be adjusted, including but not limited to, adjusting a threshold and a priority by using a dimension of a merchant, so as to satisfy large customer personalized logic, derive a merchant personalized rule on the general delivery rule, and automatically match a delivery product with a proper order for the merchant, thereby satisfying personalized delivery requirements of a user and improving ordering experience of a logistics service of the user.
In one embodiment, the plurality of dimensions includes 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 repeat ratio dimension, a commodity type dimension, and a special demand dimension.
Illustratively, as a certain merchant configures a plurality of special delivery rules, configuration rule elements of a first special delivery rule include a merchant, a sales platform, a service type, and an order line, each rule element being assigned a corresponding weight.
The configuration rule element of the second dedicated distribution rule includes a commodity volume and a commodity weight.
The configuration rule elements of the third special delivery rule include commodity type, special requirement and bill type,
And the obtained parameter entering elements in the product delivery order comprise specific definitions of product merchants, sales platforms, service types and bill types, so that for the first special delivery rule, the dimension to be evaluated comprises the merchants, the sales platforms, the service types, the bill types and the order lines, and the score of the first special delivery rule can be obtained based on the dimension to be evaluated.
The second special delivery rule and the third special delivery rule adopt the same scoring scheme to determine the special delivery rule with the highest score as the target special delivery rule, and further determine the matched logistics delivery scheme.
It is noted that the above-described figures are only schematic illustrations of processes involved in a method according to an exemplary embodiment of the invention, and are not intended to be limiting. It will be readily appreciated that the processes shown in the above figures do not indicate or limit the temporal order of these processes. In addition, it is also readily understood that these processes may be performed synchronously or asynchronously, for example, among a plurality of modules.
Those skilled in the art will appreciate that the various aspects of the invention may be implemented as a system, method, or program product. Accordingly, aspects of the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment (including firmware, micro-code, etc.) or an embodiment combining hardware and software aspects that may be referred to herein collectively as a "circuit," module "or" system.
A logistics distribution recommendation device 1000 according to this embodiment of the present invention is described below with reference to fig. 10. The logistics distribution recommendation apparatus 1000 shown in fig. 10 is only an example and should not be construed as limiting the function and scope of use of the embodiment of the present invention.
The recommendation device 1000 for logistics distribution is represented in the form of a hardware module. Components of the logistics distribution recommendation apparatus 1000 may include, but are not limited to, a detection module 1002 configured to detect whether a sender of a product distribution order configures a plurality of special distribution rules in response to an acquired product distribution order, a scoring module 1004 configured to score the plurality of special distribution rules based on entry elements of the product distribution order to obtain a scoring result if the configuration of the plurality of special distribution rules is detected, a selection module 1006 configured to select a target special distribution rule from the plurality of special distribution rules based on the scoring result, and a recommendation module 1008 configured to recommend a logistics distribution scheme of a matched product distribution order based on the target special distribution rule.
An electronic device 1100 according to this embodiment of the invention is described below with reference to fig. 11. The electronic device 1100 shown in fig. 11 is merely an example, and should not be construed as limiting the functionality and scope of use of embodiments of the present invention.
As shown in fig. 11, the electronic device 1100 is embodied in the form of a general purpose computing device. The components of the electronic device 1100 may include, but are not limited to, the at least one processing unit 1110 described above, the at least one memory unit 1120 described above, and a bus 1130 that connects the various system components, including the memory unit 1120 and the processing unit 1110.
Wherein the storage unit stores program code that is executable by the processing unit 1110 such that the processing unit 1110 performs steps according to various exemplary embodiments of the present invention described in the above-described "exemplary methods" section of the present specification. For example, the processing unit 1110 may perform steps S202 to S208 as shown in fig. 2, as well as other steps defined in the recommended method of logistics distribution of the present disclosure.
The storage unit 1120 may include a readable medium in the form of a volatile storage unit, such as a Random Access Memory (RAM) 11201 and/or a cache memory 11202, and may further include a Read Only Memory (ROM) 11203.
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 or some combination of which may include an implementation of a network environment.
The bus 1130 may be a local bus representing one or more of several types of bus structures, including a memory unit bus or memory unit controller, a peripheral bus, an accelerated graphics port, a processing unit, or a bus using any of a variety of bus architectures.
The electronic device 1100 may also communicate with one or more external devices 1160 (e.g., keyboard, pointing device, bluetooth device, etc.), one or more devices that enable a user to interact with the electronic device, and/or any devices (e.g., routers, modems, etc.) that enable the electronic device 1100 to communicate with one or more other computing devices. Such communication may occur through an input/output (I/O) interface 1150. Also, the electronic device 1100 may communicate with one or more networks such as a Local Area Network (LAN), a Wide Area Network (WAN), and/or a public network, such as the Internet, through a network adapter 1150. As shown, the network adapter 1150 communicates with other modules of the electronic device 1100 over the bus 1130. It should be appreciated that although not shown, other hardware and/or software modules may be used in connection with the electronic device, including, but not limited to, microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, data backup storage systems, and the like.
From the above description of embodiments, those skilled in the art will readily appreciate that the example embodiments described herein may be implemented in software, or may be implemented in software in combination with the necessary hardware. Thus, the technical solution according to the embodiments of the present disclosure may be embodied in the form of a software product, which may be stored in a non-volatile storage medium (may be a CD-ROM, a U-disk, a mobile hard disk, etc.) or on a network, including several instructions to cause a computing device (may be a personal computer, a server, a terminal device, or a network device, etc.) to perform the method according to the embodiments of the present disclosure.
In an exemplary embodiment of the present disclosure, a computer-readable storage medium having stored thereon a program product capable of implementing the method described above in the present specification is also provided. In some possible embodiments, the aspects of the invention may also be implemented in the form of a program product comprising program code for causing a terminal device to carry out the steps according to the various exemplary embodiments of the invention as described in the "exemplary method" section of this specification, when the program product is run on the terminal device.
A program product for implementing the above-described method according to an embodiment of the present invention may employ a portable compact disc read-only memory (CD-ROM) and include program code, and may be run on a terminal device, such as a personal computer. However, the program product of the present invention is not limited thereto, and in this document, a readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.
The computer readable signal medium may include a data signal propagated in baseband or as part of a carrier wave with readable program code embodied therein. Such a propagated data signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination of the foregoing. A readable signal medium may also be any readable medium that is not a readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.
Program code embodied on a 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.
Program code for carrying out operations of the present invention may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, C++ or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computing device, partly on the user's device, as a stand-alone software package, partly on the user's computing device, partly on a remote computing device, or entirely on the remote computing device or server. In the case of remote computing devices, the remote computing device may be connected to the user computing device through any kind 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., connected via the Internet using an Internet service provider).
It should be noted that although in the above detailed description several modules or units of a device for action execution are mentioned, such a division is not mandatory. Indeed, the features and functionality of two or more modules or units described above may be embodied in one module or unit in accordance with embodiments of the present disclosure. Conversely, the features and functions of one module or unit described above may be further divided into a plurality of modules or units to be embodied.
Furthermore, although the steps of the methods in the present disclosure are depicted in a particular order in the drawings, this does not require or imply that the steps must be performed in that particular order, or that all illustrated steps be performed, to achieve desirable results. Additionally or alternatively, certain steps may be omitted, multiple steps combined into one step to perform, and/or one step decomposed into multiple steps to perform, etc.
From the above description of embodiments, those skilled in the art will readily appreciate that the example embodiments described herein may be implemented in software, or may be implemented in software in combination with the necessary hardware. Thus, the technical solution according to the embodiments of the present disclosure may be embodied in the form of a software product, which may be stored in a non-volatile storage medium (may be a CD-ROM, a U-disk, a mobile hard disk, etc.) or on a network, including several instructions to cause a computing device (may be a personal computer, a server, a mobile terminal, or a network device, etc.) to perform the method according to the embodiments of the present disclosure.
Other embodiments of the disclosure will be apparent to those skilled in the art from consideration of the specification and practice of the disclosure disclosed herein. This application is intended to cover any adaptations, uses, or adaptations of the disclosure following, in general, the principles of the disclosure and including such departures from the present disclosure as come within known or customary practice within the art to which the disclosure pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the disclosure being indicated by the following claims.
Claims (13)
1. A method for recommending logistics distribution, comprising:
in response to the acquired product delivery order, detecting whether a sender of the product delivery order configures a plurality of special delivery rules;
if the configuration of the plurality of special delivery rules is detected, scoring the plurality of special delivery rules based on the parameter entering elements of the product delivery order to obtain scoring results;
Selecting a target dedicated distribution rule from the plurality of dedicated distribution rules based on the scoring result;
And recommending the matched logistics distribution scheme of the product distribution order based on the target special distribution rule.
2. The method of claim 1, wherein scoring the plurality of dedicated delivery rules based on the entry element of the product delivery order if the dedicated delivery rule is detected to be configured, comprises:
if the configuration of the plurality of special delivery rules is detected, configuring a plurality of dimensions based on the parameter entering element of the product delivery order for each special delivery rule, and selecting a dimension to be evaluated from the plurality of dimensions based on the configuration rule element of the special delivery rule;
Scoring each dimension to be evaluated based on the relation between the configuration rule element and the parameter entering element in the corresponding special distribution rule;
The score is derived based on the scores of the plurality of dimensions to be evaluated.
3. The recommendation method for logistics distribution according to claim 2, wherein said scoring based on the relationship between the configuration rule element and the entry element in the corresponding dedicated distribution rule for each of said dimensions to be evaluated comprises:
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 parameter entering element is empty, determining that the configuration rule element and the parameter entering element are matched, and scoring the dimension to be evaluated based on a matching condition;
and if the configuration rule element is empty, but the value of the parameter entry element is not empty, determining that the matching condition is met, and scoring the dimension to be evaluated based on the matching condition.
4. A method of recommending logistics distribution according to claim 3, further comprising:
If the configuration rule element is not empty, but the value of the parameter entry element is empty, determining that the matching condition is not satisfied, and counting negative points on the dimension to be evaluated;
If the configuration rule element is not null and the value of the parameter entering element is not null, detecting whether the value of the parameter entering element is in the configuration range of the configuration rule element;
If the value of the parameter entry element is in the configuration range of the configuration rule element, determining that the matching condition is met, and scoring the dimension to be evaluated based on the matching condition and the configuration multiple;
And if the value of the parameter entry element is not in the configuration range of the configuration rule element, determining that the matching condition is not met, and counting negative points on the dimension to be evaluated.
5. The method of recommending logistics distribution according to claim 2, wherein selecting a target dedicated distribution rule from the plurality of dedicated distribution rules based on the scoring result comprises:
Determining the dedicated distribution rule with the highest score as the target dedicated distribution rule,
And if the scoring result is lower than the scoring threshold, processing the product delivery order based on a preset spam scheme.
6. The method of recommending logistics distribution of claim 2, further comprising:
if the special distribution rules are not configured, recommending the matched logistics distribution scheme of the product distribution order based on the general configuration rules.
7. The method for recommending logistics in accordance with claim 6, wherein said recommending logistics in accordance with said product dispensing order based on said universal configuration rules comprises:
Extracting product type information from the product delivery order;
determining a priority dimension of the plurality of dimensions that matches the product type information based on the generic configuration rule;
And determining the logistics distribution scheme corresponding to the priority dimension.
8. The method of recommending logistics in accordance with claim 2, further comprising, prior to detecting whether a sender of the product delivery order configures a plurality of dedicated delivery rules in response to the acquired product delivery order:
acquiring a plurality of business scene information;
determining the priority dimension corresponding to each piece of business scene information;
Configuring the general distribution rule based on the splicing operation of the corresponding priority dimension, and
And establishing an association relation between each general distribution rule and the corresponding logistics distribution scheme.
9. The method of recommending logistics in accordance with claim 8, wherein prior to detecting whether a sender of the product delivery order configures a plurality of dedicated delivery rules in response to the obtained product delivery order, further comprising:
Responding to the obtained 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 distribution rule based on the threshold range and/or the configuration result of the weight, and
And establishing an association relation between each special distribution rule and the corresponding logistics distribution scheme.
10. The method of claim 2 to 9, wherein the plurality of dimensions includes 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 repeat ratio dimension, a commodity type dimension, and a special demand dimension.
11. The recommendation method for logistics distribution is characterized by being applied to a client and comprising the following steps:
the detection module is used for responding to the acquired product delivery order and detecting whether a sender of the product delivery order is configured with a plurality of special delivery rules or not;
the scoring module is used for scoring the plurality of special delivery rules based on the parameter entering elements of the product delivery order if the configuration of the plurality of special delivery rules is detected, so as to obtain a scoring result;
A selecting module, configured to select a target dedicated distribution rule from the plurality of dedicated distribution rules based on the scoring result;
And the recommending module is used for recommending the matched logistics distribution scheme of the product distribution order based on the target special distribution rule.
12. An electronic device, comprising:
Processor, and
A memory for storing executable instructions of the processor;
wherein the processor is configured to execute the recommended method of logistics distribution of any of claims 1-10 via execution of the executable instructions.
13. A computer readable storage medium having stored thereon a computer program, wherein the computer program when executed by a processor implements the logistics distribution recommendation method of any of claims 1-10.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311107969.4A CN119539640A (en) | 2023-08-30 | 2023-08-30 | Recommended method, configuration device, electronic device and storage medium for logistics distribution |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311107969.4A CN119539640A (en) | 2023-08-30 | 2023-08-30 | Recommended method, configuration device, electronic device and storage medium for logistics distribution |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN119539640A true CN119539640A (en) | 2025-02-28 |
Family
ID=94711803
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202311107969.4A Pending CN119539640A (en) | 2023-08-30 | 2023-08-30 | Recommended method, configuration device, electronic device and storage medium for logistics distribution |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN119539640A (en) |
Citations (13)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2001061580A1 (en) * | 2000-02-18 | 2001-08-23 | Kabushiki Kaisha Toshiba | Method for providing service through information network and method for using service |
| US20130166468A1 (en) * | 2011-12-22 | 2013-06-27 | Timo Vogelgesang | Business rules-based determination of retail and wholesale allocation |
| CN109784618A (en) * | 2018-12-05 | 2019-05-21 | 东南大学 | Physical distribution trading matching process |
| CN111104593A (en) * | 2019-12-12 | 2020-05-05 | 南京邮电大学 | Logistics information platform, logistics service recommendation method and logistics service coordination method |
| CN113011659A (en) * | 2021-03-23 | 2021-06-22 | 赛可智能科技(上海)有限公司 | Logistics distribution method and device and computer readable storage medium |
| CN113762829A (en) * | 2020-08-05 | 2021-12-07 | 北京京东振世信息技术有限公司 | Distribution method and device of ordered goods and computer readable medium |
| KR20220072311A (en) * | 2020-11-25 | 2022-06-02 | 재단법인 한국우편사업진흥원 | Method for designing intelligent integrated logistics platform |
| CN114693218A (en) * | 2022-04-26 | 2022-07-01 | 北京电解智科技有限公司 | Distribution order processing method and device, electronic equipment and storage medium |
| CN115375243A (en) * | 2022-09-01 | 2022-11-22 | 北京京东乾石科技有限公司 | Order distribution method and device, electronic equipment and computer readable medium |
| CN115936569A (en) * | 2022-11-28 | 2023-04-07 | 福建省捷邦供应链管理股份有限公司 | Logistics storage distribution management method, system, device and storage medium |
| CN116307973A (en) * | 2023-01-11 | 2023-06-23 | 阿里巴巴（中国）有限公司 | Configuration method, logistics service scheme determination method and computing equipment |
| US20230281255A1 (en) * | 2022-03-07 | 2023-09-07 | Markison Patent Portal, Inc. | Computer with improved computer architecture |
| CN120873037A (en) * | 2025-09-18 | 2025-10-31 | 浪潮云信息技术股份公司 | Multi-dimensional feature fusion-based field rule matching recommendation method and device |
-
2023
- 2023-08-30 CN CN202311107969.4A patent/CN119539640A/en active Pending
Patent Citations (13)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2001061580A1 (en) * | 2000-02-18 | 2001-08-23 | Kabushiki Kaisha Toshiba | Method for providing service through information network and method for using service |
| US20130166468A1 (en) * | 2011-12-22 | 2013-06-27 | Timo Vogelgesang | Business rules-based determination of retail and wholesale allocation |
| CN109784618A (en) * | 2018-12-05 | 2019-05-21 | 东南大学 | Physical distribution trading matching process |
| CN111104593A (en) * | 2019-12-12 | 2020-05-05 | 南京邮电大学 | Logistics information platform, logistics service recommendation method and logistics service coordination method |
| CN113762829A (en) * | 2020-08-05 | 2021-12-07 | 北京京东振世信息技术有限公司 | Distribution method and device of ordered goods and computer readable medium |
| KR20220072311A (en) * | 2020-11-25 | 2022-06-02 | 재단법인 한국우편사업진흥원 | Method for designing intelligent integrated logistics platform |
| CN113011659A (en) * | 2021-03-23 | 2021-06-22 | 赛可智能科技(上海)有限公司 | Logistics distribution method and device and computer readable storage medium |
| US20230281255A1 (en) * | 2022-03-07 | 2023-09-07 | Markison Patent Portal, Inc. | Computer with improved computer architecture |
| CN114693218A (en) * | 2022-04-26 | 2022-07-01 | 北京电解智科技有限公司 | Distribution order processing method and device, electronic equipment and storage medium |
| CN115375243A (en) * | 2022-09-01 | 2022-11-22 | 北京京东乾石科技有限公司 | Order distribution method and device, electronic equipment and computer readable medium |
| CN115936569A (en) * | 2022-11-28 | 2023-04-07 | 福建省捷邦供应链管理股份有限公司 | Logistics storage distribution management method, system, device and storage medium |
| CN116307973A (en) * | 2023-01-11 | 2023-06-23 | 阿里巴巴（中国）有限公司 | Configuration method, logistics service scheme determination method and computing equipment |
| CN120873037A (en) * | 2025-09-18 | 2025-10-31 | 浪潮云信息技术股份公司 | Multi-dimensional feature fusion-based field rule matching recommendation method and device |
Non-Patent Citations (1)
| Title |
|---|
| 邵亚飞;: "层次分析法在服装零售连锁企业第三方物流评选中的应用", 企业技术开发, no. 03, 1 February 2010 (2010-02-01), pages 67 - 69 * |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US11120493B2 (en) | Payment method, apparatus and system | |
| CN108334387B (en) | Dynamic interface rendering method and device | |
| CN113657471B (en) | Method, device and electronic device for constructing multi-classification gradient boosting tree | |
| US12524623B2 (en) | Extensible digital assistant interface using natural language processing to respond to user intent | |
| EP2887299A1 (en) | System and method for online shopping | |
| CN114066363A (en) | Order information processing method and device, electronic equipment and computer readable medium | |
| US12333481B1 (en) | Dynamic physical data transfer routing | |
| CN115330494A (en) | Online retail method, device, equipment and storage medium based on community group buying | |
| CN107977876A (en) | For handling the method and device of sequence information | |
| CN111861598A (en) | Object display method, apparatus, electronic device and readable medium | |
| US20230067824A1 (en) | Preference inference device, preference inference method, and preference inference program | |
| CN113554493B (en) | Interactive ordering method, device, electronic equipment and computer readable medium | |
| US20200118193A1 (en) | Digital content publisher negotiated transactional advertiser | |
| US20140279399A1 (en) | System and method for matching vendors and clients | |
| CN119539640A (en) | Recommended method, configuration device, electronic device and storage medium for logistics distribution | |
| US11475395B2 (en) | Systems and methods for combinatorial resource optimization | |
| CN111078636A (en) | Marketing data processing method and system and related equipment | |
| WO2023018956A1 (en) | Device recognition using recognition identifier | |
| JP2023169086A (en) | Information processing device, information processing method and information processing program | |
| JP2023171710A (en) | Information processing apparatus, information processing method, and information processing program | |
| US20170161714A1 (en) | Selecting an electronic payment account to maximize rewards | |
| CN110099125B (en) | Information switching method and device, electronic equipment and computer readable storage medium | |
| CN108961000B (en) | Automatic order generation method, system, medium and electronic equipment | |
| CN113762684A (en) | New user risk assessment method and device, electronic equipment and medium | |
| CN114757738A (en) | Commodity information processing method, processing device, electronic device and storage medium |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |