Logistics order processing method and device, equipment and storage medium
By identifying service scenarios and generating personalized notification copy through real-time logistics trajectory data, the problem of lack of personalization in traditional logistics notification methods is solved, and customer satisfaction and logistics service efficiency are improved.
Patent Information
- Application Number
- CN202411358039.0
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-09-27
- Publication Date
- 2024-12-27
AI Technical Summary
Traditional logistics notification methods lack personalization and cannot accurately convey service scenarios and key information, resulting in poor customer experience and difficult to meet customers' needs for personalized service notifications.
By obtaining real-time logistics trajectory data, the current service scenario is determined, and the dynamic fields are filled with the scene are generated to generate personalized notification copy, which is sent to the target object, and the decision model and copy template database are used to realize intelligent copy generation and multi-channel push.
It improves the relevance and effectiveness of notifications, enhances customers' trust and satisfaction with logistics services, improves the quality and efficiency of logistics services, reduces manual communication needs, and improves the real-time and flexibility of services.
Smart Images
Figure CN119204887A_ABST
Abstract
Description
Technical Field
[0001] The present invention belongs to the field of logistics and transportation technology, and specifically relates to a logistics order processing method, device, equipment and storage medium. Background Art
[0002] In the current logistics service field, customers have increasingly higher requirements for the timeliness and accuracy of logistics information. Traditional logistics notification methods are often relatively general and lack personalization, and cannot accurately convey specific service scenarios and key information to customers, resulting in poor customer experience. In addition, the complexity and diversity of logistics data make it a challenge to accurately identify service scenarios and generate corresponding notification copy. Due to the lack of effective data analysis and processing mechanisms, as well as intelligent copy generation and multi-channel push systems, logistics companies find it difficult to meet customers' expectations for personalized service notifications. Summary of the invention
[0003] In view of the deficiencies in the prior art, the purpose of the present invention is to provide a logistics order processing method, device, equipment and storage medium to solve the problem that the prior art logistics transportation order processing method is single and cannot meet customers' personalized information needs.
[0004] According to one aspect of the present application, the present application provides a logistics order processing method, the method comprising:
[0005] Obtain real-time logistics track data of target logistics orders;
[0006] Determining a current service scenario of the target logistics order according to the real-time logistics trajectory data;
[0007] Determine a target copy template corresponding to the current service scenario, wherein the target copy template contains a plurality of preset dynamic fields;
[0008] Extracting target attribute data from the real-time logistics trajectory data, wherein the target attribute data is one or more of the real-time logistics trajectory data, and one target attribute data corresponds to one preset dynamic field;
[0009] Based on the target attribute data and the current service scenario, the dynamic fields in the target copy template are correspondingly filled to obtain the notification copy of the current service scenario;
[0010] The notification text is sent to the target object.
[0011] In some embodiments, determining the current service scenario of the target logistics order according to the real-time logistics track includes:
[0012] Performing data cleaning and data conversion on the real-time logistics trajectory data to obtain target trajectory data in a target format;
[0013] extracting a plurality of target fields from the target trajectory data in the target format;
[0014] Obtaining a field meaning correspondence table, wherein the field meaning correspondence table represents a correspondence between fields and field meanings;
[0015] Based on the field meaning correspondence table, determining the target field meanings corresponding to each of the plurality of target fields;
[0016] Obtaining a service scenario correspondence table, wherein the service scenario correspondence table represents the correspondence between the field meanings and the service scenarios, wherein a plurality of target field meaning combinations correspond to one service scenario;
[0017] Based on the scenario service correspondence table and the meanings of the multiple target fields, the current service scenario of the target logistics order is determined.
[0018] In some embodiments, determining the current service scenario of the target logistics order according to the real-time logistics track includes:
[0019] The real-time logistics trajectory is input into a target decision model to determine the current service scenario of the target logistics order based on an output result of the target decision model, wherein the target decision model is pre-trained, and training the target decision model includes:
[0020] Get the historical logistics tracks corresponding to multiple historical orders;
[0021] Extracting characteristic data from the plurality of historical logistics trajectories;
[0022] Determine multiple preset service scenarios;
[0023] Setting a label identifier for each of the preset service scenarios;
[0024] The target decision model is trained based on the feature data and the label identifier.
[0025] In some embodiments, obtaining a target copy template corresponding to the current service scenario includes:
[0026] Obtaining the correspondence between the service scenario and the copywriting template;
[0027] Get the copywriting template database;
[0028] Based on the correspondence between the service scenario and the copy template, a target copy template corresponding to the current service scenario is acquired from the copy template database.
[0029] In some embodiments, extracting target attribute data from the real-time logistics trajectory data includes:
[0030] Determine identification data for identifying the current service scenario, and use the identification data as the target attribute data to be extracted;
[0031] Extract the target attribute data from the real-time logistics trajectory data
[0032] In some embodiments, filling the dynamic fields in the target copy template accordingly based on the target attribute data includes:
[0033] Obtain the correspondence between attribute data, dynamic fields, and service scenarios;
[0034] Based on the correspondence between the attribute data, the dynamic field and the service scenario, the target attribute data and the current service scenario replace the field value of the corresponding preset dynamic field.
[0035] In some embodiments, sending the notification text to the target object includes:
[0036] Determine a target sending mode of the target object;
[0037] The notification text is sent to the target object based on the target sending method.
[0038] According to another aspect of the present application, a logistics order processing device is also disclosed, the device comprising:
[0039] A real-time logistics track data acquisition module is used to acquire the real-time logistics track data of the target logistics order;
[0040] A current service scenario determination module, used to determine the current service scenario of the target logistics order according to the real-time logistics trajectory data;
[0041] A target copy template determination module, used to determine a target copy template corresponding to the current service scenario, wherein the target copy template contains a plurality of preset dynamic fields;
[0042] A target attribute data extraction module, used to extract target attribute data from the real-time logistics trajectory data, wherein the target attribute data is one or more of the real-time logistics trajectory data, and one target attribute data corresponds to one preset dynamic field;
[0043] A filling module, configured to fill the dynamic fields in the target copy template accordingly based on the target attribute data and the current service scenario, so as to obtain the notification copy of the current service scenario;
[0044] The notification copy sending module is used to send the notification copy to the target object.
[0045] According to another aspect of the present application, an electronic device is also disclosed, which includes a memory and at least one processor, wherein the memory stores instructions; the at least one processor calls the instructions in the memory so that the electronic device executes each step of the logistics order processing method as described in any one of the above items.
[0046] According to another aspect of the present application, a computer-readable storage medium is also disclosed, on which instructions are stored, characterized in that when the instructions are executed by a processor, each step of the logistics order processing method as described in any one of the above items is implemented.
[0047] The present invention includes but is not limited to the following beneficial effects: (1) The present application can generate personalized notification text based on the current service scenario, thereby improving the relevance and effectiveness of the notification, enhancing customer trust and satisfaction with logistics services, and improving the overall service quality and efficiency of logistics; (2) The present application can obtain real-time logistics trajectory data to understand the status of logistics orders in real time, thereby timely updating service scenarios and notification texts and improving the real-time nature of services; (3) By determining the current service scenario and filling in the corresponding dynamic fields, personalized notification texts can be generated for specific service scenarios to improve the relevance and effectiveness of notifications; (4) By automatically generating and sending notification texts, the need for manual communication can be reduced, thereby reducing communication costs; (5) By performing data cleaning and data conversion on real-time logistics trajectory data, the present application can improve data quality, reduce the impact of noise and outliers, and thereby improve the accuracy of service scenario identification; (6) By obtaining a field meaning correspondence table, the meaning of each field can be clarified, the data interpretability can be enhanced, and it is helpful to understand and analyze the data; (7) By combining the meanings of multiple target fields to correspond to a service scenario, more flexible identification can be achieved. (8) Through data-based service scenario identification and notification copy generation, the decision-making process can be optimized and the efficiency and effectiveness of decision-making can be improved; (9) When training the target decision model, by setting label identifiers for preset service scenarios, new service scenarios can be easily added to improve the scalability of the service; (10) In this application, by setting different copy templates for different service scenarios, more personalized services can be provided to enhance customer satisfaction; (11) In this application, by extracting target attribute data from logistics trajectory data in real time, changes in service scenarios can be responded to more quickly, and the real-time performance of services can be improved. Moreover, by extracting identification data used to identify the current service scenario, the current service scenario can be predicted more accurately, thereby generating more accurate notification copy. Furthermore, by filling dynamic fields based on real-time target attribute data, changes in service scenarios can be responded to more quickly, thereby improving the real-time performance of services; (12) In this application, different target objects correspond to different target sending methods. By determining the target sending method of the target object, the notification copy can be sent to the target object more effectively, thereby improving the notification efficiency. BRIEF DESCRIPTION OF THE DRAWINGS
[0048] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art are briefly introduced below.
[0049] Figure 1 It is a flow chart of the logistics order processing method of the embodiment of the present application;
[0050] Figure 2is another flow chart of the logistics order processing method of the embodiment of the present application;
[0051] Figure 3 is another flow chart of the logistics order processing method of the embodiment of the present application;
[0052] Figure 4 is a structural block diagram of a logistics order processing device according to an embodiment of the present application;
[0053] Figure 5 It is a schematic diagram of the structure of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION
[0054] The embodiment of the present invention provides a logistics order processing method, including obtaining real-time logistics trajectory data of a target logistics order; determining the current service scenario of the target logistics order according to the real-time logistics trajectory data; determining a target copy template corresponding to the current service scenario, wherein there are multiple preset dynamic fields in the target copy template; extracting target attribute data from the real-time logistics trajectory data, wherein the target attribute data is one or more of the real-time logistics trajectory data, and one target attribute data corresponds to one preset dynamic field; based on the target attribute data and the current service scenario, correspondingly filling in the dynamic fields in the target copy template to obtain a notification copy of the current service scenario; and sending the notification copy to the target object. The present application can improve the relevance and effectiveness of notifications by generating personalized notification copy based on the current service scenario, thereby enhancing customer trust and satisfaction with logistics services and improving the overall service quality and efficiency of logistics.
[0055] The terms "first", "second", "third", "fourth", etc. (if any) in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments described herein can be implemented in an order other than that illustrated or described herein. In addition, the terms "including" or "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.
[0056] For ease of understanding, the specific process of the embodiment of the present invention is described below. Specifically, Figure 1 This is a flow chart of the logistics order processing method of this application, and the steps include:
[0057] S100: Acquire real-time logistics track data of a target logistics order.
[0058] In one example, logistics orders that require attention can be screened out as target logistics orders based on specific conditions (such as customer demand, order status, time period, etc.). These conditions can be set by user input or automatically by the system. The target logistics order can also be confirmed based on a unique identifier (such as an order number) to ensure the accuracy of subsequent operations. Furthermore, after obtaining the target logistics order, the real-time logistics trajectory data of the target logistics order can be obtained from the logistics tracking system or real-time monitoring platform, where the trajectory data may include but is not limited to the current location (GPS coordinates or geographic location), various nodes in the transportation process (such as transfer stations, distribution centers, etc.), and timestamps (arrival and departure times of each node), etc.
[0059] Furthermore, after obtaining the target logistics order, it is also possible to connect to a logistics management system, a database or other information source to extract order data information related to the target logistics order, wherein the order data information may include but is not limited to the place of shipment and the destination.
[0060] S102: Determine the current service scenario of the target logistics order based on the real-time logistics trajectory data.
[0061] Specifically, in one example, Figure 2 This is a flowchart of an exemplary method for determining the current service scenario of the target logistics order according to the real-time logistics trajectory data in step S102, see Figure 2 As shown, the method comprises the following steps:
[0062] S200: Perform data cleaning and data conversion on the real-time logistics trajectory data to obtain target trajectory data in a target format.
[0063] Specifically, data cleaning can refer to checking and correcting or deleting errors, inconsistencies or irrelevant parts in the data. In one example, data cleaning of real-time logistics trajectory data can first check the missing values in the real-time logistics trajectory data and process them, such as filling missing values or deleting missing data records, and further detect and process abnormal values, such as unreasonable time intervals, geographic location deviations, etc. Among them, invalid data in real-time logistics trajectory data can be removed based on the missing value processing algorithm, and abnormal characters or erroneous records in the data can be identified and removed based on regular expression matching and denoising algorithms;
[0064] Furthermore, the data conversion here may refer to the conversion of the real-time logistics trajectory data after cleaning. For example, timestamps in different formats may be converted into a unified time format to ensure data consistency and a unified representation of geographic location, such as converting different coordinate systems into a unified coordinate system (such as WGS84). Among them, time data in different formats may be unified into a specific standard format based on a time conversion function, thereby obtaining target trajectory data in a target format.
[0065] Furthermore, the trajectory data can be simplified, such as by using trajectory point clustering or trajectory line simplification algorithms to reduce the amount of data, and by aggregating continuous trajectory points in the same state to simplify the representation of trajectory data.
[0066] S202: extract multiple target fields from the target trajectory data in a target format.
[0067] Specifically, according to the data storage format (such as JSON, XML, CSV, etc.), a suitable parsing tool can be selected to further parse the data in the target trajectory data to obtain multiple fields, and then the target field to be extracted from the multiple fields can be extracted. It can be understood that the target field to be extracted can be predetermined and directly extracted after the data is parsed. Exemplarily, the target field can be the fields such as Scan_type, remarkid, udf01 to udf03, SVC_LVL and Cmt_Inf mentioned in the above example.
[0068] S204: Obtain a field meaning correspondence table.
[0069] Specifically, the field meaning correspondence table represents the correspondence between the field and the field meaning, and the correspondence table can be preset. In an example, continuing the above example analysis, it can be seen that the correspondence between the field and the field meaning can be as follows:
[0070] Scan_type: A field that can represent the scan type, used to identify the type of logistics operation.
[0071] remarkid: This can be a field used to record special remarks or identification.
[0072] udf01, udf02, udf03: can be user-defined fields that can store specific information based on business needs.
[0073] SVC_LVL: can be a service level field, indicating the grade or type of logistics service.
[0074] Cmt_Inf: This can be a comment or note information field, containing a detailed description text about the logistics service.
[0075] S206: Determine the target field meanings corresponding to the multiple target fields based on the field meaning correspondence table.
[0076] Specifically, after the field meaning correspondence table is obtained, the target field meaning corresponding to each target field is determined based on the corresponding relationship in the correspondence table.
[0077] S208. Obtain a service scenario correspondence table.
[0078] S210. Determine the current service scenario of the target logistics order based on the scenario service correspondence table and the meanings of multiple target fields.
[0079] Specifically, the service scenario correspondence table represents the correspondence between the field meaning and the service scenario. The correspondence can be preset. In one example, a combination of multiple target field meanings corresponds to a service scenario. Exemplarily, based on the above examples, when the target field Scan_type is "scanned" and the target field SVC_LVL is high-level, the corresponding service scenario is "door-to-door delivery", and when the target field Scan_type is "scanned" and the target field SVC_LVL is low-level, the corresponding service scenario is "self-pickup". It can be understood that the above correspondence is only a preferred setting method. In other feasible schemes, there can also be other combinations, which are not specifically limited here.
[0080] In the embodiment of the application, the application can understand the status of logistics orders in real time by acquiring real-time logistics trajectory data, thereby timely updating service scenarios and notification texts, and improving the real-time nature of services. Furthermore, by performing data cleaning and data conversion on real-time logistics trajectory data, the quality of data can be improved, the impact of noise and outliers can be reduced, and the accuracy of service scenario identification can be improved; by acquiring a field meaning correspondence table, the meaning of each field can be clarified, the interpretability of the data can be enhanced, and it is helpful to understand and analyze the data; by combining the meanings of multiple target fields to correspond to a service scenario, a variety of service scenarios can be more flexibly identified, and the flexibility of services can be improved;
[0081] Furthermore, in another example, determining the current service scenario of the target logistics order based on the real-time logistics trajectory data can specifically be inputting the real-time logistics trajectory into the target decision model to determine the current service scenario of the target logistics order based on the output result of the target decision model.
[0082] Specifically, the target decision model is pre-trained. In one example, the training target decision model can be based on Figure 3 The flowchart shown is implemented, for details, refer to Figure 3 , which may specifically include the following steps:
[0083] S300: Obtain historical logistics tracks corresponding to each of a plurality of historical orders.
[0084] Specifically, it is possible to first determine which historical orders need to obtain logistics trajectories. In some examples, this can be based on certain specific conditions, such as obtaining all orders within the past week or the past month, or obtaining all orders from a specific customer. Furthermore, after obtaining the target logistics order, the historical logistics trajectory corresponding to each historical order can be obtained from the logistics tracking system or real-time monitoring platform, where the trajectory data of each historical logistics trajectory may include but is not limited to the current location (GPS coordinates or geographic location), various nodes in the transportation process (such as transfer stations, distribution centers, etc.), and timestamps (arrival and departure times of each node), etc.
[0085] S302: Extract feature data from multiple historical logistics trajectories.
[0086] In some examples, feature data may include, but are not limited to, order processing time, number of transfer stations, total transportation distance, number of delayed shipments, etc. Specifically, order processing time is usually the start time and end time of an order. These times usually exist as fields in logistics data. What we need to do is to subtract the start time from the end time to get the order processing time. It should be noted that feature data needs to be extracted from each historical logistics estimation trajectory.
[0087] S304: Determine multiple preset service scenarios.
[0088] Specifically, the preset service scenarios may include, but are not limited to, door-to-door delivery, door-to-door delivery, and other service scenarios. In one example, multiple preset service scenarios may be pre-set based on a model such as a questionnaire.
[0089] S306: Set a label identifier for each preset service scenario.
[0090] In one example, based on the preset service scenarios exemplified above, the label identification of home delivery can be set as "10", the label identification of self-pickup to home delivery can be set as "20", and the label identification of door-to-door delivery can be set as "30". It can be understood that the label identification can be set based on one's own needs, and the above examples of label identification for each preset service scenario are only a preferred embodiment and are not limited thereto.
[0091] S308: Training a target decision model based on feature data and label identification.
[0092] In one example, the acquired multiple feature data can be grouped to obtain a training group, a test group, and a verification group. The target decision model is trained using the feature data corresponding to the training group, and the test and verification are performed based on the feature data corresponding to the test group and the verification group, respectively, to improve the accuracy and generalization ability of the target decision model. When training the target decision model, the present application can easily add new service scenarios by setting label identifiers for preset service scenarios, thereby improving the scalability of the service.
[0093] S104: Determine a target copy template corresponding to the current service scenario, wherein the target copy template contains a plurality of preset dynamic fields.
[0094] Specifically, in one example, determining the target copy template corresponding to the current service scenario can be performed by first obtaining the correspondence between the service scenario and the copy template; secondly obtaining the copy template database; and thirdly obtaining the target copy template corresponding to the current service scenario from the copy template database based on the correspondence between the service scenario and the copy template. It is understandable that the copy template database pre-stores multiple copy templates, each copy template corresponding to a service scenario.
[0095] It can be understood that the target copy template is one of multiple copy templates in the copy template database, and the target copy template includes multiple preset dynamic fields. In one example, the preset dynamic fields can be key fields such as Scan_type, remarkid, udf01 to udf03, SVC_LVL and Cmt_Inf. Among them, remarkid can be a field used to record special remarks or identifications; udf01, udf02, udf03: can be user-defined fields, which can store specific information according to business needs; SVC_LVL can be a service level field, indicating the level or type of logistics service; Cmt_Inf can be a comment or note information field, containing a detailed description text about the logistics service.
[0096] S106. Extract target attribute data from the real-time logistics trajectory data.
[0097] Specifically, dynamic fields may refer to data fields that change according to actual conditions during the logistics process. The values of these fields are not fixed at the beginning of the logistics activities, but change with the different stages of the transportation, processing and delivery of the goods. Dynamic fields can provide real-time, updated information to help logistics companies, customers and other relevant parties track and manage the status of goods. For example, information such as order number and delivery time. Target attribute data refers to the actual data of the dynamic fields that will be filled in the copy template. These data may include order number, estimated time of arrival, current location, service type, etc. These data usually come from logistics information systems, databases or real-time tracking services. It can be understood that by extracting target attribute data from logistics trajectory data in real time, changes in service scenarios can be responded to more quickly, and the real-time nature of services can be improved. Moreover, by extracting identification data for identifying the current service scenario, the current service scenario can be predicted more accurately, thereby generating more accurate notification copy. Further, by filling dynamic fields based on real-time target attribute data, changes in service scenarios can be responded to more quickly, and the real-time nature of services can be improved.
[0098] S108. Based on the target attribute data and the current service scenario, the dynamic fields in the target copy template are filled accordingly to obtain the notification copy of the current service scenario.
[0099] Specifically, based on the target attribute data and the current service scenario, the dynamic fields in the target copy template are filled in accordingly to obtain the notification copy of the current service scenario. Specifically, it can be that the correspondence between the attribute data, the dynamic fields and the service scenarios is first obtained, and then based on the correspondence between the attribute data, the dynamic fields and the service scenarios, the target attribute data and the current service scenario are replaced with the field values of the corresponding preset dynamic fields.
[0100] S110: Send the notification text to the target object.
[0101] It can be understood that the present application can improve the relevance and effectiveness of notifications by generating personalized notification copy based on the current service scenario, thereby enhancing customers' trust and satisfaction with logistics services and improving the overall service quality and efficiency of logistics; further, by determining the current service scenario and filling in the corresponding dynamic fields, personalized notification copy for specific service scenarios can be generated to improve the relevance and effectiveness of notifications; by automatically generating and sending notification copy, the need for manual communication can be reduced, thereby reducing communication costs.
[0102] Specifically, before sending the notification text to the target object, the target sending method of the target object can be determined first; it is understandable that different target objects can correspond to different sending methods, for example, the target object can be a customer, a consignee, or a relevant stakeholder. It is understandable that understanding the preferences of the target object is the key to choosing a sending method, which may include the target object's preferred method of receiving information (such as email, text message, App notification, etc.), as well as their preference for the time to receive information. Furthermore, the notification text is sent to the target object based on the target sending method. Specifically, different target objects correspond to different target sending methods. By determining the target sending method of the target object, the notification text can be sent to the target object more effectively, thereby improving the efficiency of notification.
[0103] According to another aspect of the present application, a logistics order processing device is also disclosed. Specifically, Figure 4 As shown, the logistics order processing device includes:
[0104] A real-time logistics track data acquisition module is used to acquire the real-time logistics track data of the target logistics order;
[0105] The current service scenario determination module is used to determine the current service scenario of the target logistics order based on the real-time logistics trajectory data;
[0106] A target copy template determination module is used to determine a target copy template corresponding to the current service scenario, and there are multiple preset dynamic fields in the target copy template;
[0107] A target attribute data extraction module is used to extract target attribute data from the real-time logistics trajectory data. The target attribute data is one or more of the real-time logistics trajectory data. One target attribute data corresponds to one preset dynamic field.
[0108] A filling module is used to fill the dynamic fields in the target copy template accordingly based on the target attribute data and the current service scenario to obtain the notification copy for the current service scenario;
[0109] The notification copy sending module is used to send the notification copy to the target object.
[0110] Further, in one example, the current service scenario determination module includes:
[0111] A data processing unit, used for cleaning and converting the real-time logistics trajectory data to obtain target trajectory data in a target format;
[0112] A target field extraction unit, used for extracting a plurality of target fields from the target trajectory data in a target format;
[0113] A field meaning correspondence table acquisition unit, used to acquire a field meaning correspondence table, wherein the field meaning correspondence table represents the correspondence between the field and the field meaning;
[0114] A target field meaning determination unit determines target field meanings corresponding to each of the plurality of target fields based on the field meaning correspondence table;
[0115] A service scenario correspondence table acquisition unit, used to acquire a service scenario correspondence table, wherein the service scenario correspondence table represents the correspondence between field meanings and service scenarios, wherein a combination of multiple target field meanings corresponds to one service scenario;
[0116] The current service scenario determination unit is used to determine the current service scenario of the target logistics order based on the scenario service correspondence table and the meanings of multiple target fields.
[0117] Furthermore, in one example, the current service scenario determination module further includes:
[0118] An input unit is used to input the real-time logistics trajectory into the target decision model to determine the current service scenario of the target logistics order based on the output result of the target decision model, wherein the target decision model is pre-trained, and training the target decision model includes obtaining the historical logistics trajectories corresponding to multiple historical orders; extracting feature data from the multiple historical logistics trajectories; determining multiple preset service scenarios; setting a label identifier for each preset service scenario; and training the target decision model based on the feature data and the label identifier.
[0119] Furthermore, the target copy template determination module includes:
[0120] A copy template correspondence relationship acquisition unit, used to acquire the correspondence relationship between the service scenario and the copy template;
[0121] A copy template database acquisition unit, used to acquire a copy template database;
[0122] The target copy template acquisition unit is used to acquire a target copy template corresponding to the current service scenario from a copy template database based on the correspondence between the service scenario and the copy template.
[0123] Furthermore, the target attribute data extraction module includes:
[0124] An identification data determination unit, used to determine identification data for identifying the current service scenario, and use the identification data as target attribute data to be extracted;
[0125] The target attribute data determination unit is used to extract the target attribute data from the real-time logistics trajectory data.
[0126] Furthermore, the filling module also includes:
[0127] A service scenario correspondence acquisition unit, used to acquire the correspondence between attribute data, dynamic fields and service scenarios;
[0128] The replacement unit is used to replace the field value of the corresponding preset dynamic field with the target attribute data and the current service scenario based on the correspondence between the attribute data, the dynamic field and the service scenario.
[0129] Furthermore, the notification copy sending module includes:
[0130] A target sending mode determining unit, used to determine a target sending mode of a target object;
[0131] The notification text determination unit is used to send the notification text to the target object based on the target sending method.
[0132] The application introduction of the relevant modules of the device in this example can refer to the relevant introduction of the principle of the above method, which will not be repeated here.
[0133] According to another aspect of the present application, the present application also discloses an electronic device, which includes a memory and at least one processor, wherein instructions are stored in the memory; at least one processor calls the instructions in the memory so that the electronic device executes each step of the above logistics order processing method.
[0134] above Figure 4 The grid warehouse billing device based on operating status in the embodiment of the present invention is described in detail from the perspective of modular functional entities, and the electronic device in the embodiment of the present invention is described in detail from the perspective of hardware processing.
[0135] Figure 5 is a schematic diagram of the structure of an electronic device provided by an embodiment of the present invention. The electronic device 500 may have relatively large differences due to different configurations or performances, and may include one or more processors (central processing units, CPU) 510 (for example, one or more processors) and a memory 520, and one or more storage media 530 (for example, one or more mass storage devices) storing application programs 533 or data 532. Among them, the memory 520 and the storage medium 530 can be short-term storage or permanent storage. The program stored in the storage medium 530 may include one or more modules (not shown in the figure), and each module may include a series of instruction operations in the electronic device 500. Furthermore, the processor 510 can be configured to communicate with the storage medium 530 to execute a series of instruction operations in the storage medium 530 on the electronic device 500.
[0136] The electronic device 500 may also include one or more power supplies 540, one or more wired or wireless network interfaces 550, one or more input and output interfaces 550, and / or one or more operating systems 531, such as Windows Serve, Mac OS X, Unix, Linux, FreeBSD, etc. It will be appreciated by those skilled in the art that Figure 5 The structure of the electronic device shown does not constitute a limitation on the electronic device, and may include more or less components than shown in the figure, or combine some components, or arrange the components differently.
[0137] The present invention also provides a computer-readable storage medium, which may be a non-volatile computer-readable storage medium or a volatile computer-readable storage medium. Instructions are stored in the computer-readable storage medium. When the instructions are executed on a computer, the computer executes the steps of the logistics order processing method.
[0138] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working process of the above-described system, device, or unit can refer to the corresponding process in the aforementioned method embodiment and will not be repeated here.
[0139] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution can be embodied in the form of a software product, which is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods of each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM), random access memory (RAM), disk or optical disk, etc., various media that can store program codes.
[0140] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features thereof may be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.
Claims
1. A logistics order processing method, characterized in that: The method comprises: Obtain real-time logistics track data of target logistics orders; Determining a current service scenario of the target logistics order according to the real-time logistics trajectory data; Determine a target copy template corresponding to the current service scenario, wherein the target copy template contains a plurality of preset dynamic fields; Extracting target attribute data from the real-time logistics trajectory data, wherein the target attribute data is one or more of the real-time logistics trajectory data, and one target attribute data corresponds to one preset dynamic field; Based on the target attribute data and the current service scenario, the dynamic fields in the target copy template are correspondingly filled to obtain the notification copy of the current service scenario; The notification text is sent to the target object.
2. The logistics order processing method according to claim 1, characterized in that: Determining the current service scenario of the target logistics order according to the real-time logistics track includes: Performing data cleaning and data conversion on the real-time logistics trajectory data to obtain target trajectory data in a target format; extracting a plurality of target fields from the target trajectory data in the target format; Obtaining a field meaning correspondence table, wherein the field meaning correspondence table represents a correspondence between fields and field meanings; Determining target field meanings corresponding to each of the plurality of target fields based on the field meaning correspondence table; Obtaining a service scenario correspondence table, wherein the service scenario correspondence table represents the correspondence between the field meaning and the service scenario, wherein a plurality of target field meaning combinations correspond to one service scenario; Based on the scenario service correspondence table and the meanings of the multiple target fields, the current service scenario of the target logistics order is determined.
3. The logistics order processing method according to claim 1, characterized in that: Determining the current service scenario of the target logistics order according to the real-time logistics track includes: The real-time logistics trajectory is input into a target decision model to determine the current service scenario of the target logistics order based on an output result of the target decision model, wherein the target decision model is pre-trained, and training the target decision model includes: Get the historical logistics tracks corresponding to multiple historical orders; Extracting characteristic data from the plurality of historical logistics trajectories; Determine multiple preset service scenarios; Setting a label identifier for each of the preset service scenarios; The target decision model is trained based on the feature data and the label identifier.
4. The logistics order processing method according to claim 1, characterized in that: The acquiring of the target copy template corresponding to the current service scenario includes: Obtaining the correspondence between the service scenario and the copywriting template; Get the copywriting template database; Based on the correspondence between the service scenario and the copy template, a target copy template corresponding to the current service scenario is acquired from the copy template database.
5. The logistics order processing method according to claim 1, characterized in that: The extracting target attribute data from the real-time logistics trajectory data comprises: Determine identification data for identifying the current service scenario, and use the identification data as the target attribute data to be extracted; The target attribute data is extracted from the real-time logistics trajectory data.
6. The logistics order processing method according to claim 1, characterized in that: The corresponding filling of the dynamic fields in the target copy template based on the target attribute data includes: Obtain the correspondence between attribute data, dynamic fields, and service scenarios; Based on the correspondence between the attribute data, the dynamic field and the service scenario, the target attribute data and the current service scenario replace the field value of the corresponding preset dynamic field.
7. The logistics order processing method according to claim 1, characterized in that: The sending of the notification text to the target object includes: Determine a target sending mode of the target object; The notification text is sent to the target object based on the target sending method.
8. A logistics order processing device, characterized in that: The device comprises: A real-time logistics track data acquisition module is used to acquire the real-time logistics track data of the target logistics order; A current service scenario determination module, used to determine the current service scenario of the target logistics order according to the real-time logistics trajectory data; A target copy template determination module, used to determine a target copy template corresponding to the current service scenario, wherein the target copy template contains a plurality of preset dynamic fields; A target attribute data extraction module, used to extract target attribute data from the real-time logistics trajectory data, wherein the target attribute data is one or more of the real-time logistics trajectory data, and one target attribute data corresponds to one preset dynamic field; A filling module, configured to fill the dynamic fields in the target copy template accordingly based on the target attribute data and the current service scenario, so as to obtain the notification copy of the current service scenario; The notification copy sending module is used to send the notification copy to the target object.
9. An electronic device, characterized in that: The electronic device includes a memory and at least one processor, wherein the memory stores instructions; the at least one processor calls the instructions in the memory so that the electronic device executes each step of the logistics order processing method as claimed in claims 1-7.
10. A computer-readable storage medium having instructions stored thereon, characterized in that: When the instructions are executed by the processor, the various steps of the logistics order processing method as described in any one of claims 1-7 are implemented.