Object processing method, apparatus, device, and storage medium

Abstract

The application provides an object processing method and device, equipment and storage medium. It relates to the technical field of data processing. The method comprises: in response to an end instruction of a passenger for a travel task, obtaining a plurality of first service resources corresponding to a driver, the types of the first service resources and attribute information of the driver; determining a target service resource according to the attribute information, the first service resources and the corresponding types; calling a service interface of the target service resource to perform transfer processing on a first object value of a first object corresponding to the passenger, so that the first object value is directly routed from a resource node corresponding to the passenger to a resource receiving node corresponding to the driver; obtaining historical behavior information of the driver, and determining an object processing strategy according to the historical behavior information and the attribute information; executing the object processing strategy and performing deduction processing on a second object value of a second object corresponding to the driver through a deduction channel independent of the transfer processing. The reliability of object processing is improved.

Description

Technical Field

[0001] This application relates to the field of data processing technology, and in particular to an object processing method, apparatus, device and storage medium. Background Technology

[0002] In multi-stage, multi-participant business processes, the transfer of business objects between passengers and drivers has become a common requirement. To improve user satisfaction, this business object needs to be processed with finer detail.

[0003] In related technologies, a unified collection and redistribution approach is generally used for object processing. That is, the passenger's business objects are first transferred to the collection node on the server side, and then the server distributes the business objects from the collection node to the receiving node corresponding to the driver.

[0004] However, in the above process, business objects need to be transferred through the server's aggregation node, which causes a delay in the arrival of business objects at the receiving node, and the retention of them on the server may pose compliance risks, resulting in low reliability of object processing. Summary of the Invention

[0005] This application provides an object processing method, apparatus, device, and storage medium to solve the technical problem of low reliability in object processing.

[0006] In a first aspect, embodiments of this application provide an object processing method, including:

[0007] In response to the passenger's instruction to end the trip, obtain multiple primary service resources corresponding to the driver, the type of each primary service resource, and the driver's attribute information;

[0008] The target service resource is determined based on the attribute information, each primary service resource, and its corresponding type.

[0009] Call the service interface of the target service resource to transfer the value of the first object of the first object corresponding to the passenger, so that the value of the first object is directly routed from the resource node corresponding to the passenger to the resource receiving node corresponding to the driver.

[0010] Obtain the driver's historical behavior information, and determine the object processing strategy based on the historical behavior information and attribute information;

[0011] The object processing strategy is executed, and the second object value of the second object corresponding to the driver is deducted through a deduction channel independent of the transfer processing.

[0012] In one possible implementation, the target service resource is determined based on attribute information, each first service resource, and its corresponding type, including:

[0013] Based on attribute information, each first service resource and its corresponding type, determine the driver's activity level and object loss information when using each first service resource. The object loss information is the object loss value generated by the first service resource during object processing.

[0014] Based on activity level, object loss information, and the type of each primary service resource, the target service resource is determined.

[0015] In one possible implementation, the target service resource is determined based on activity level, object loss information, and the type of each first service resource, including:

[0016] Based on activity level, a first weight is determined. The first weight is used to indicate the degree of influence of activity level on object processing of the first service resource.

[0017] Based on the object loss information, a second weight is determined. The second weight is used to indicate the degree of impact of the object loss information on the object processing of the first service resource.

[0018] The third weight is determined based on the type of each primary service resource;

[0019] Based on activity level, first weight, object loss information, second weight, and third weight, a first parameter is determined, and based on the first parameter, a target service resource is determined, wherein the first parameter of the target service resource is greater than a first threshold.

[0020] In one possible implementation, determining the object processing strategy based on historical behavior information and attribute information includes:

[0021] Based on the attribute information, the driver's credit parameters are determined. These credit parameters are used to indicate the driver's creditworthiness.

[0022] Based on the pre-trained language model, historical behavior information, and credit parameters, an object processing strategy is obtained.

[0023] In one possible implementation, an object processing strategy is obtained based on a pre-trained language model, historical behavior information, and credit parameters, including:

[0024] Temporal features are extracted from historical behavioral information to obtain behavioral feature sequences;

[0025] The behavioral feature sequence and credit parameters are transformed to obtain a text sequence, which is a semantic description of the driver's resource fluctuation characteristics at different time periods.

[0026] The text sequence is input into a pre-trained language model to obtain risk warning information, which includes the probability of failure to deduct the second object value in the future time period.

[0027] Based on the risk warning information, determine the target handling strategy.

[0028] In one possible implementation, determining the object handling strategy based on the risk warning information includes:

[0029] When the risk warning information indicates that the probability of failure to deduct is greater than or equal to the second threshold, the object processing strategy is determined to be to periodically deduct the first reduction from the second object value;

[0030] When the risk warning information indicates that the probability of failure to deduct is less than the second threshold, the object processing strategy is to determine the second reduction corresponding to the travel task and deduct the second reduction from the second object value.

[0031] In one possible implementation, periodically subtracting the first deduction from the second object value is obtained through the following steps:

[0032] Get the third reduction corresponding to each travel task within multiple historical preset periods, where the preset periods include the start time and the end time;

[0033] Based on multiple third reductions, determine the first reduction to be deducted in the current preset period;

[0034] When the current time is the start time of the preset period, the first deduction is subtracted from the second object value.

[0035] Secondly, embodiments of this application provide an object processing apparatus, including: an acquisition module, a first determination module, a transfer module, a second determination module, and a deduction module, wherein:

[0036] The acquisition module is used to respond to the passenger's command to end the travel task and acquire multiple first service resources corresponding to the driver, the type of each first service resource, and the driver's attribute information.

[0037] The first determination module is used to determine the target service resource based on attribute information, each first service resource and its corresponding type;

[0038] The transfer module is used to call the service interface of the target service resource to transfer the first object value of the first object corresponding to the passenger, so that the first object value is directly routed from the resource node corresponding to the passenger to the resource receiving node corresponding to the driver.

[0039] The second determination module is used to acquire the driver's historical behavior information and determine the object processing strategy based on the historical behavior information and attribute information.

[0040] The deduction module is used to execute the object processing strategy and deduct the second object value of the second object corresponding to the driver through a deduction channel independent of the transfer processing.

[0041] In one possible implementation, the first determining module is specifically used for:

[0042] Based on attribute information, each first service resource and its corresponding type, determine the driver's activity level and object loss information when using each first service resource. The object loss information is the object loss value generated by the first service resource during object processing.

[0043] Based on activity level, object loss information, and the type of each primary service resource, the target service resource is determined.

[0044] In one possible implementation, the first determining module is specifically used for:

[0045] Based on activity level, a first weight is determined. The first weight is used to indicate the degree of influence of activity level on object processing of the first service resource.

[0046] Based on the object loss information, a second weight is determined. The second weight is used to indicate the degree of impact of the object loss information on the object processing of the first service resource.

[0047] The third weight is determined based on the type of each primary service resource;

[0048] Based on activity level, first weight, object loss information, second weight, and third weight, a first parameter is determined, and based on the first parameter, a target service resource is determined, wherein the first parameter of the target service resource is greater than a first threshold.

[0049] In one possible implementation, the second determining module is specifically used for:

[0050] Based on the attribute information, the driver's credit parameters are determined. These credit parameters are used to indicate the driver's creditworthiness.

[0051] Based on the pre-trained language model, historical behavior information, and credit parameters, an object processing strategy is obtained.

[0052] In one possible implementation, the second determining module is specifically used for:

[0053] Temporal features are extracted from historical behavioral information to obtain behavioral feature sequences;

[0054] The behavioral feature sequence and credit parameters are transformed to obtain a text sequence, which is a semantic description of the driver's resource fluctuation characteristics at different time periods.

[0055] The text sequence is input into a pre-trained language model to obtain risk warning information, which includes the probability of failure to deduct the second object value in the future time period.

[0056] Based on the risk warning information, determine the target handling strategy.

[0057] In one possible implementation, the second determining module is specifically used for:

[0058] When the risk warning information indicates that the probability of failure to deduct is greater than or equal to the second threshold, the object processing strategy is determined to be to periodically deduct the first reduction from the second object value;

[0059] When the risk warning information indicates that the probability of failure to deduct is less than the second threshold, the object processing strategy is to determine the second reduction corresponding to the travel task and deduct the second reduction from the second object value.

[0060] In one possible implementation, periodically subtracting the first deduction from the second object value is obtained through the following steps:

[0061] Get the third reduction corresponding to each travel task within multiple historical preset periods, where the preset periods include the start time and the end time;

[0062] Based on multiple third reductions, determine the first reduction to be deducted in the current preset period;

[0063] When the current time is the start time of the preset period, the first deduction is subtracted from the second object value.

[0064] Thirdly, embodiments of this application provide an electronic device, including: a memory and a processor;

[0065] The memory stores instructions that the computer executes;

[0066] The processor executes computer execution instructions stored in memory, causing the processor to perform the first aspect and / or various possible implementations of the first aspect as described above.

[0067] Fourthly, embodiments of this application provide a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, are used to implement the first aspect and / or various possible implementations of the first aspect.

[0068] Fifthly, embodiments of this application provide a computer program product, including a computer program that, when executed by a processor, implements the first aspect and / or various possible implementations of the first aspect.

[0069] The object processing method, apparatus, device, and storage medium provided in this application embodiment, in response to a passenger's end instruction for a travel task, acquires multiple first service resources corresponding to the driver, the type of each first service resource, and the driver's attribute information; determines a target service resource based on the attribute information, each first service resource, and its corresponding type; calls the service interface of the target service resource to perform transfer processing on the first object value of the first object corresponding to the passenger, so that the first object value is directly routed from the resource node corresponding to the passenger to the resource receiving node corresponding to the driver; acquires the driver's historical behavior information, and determines an object processing strategy based on the historical behavior information and attribute information; executes the object processing strategy, and performs deduction processing on the second object value of the second object corresponding to the driver through a deduction channel independent of the transfer processing. In the above method, the electronic device can dynamically determine the target service resource by performing differential analysis on the type and attribute information of multiple first service resources corresponding to the driver. This allows the first object value to be directly routed from the resource node corresponding to the passenger to the resource receiving node corresponding to the driver. Furthermore, the second object value is deducted through a deduction channel independent of this transfer process. This avoids the problem of business objects and technical service objects being mixed up and unable to be collected independently due to the business object being transferred through the collection node of the electronic device. It can achieve the separation of the transfer process and the deduction process, and complete the independent collection of technical service objects without the electronic device participating in the collection and distribution of business objects. This ensures both the directness and timeliness of the transfer of the first object value and the independence of the deduction of the second object value, thereby improving the reliability of object processing. Attached Figure Description

[0070] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0071] Figure 1 This application provides an illustration of the application scenario.

[0072] Figure 2 A schematic diagram illustrating the process of an object processing method provided in this application;

[0073] Figure 3 A schematic diagram illustrating the process of object value transfer in the prior art provided in this application;

[0074] Figure 4 A schematic diagram illustrating the process of object value transfer in this solution provided for this application;

[0075] Figure 5 A schematic diagram of the timing scheme provided in this application;

[0076] Figure 6 A schematic diagram illustrating the process of determining the target service resources provided for this application;

[0077] Figure 7 A schematic diagram illustrating the process of determining the object processing strategy provided in this application;

[0078] Figure 8 A schematic diagram showing the timing comparison of the object processing strategies provided in this application;

[0079] Figure 9 A schematic diagram illustrating another object processing method provided in this application;

[0080] Figure 10 A schematic diagram of the display interface of the first terminal device provided in this application;

[0081] Figure 11 A schematic diagram of the display interface of the second terminal device provided in this application;

[0082] Figure 12 A schematic diagram of the structure of an object processing device provided in this application;

[0083] Figure 13 A schematic diagram of the structure of the electronic device provided in this application.

[0084] The accompanying drawings illustrate specific embodiments of this application, which will be described in more detail below. These drawings and descriptions are not intended to limit the scope of the concept in any way, but rather to illustrate the concept of this application to those skilled in the art through reference to particular embodiments. Detailed Implementation

[0085] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0086] The collection, storage, use, processing, transmission, provision, and disclosure of financial data or user data involved in the technical solution of this application all comply with the provisions of relevant laws and regulations and do not violate public order and good morals.

[0087] It should be noted that in the embodiments of this application, certain software, components, models and other existing solutions in the industry may be mentioned. These should be regarded as exemplary and are only intended to illustrate the feasibility of implementing the technical solution of this application. However, it does not mean that the applicant has used or necessarily used the solution.

[0088] Figure 1The application scenario diagram provided in this application is as follows: Figure 1 As shown, it includes an electronic device, a first terminal device, and a second terminal device, wherein the first terminal device is a passenger-side terminal device, and the second terminal device is a driver-side terminal device.

[0089] The electronic device can communicate with both the first terminal device and the second terminal device. The electronic device can receive instructions from the first terminal device and trigger communication between the first terminal device and the second terminal device based on the received instructions. That is, the first terminal device can directly perform object processing and other operations with the second terminal device. Furthermore, the electronic device can also perform object processing operations with the second terminal device, ensuring that the object processing link between the electronic device and the second terminal device is independent of the object processing link between the first terminal device and the second terminal device. This separates the link between the transfer processing of the first object value and the deduction processing of the second object value, improving the reliability of object processing.

[0090] Among them, electronic devices can be servers, computers, or other devices with data processing capabilities, and terminal devices can be servers, computers, or other devices.

[0091] Based on the above scenarios, it is clear that existing technologies generally employ a unified collection and redistribution approach for object processing. This involves first transferring passenger business objects to a server-side collection node, and then the server distributing these objects from the collection node to the driver's corresponding receiving node. However, in this process, the business objects need to pass through the server-side collection node, causing a delay in their arrival at the receiving node. Furthermore, retaining these objects on the server side may pose compliance risks, resulting in low reliability in object processing.

[0092] The object processing method, apparatus, device, and storage medium provided in this application obtain multiple first service resources corresponding to the driver, the type of each first service resource, and the attribute information of the driver, determine the target service resource, and call its service interface, so that the first object value is directly routed from the resource node corresponding to the passenger to the resource receiving node corresponding to the driver, and the second object value corresponding to the driver is deducted through a deduction channel independent of the transfer processing. In the above method, electronic devices can dynamically select target service resources by performing differential analysis on the type and attribute information of multiple first service resources, realizing adaptive routing of the transfer processing path. This eliminates the intermediate link of the platform-side collection node, thereby eliminating compliance risks caused by service object retention at the architectural level and improving the resource flow efficiency of service providers. Furthermore, electronic devices can perform deduction processing through a deduction channel independent of the transfer processing, placing the transfer of the first object value and the deduction of the second object value on two independent processing links. This solves the problem in existing technologies where business objects and technical service objects are mixed up and cannot be collected independently due to the transfer of business objects through the collection node. This method does not require electronic devices to participate in the collection and distribution of business objects, avoiding the retention of business objects on electronic devices and improving the reliability of object processing. Moreover, this method is applicable to different types of service resources and service scenarios, enhancing the versatility and scalability of the solution. While improving the security of object processing, it significantly improves the reliability of independently collecting technical service objects.

[0093] The technical solution of this application and how it solves the above-mentioned technical problems will be described in detail below with specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments. The embodiments of this application will be described below with reference to the accompanying drawings.

[0094] Figure 2 A schematic diagram illustrating the process of an object processing method provided in this application, such as... Figure 2 As shown, the method includes:

[0095] S201. In response to the passenger's instruction to end the travel task, obtain multiple first service resources corresponding to the driver, the type of each first service resource, and the driver's attribute information.

[0096] The execution subject in this application embodiment can be an electronic device or an object processing device disposed in an electronic device. The object processing device can be implemented by software or by a combination of software and hardware. The electronic device can be a terminal device or a server.

[0097] A travel task can refer to a passenger's journey from origin to destination, generated by an electronic device based on a ride-hailing request sent by the passenger through a first terminal device. This travel task includes information such as passenger information, driver information, origin and destination, and an estimated value for a first object.

[0098] Specifically, when generating this travel task, the electronic device does not generate a merge transfer instruction to instruct the passenger to transfer the object to the electronic device; that is, the electronic device does not create a processing document for the passenger to transfer the business object to the electronic device.

[0099] The end command is used to indicate that the trip service corresponding to the travel task has been completed. It can be triggered by the passenger through the first terminal device, by the driver through the second terminal device, or by the electronic device automatically detecting when the trip has reached the destination based on the location information.

[0100] The first service resource can refer to the service channel that the driver pre-configures in his electronic device to receive the business objects transferred by passengers, such as the receiving carriers provided by different service providers bound to the driver.

[0101] The first type of service resource can refer to the category identifier of the service channel, used to distinguish different service channels. For example, the first type of service resource corresponds to service provider A, and the second type of service resource corresponds to service provider B.

[0102] Attribute information can refer to the profile data submitted by the driver when registering in the electronic device, as well as the usage data associated with each primary service resource, including but not limited to the driver's registration information, credit rating information, and usage frequency information of each primary service resource.

[0103] In some embodiments, obtaining the multiple first service resources corresponding to the driver, the type of each first service resource, and the driver's attribute information can be achieved in the following way: When the driver registers for the first time, the electronic device receives a binding request for at least one first service resource submitted by the driver through a second terminal device. The binding request carries the identifier and type information of the first service resource, and the electronic device associates and stores the first service resource with the driver. At the same time, the electronic device records the driver's historical operation data during the use of each first service resource, and generates the driver's attribute information based on the historical operation data.

[0104] In some embodiments, at the start of a trip, the electronic device receives a ride-hailing request sent by a passenger through a first terminal device. This request includes passenger information, origin and destination information, etc. The electronic device matches a suitable driver based on the ride-hailing request and generates a trip task. During the generation of the trip task, the electronic device only creates information documents for recording the trip service and does not create a merge transfer instruction to instruct the passenger to transfer the service object to the electronic device.

[0105] S202. Determine the target service resource based on the attribute information, each first service resource, and its corresponding type.

[0106] The target service resource can refer to the specific service channel selected from the multiple primary service resources corresponding to the driver, which is used to receive passenger transfers in this travel task.

[0107] In some embodiments, the target service resource can be determined as follows: the electronic device pre-stores a mapping table between the type and priority of each first service resource, determines the priority order of each first service resource according to the mapping table, and determines the first service resource with the highest priority as the target service resource. For example, the electronic device can statistically analyze the success rate of each type of service resource based on historical data, set the type with the highest success rate as high priority, and directly select the first service resource corresponding to that type as the target service resource at the end of each travel task.

[0108] Optionally, the electronic device can also improve the retrieval efficiency of target service resources through a caching mechanism: After initially identifying a driver's target service resource, the electronic device caches the identifier of the target service resource in the cache area corresponding to that driver and sets a cache validity period. If the device receives an end command for the driver's corresponding travel task again within the cache validity period, it directly reads the identifier of the target service resource from the cache, reducing redundant calculation overhead. When the cache expires or the target service resource becomes unavailable, the determination logic is re-executed.

[0109] S203. Call the service interface of the target service resource to transfer the first object value of the first object corresponding to the passenger, so that the first object value is directly routed from the resource node corresponding to the passenger to the resource receiving node corresponding to the driver.

[0110] The service interface is used for data interaction between electronic devices and the service provider system corresponding to the target service resource to initiate a transfer request for the business object.

[0111] The first object can refer to the object storage carrier corresponding to the passenger in the electronic device, which is used to store or pay out business objects.

[0112] The first object value can refer to the numerical value of the business object that the passenger needs to transfer to the driver, which corresponds to this travel task, such as the output value corresponding to this trip.

[0113] A resource node can refer to the storage location of the first object corresponding to a passenger, such as the object storage carrier of the passenger.

[0114] The resource receiving node can refer to the receiving location bound to the first service resource corresponding to the driver, such as the receiving carrier registered by the driver through the service provider.

[0115] In some embodiments, to avoid the first object value passing through the collection node of the electronic device during the transfer process, the risk of the electronic device forming a business object collection is eliminated, while enabling the driver to receive the first object value immediately without waiting for the processing cycle of the electronic device.

[0116] Therefore, the specific implementation process of this solution is as follows: When the trip ends, the electronic device pushes a transfer page to the passenger's first terminal device. The recipient information configured in this transfer page is the identifier of the target service resource corresponding to the driver, that is, the recipient is the driver himself, not the electronic device. After the passenger confirms through this transfer page, the first object value is directly transferred from the resource node corresponding to the passenger to the resource receiving node corresponding to the driver. No node of the electronic device participates in the transfer of the first object value.

[0117] In this way, the transfer link of the first object value is completely isolated from the electronic device, which avoids the risk of the electronic device engaging in the transfer and processing of business objects without permission from the system design level, while improving the timeliness of the driver receiving the first object value.

[0118] Below, through Figure 3 and Figure 4 This paper provides a detailed explanation of the transfer methods of the first object value and the second object value in the existing technology and this solution.

[0119] Figure 3 The diagram provided in this application illustrates the process of object value transfer in the prior art. Figure 4 A schematic diagram illustrating the process of object value transfer in the scheme provided in this application.

[0120] Please see Figure 3 In existing technology, the flow of the first object value is as follows: the passenger first transfers the first object value to the collection node of the electronic device (which can be understood as a service platform). After the electronic device completes the collection, it separates the second object value from the first object value and stores it, and then transfers the remaining first object value to the driver's receiving node. In this process, the first object value and the second object value belong to the same flow link and both need to be processed through the collection node of the electronic device.

[0121] Please see Figure 4 In this scheme, the flow of the first object value is divided into two independent links: the first link routes the first object value directly from the resource node corresponding to the passenger to the resource receiving node corresponding to the driver, without passing through the collection node of the electronic device; the second link involves the electronic device deducting the second object value from the second object corresponding to the driver through a deduction channel independent of the first link, and transferring the second object value to the collection node of the electronic device. The first and second links are independent of each other at the object level and do not affect each other.

[0122] S204. Obtain the driver's historical behavior information, and determine the object processing strategy based on the historical behavior information and attribute information.

[0123] Historical behavior information can refer to the operation records related to business objects generated by the driver's historical travel tasks completed in electronic devices.

[0124] For example, historical behavior information may include, but is not limited to, historical transfer success records, historical deduction success records, historical deduction failure records, and fluctuation data of business objects in object storage carriers.

[0125] The object processing strategy is used to guide the electronic device on how and when to deduct the second object value corresponding to the driver.

[0126] In some embodiments, historical behavior information can be obtained in the following way: After each trip is completed, the electronic device records the transfer result of the first object value corresponding to that trip, as well as the execution result of subsequent deduction processing, and stores the above results in association with the driver to form a historical behavior dataset of the driver. When it is necessary to determine the object processing strategy, the electronic device extracts data within a preset time window from the historical behavior dataset as historical behavior information.

[0127] In some embodiments, the electronic device can adopt a preset rule matching mode, pre-configure multiple sets of standard object processing strategies, and set corresponding attribute thresholds and behavior thresholds for each strategy; after obtaining the driver's historical behavior information and attribute information, compare each indicator with the threshold conditions of each strategy one by one, and match the standard strategy that meets the conditions as the current driver's object processing strategy; this method does not require complex model reasoning, and can complete strategy matching only through rule comparison, which is simple in logic, stable in operation, and can quickly complete strategy generation.

[0128] In some embodiments, the electronic device classifies drivers into different credit levels based on credit rating information in the driver's attribute information and presets corresponding processing strategies for different credit levels. For example, when the credit level is level one, the processing strategy is determined to be strategy one, that is, deduction is executed immediately after each trip; when the credit level is level two, the processing strategy is determined to be strategy two, that is, deduction is executed uniformly within a preset fixed time period. This method does not require complex model calculations, is simple to implement, and has a fast response speed.

[0129] Optionally, the electronic device can also determine the object processing strategy based on the driver's manually selected strategy preferences. For example, during registration or use, the driver selects one of several candidate strategies provided by the electronic device as the default strategy through a second terminal device. The electronic device then directly calls this default strategy to perform the deduction processing after each trip.

[0130] S205. Execute the object processing strategy and deduct the second object value of the second object corresponding to the driver through a deduction channel independent of the transfer processing.

[0131] A deduction channel can refer to a dedicated link established between the electronic device and the driver for performing the deduction of a second object value. This deduction channel is independent of the transfer processing link in S203; that is, the establishment and execution of the deduction channel do not depend on the completion status of the transfer processing, and the execution result of the transfer processing does not affect the triggering logic of the deduction channel. This deduction channel is established based on a resource adjustment authorization certificate pre-signed by the driver.

[0132] The second object can refer to the object storage carrier in the driver's electronic device that is used to deduct the technical service object. The receiving carrier corresponding to the second object and the first service resource can be the same carrier; that is, the carrier in which the driver receives the first object value and the carrier used to deduct the second object value are the same carrier.

[0133] The second object value can refer to the numerical value of the business object that can be deducted from the second object, such as the available object value in the driver's object storage carrier.

[0134] In some embodiments, the electronic device can obtain an authorization credential returned by the service provider and bind and store the authorization credential with the driver. This authorization credential authorizes the electronic device to deduct a preset value from the driver's second object through the deduction channel when preset conditions are met, without requiring manual confirmation from the driver each time.

[0135] After each trip, the electronic device, according to the determined object processing strategy, calls the service provider's deduction execution interface, passing in parameters such as the authorization certificate, the identifier of this trip, and the deduction value. Based on the authorization certificate, the service provider deducts the corresponding second object value from the driver's second object and transfers the deducted second object value to the corresponding aggregation node of the electronic device. The result of the deduction execution is returned to the electronic device in real time. If the deduction execution fails, the electronic device records the deduction failure status and the reason for the failure; this deduction failure status does not affect the completed transfer processing of the first object value in S203.

[0136] In some embodiments, the transfer processing of the first object value and the subtraction processing of the second object value are independent of each other in timing. Specifically, this includes two timing methods: serial and parallel.

[0137] The specific process of the serial method is as follows: The electronic device first performs the transfer processing of the first object value. After receiving the callback notification that the transfer processing is successful, it then triggers the deduction processing of the second object value. That is, the routing of the first object value from the resource node corresponding to the passenger to the resource receiving node corresponding to the driver is completed first. After confirming that the transfer is completed, the deduction operation is performed through the deduction channel.

[0138] The specific process of the parallel method is as follows: the electronic device simultaneously triggers the transfer processing of the first object value and the deduction processing of the second object value. The two processing instructions are executed by different service interfaces and do not depend on each other.

[0139] Regardless of the timing method used, the execution result of the deduction process for the second object value does not affect the transfer process already completed for the first object value. Even if the deduction process fails, the first object value remains in the resource receiving node corresponding to the driver. The electronic device only records the deduction failure status and re-triggers the deduction process after a preset time, or switches to another method to continue completing the deduction.

[0140] Below, through Figure 5 The serial timing method and the parallel timing method of this application are described in detail.

[0141] Figure 5 A schematic diagram illustrating the timing scheme provided in this application. Please refer to [link / reference]. Figure 5 The first process is the authorization and signing process: this is a preliminary step and is independent of the trip task processing process in terms of timing. The driver submits an authorization and signing application to the electronic device through a second terminal device. After the electronic device completes the information verification and agreement activation processing, it stores the signed agreement. After this authorization and signing process is completed, it can support the deduction processing for subsequent trip tasks without having to be repeated with each single trip task.

[0142] The second process is the travel task processing process, which includes two independent processing links. The first link is the transfer processing link for the first object value. When the passenger initiates the transfer of the first object value, after the electronic device completes the processing scheduling, the first object value is directly routed from the resource node corresponding to the passenger to the resource receiving node corresponding to the driver. The second link is the deduction processing link for the second object value. The electronic device deducts the second object value from the second object corresponding to the driver through an independent deduction channel and transfers the deducted second object value to the electronic device's aggregation node. The triggering timing and execution result of the second link are decoupled from the first link; the two links belong to different processing channels and execution nodes.

[0143] The overall architecture separates the authorization signing and travel task processing in a sequential manner, and ensures the independence of the transfer processing link and the deduction processing link, thereby achieving the separation of the link between the first object value and the second object value at the processing flow level.

[0144] The object processing method, apparatus, device, and storage medium provided in this application obtain multiple first service resources corresponding to the driver, the type of each first service resource, and the driver's attribute information. It then determines the target service resource and calls its service interface, enabling the first object value to be directly routed from the resource node corresponding to the passenger to the resource receiving node corresponding to the driver. Furthermore, it deducts the second object value corresponding to the driver through a deduction channel independent of the transfer processing. In this method, the electronic device can dynamically determine the target service resource by performing differential analysis on the type and attribute information of the multiple first service resources corresponding to the driver. This allows the first object value to be directly routed from the resource node corresponding to the passenger to the resource receiving node corresponding to the driver. The second object value is then deducted through a deduction channel independent of the transfer processing. This avoids the problem of business objects and technical service objects being mixed up and unable to be independently collected due to the business object being transferred through the electronic device's collection node. It achieves separation of the transfer processing and deduction processing links, enabling independent collection of technical service objects without the electronic device's involvement in the collection and distribution of business objects. This ensures both the directness and timeliness of the first object value transfer and the independence of the second object value deduction, improving the reliability of object processing.

[0145] Figure 6 A schematic diagram illustrating the process of determining the target service resources provided in this application, as shown below. Figure 6 As shown, the method includes:

[0146] S601. Based on the attribute information, each first service resource and its corresponding type, determine the driver's activity level and object loss information when using each first service resource.

[0147] The object loss information refers to the object loss value generated by the first service resource during object processing. This can be understood as the processing overhead deducted by the service provider corresponding to a particular first service resource when a driver uses that first service resource to receive a first object value. For example, a certain type of service resource may charge a certain object loss value proportionally when processing a single object transfer.

[0148] Activity level refers to the frequency with which a driver uses each primary service resource, reflecting the driver's dependence on and preference for a particular service resource. Higher activity level indicates that the driver is more inclined to use that service resource for object reception.

[0149] In some embodiments, when calculating activity level, the electronic device can obtain historical operation records of the driver's use of each first service resource within a preset time period, summarize data such as the number of times each first service resource was used, the frequency of use, and the time of the most recent use, and calculate the activity level of each first service resource based on the above data. For example, the number of times of use and the frequency of use can be normalized and then weighted and summed to obtain the activity level value.

[0150] In some embodiments, when calculating object loss information, the electronic information can query the loss parameters published by the service provider corresponding to each type of first service resource, and determine the object loss information of the first service resource by combining the parameters with preset loss calculation rules. For example, the electronic device can pre-set a mapping table between type and loss parameters. When it is necessary to determine object loss information, it can directly look up the corresponding loss parameters, i.e., the object loss value, according to the type of the first service resource.

[0151] S602. Based on the activity level, object loss information, and the type of each first service resource, determine the target service resource.

[0152] In some embodiments, the electronic device may determine the target service resource based on the following method, according to activity level, object loss information and the type of each first service resource: determining a first weight based on activity level; determining a second weight based on object loss information; determining a third weight based on the type of each first service resource; determining a first parameter based on activity level, first weight, object loss information, second weight and third weight, and determining the target service resource based on the first parameter, wherein the first parameter of the target service resource is greater than a first threshold.

[0153] The first weight is used to indicate the degree of influence of activity on the object processing of the first service resource. That is, the first weight can be understood as reflecting the importance of activity in the selection of the target service resource. For example, if the strategy tends to prioritize service resources frequently used by drivers, the first weight can be set higher (e.g., 0.8); conversely, if the reference value of activity is low, the first weight can be set lower (e.g., 0.3).

[0154] The second weight is used to indicate the degree of influence of object loss information on object processing of the first service resource. In other words, the second weight reflects the importance of the object loss value in the selection of the target service resource. For example, if the strategy prefers to prioritize service resources with lower loss to save processing overhead, the second weight can be set higher (e.g., 0.7).

[0155] The third weight can be understood as an adjustment coefficient determined based on the type of the primary service resource, used to reflect the differentiated impact of different types of service resources in the overall evaluation. For example, certain types of service resources have advantages in stability or coverage, and can be given additional preferential adjustments through the third weight.

[0156] The first parameter can refer to a score used to evaluate the overall suitability of each first service resource, which is obtained by weighting the activity level, object loss information, and type. A higher first parameter indicates that the first service resource is more suitable to be selected as the target service resource under the current conditions.

[0157] The first threshold can refer to the scoring criteria used to screen target service resources. Only service resources whose first parameter is greater than this threshold can be included in the candidate range. This threshold can be preset based on historical experience data, or it can be dynamically adjusted by the electronic equipment according to actual operating conditions.

[0158] In some embodiments, the first weight can be determined by the electronic device analyzing the correlation between activity level and object transfer success rate based on historical usage data in the driver's attribute information, and determining the first weight based on this correlation. For example, if historical data shows that service resources with high activity levels also have a correspondingly high transfer success rate, then a higher first weight can be assigned to the activity level.

[0159] In some embodiments, the second weight can be determined as follows: the electronic device determines the importance of object loss information based on a preset loss control strategy and the value of the first object corresponding to the current travel task, and then determines the second weight. For example, when the value of the first object is large, the object loss value has a more significant impact on the final transferred object, and the second weight can be dynamically increased in this case.

[0160] In some embodiments, the third weight can be determined by the electronic device querying a preset mapping table between type and weight based on the type of each first service resource to obtain the third weight. This mapping table can be configured based on historical performance data of each type of service resource; for example, types with high transfer success rates and fast response times can be assigned higher third weights.

[0161] In some embodiments, after determining the weights, the electronic device can first perform dimensional unification processing on the activity level and object loss information, converting them to the same numerical range (e.g., a range of 0 to 1) to eliminate the influence of different dimensions on the calculation results. Then, by calculating the first product of activity level and the first weight, and the second product of object loss information and the second weight, the first product and the second product are added together to obtain a weighted sum. Finally, the weighted sum is multiplied by the third weight to obtain the first parameter.

[0162] In the above manner, the first and second weights control the contribution ratio of activity and object loss information in the summation, respectively, while the third weight, as an overall adjustment coefficient, can be amplified or reduced based on the type of service resources according to the summation result, reflecting the global impact of type on the comprehensive evaluation result.

[0163] In some embodiments, when determining a target service resource based on a first parameter, the electronic device calculates the first parameter corresponding to each first service resource and identifies first service resources whose first parameter is greater than a first threshold as candidate service resources. If there is only one candidate service resource, that candidate service resource is identified as the target service resource. If there are multiple candidate service resources, they are sorted from largest to smallest according to the first parameter, and the candidate service resource with the largest first parameter is identified as the target service resource. If the first parameter of all first service resources is not greater than the first threshold, the electronic device can select the first service resource with the largest first parameter as the target service resource, or push a prompt message to the driver so that the driver can manually select the target service resource.

[0164] By dynamically selecting target service resources, the success rate of transferring the first object value is significantly improved, reducing transfer failures caused by limitations of a single service resource. Simultaneously, optimizing the transfer path reduces object loss and enhances passenger flexibility during processing. Furthermore, the dynamic routing mechanism can adapt to the service resource configuration characteristics of different drivers, ensuring the versatility of the technical solution.

[0165] The object processing method, apparatus, device, and storage medium provided in this application determine the target service resource by quantitatively analyzing the activity and object loss information of multiple first service resources corresponding to the driver, and combining the type of each first service resource. In the above method, the electronic device can assign differentiated weights to activity, object loss information, and service resource type, and select the target service resource from multiple first service resources based on the weighted calculation of the first parameter. This avoids the problem of mismatch between the target service resource and the driver's actual usage caused by the use of fixed service resources or single selection rules in traditional methods. Furthermore, by incorporating activity, object loss information, and service resource type into a unified calculation framework, the accuracy and rationality of the target service resource selection are ensured. This improves the success rate of first object value transfer processing and provides reliable service resource guarantees for the execution of subsequent object processing strategies.

[0166] Based on any of the above embodiments, the following, in conjunction with Figure 7 The method for determining the object processing strategy is explained in detail.

[0167] Figure 7 A schematic diagram illustrating the process of determining the object processing strategy provided in this application. Please refer to [link / reference]. Figure 7 The method may include:

[0168] S701. Determine the driver's credit parameters based on the attribute information.

[0169] Among them, the credit parameter is used to indicate the driver's creditworthiness. It can be understood as a comprehensive quantitative evaluation of the driver's performance in object transfer and deduction processing in historical travel tasks. The higher the credit parameter, the higher the proportion of successful deduction processing in the driver's historical records, and the more abundant the object values ​​available for deduction in the second object.

[0170] In some embodiments, determining a driver's credit parameters can be achieved by the electronic device extracting data such as the driver's historical successful deduction count, historical failed deduction count, and historical fluctuation range of the second object value from attribute information, and calculating credit parameters according to preset credit assessment rules. For example, the historical deduction success rate (the ratio of successful deductions to total deductions) can be used as a credit parameter, or the deduction success rate can be obtained by weighted summation of the object value fluctuation stability. The credit parameter can be expressed in numerical form or as a discrete credit rating.

[0171] S702. Based on the pre-trained language model, historical behavior information, and credit parameters, obtain the object processing strategy.

[0172] A pre-trained language model can refer to a neural network model that has been pre-trained on a large amount of text data and has the ability to understand semantics and perform sequence analysis.

[0173] This model can perform semantic parsing on the input text sequence, extract the implicit patterns and rules, and output the corresponding prediction results. In this embodiment, the language model is used to analyze the resource fluctuation characteristics of drivers in different time periods and predict the probability of failure to deduct the second object value in future time periods.

[0174] In some embodiments, the electronic device may derive an object processing strategy based on a pre-trained language model, historical behavior information, and credit parameters as follows: extracting temporal features from historical behavior information to obtain a behavior feature sequence; converting the behavior feature sequence with the credit parameters to obtain a text sequence; inputting the text sequence into a pre-trained language model to obtain risk warning information, which includes the probability of failure to deduct the second object value in the future time period; and determining the object processing strategy based on the risk warning information.

[0175] A behavioral characteristic sequence can refer to a numerical sequence arranged chronologically, reflecting the changing patterns of object values ​​for a driver over multiple historical periods. This sequence includes information such as the driver's reception of the first object value, the deduction of the second object value, and the fluctuation trend of the object value within different time windows.

[0176] The text sequence is a semantic description of the driver's resource fluctuation characteristics at different times. It can be understood as converting the behavioral feature sequence and credit parameters, which are originally represented in numerical form, into a text description in natural language so that the language model can understand and process them. For example, the numerical value of "average daily value of the second object in the past 30 days" can be converted into a semantic expression such as "the value of the second object has been at a high level in the past 30 days".

[0177] Risk warning information refers to the prompts output by a language model after analyzing and issuing warnings about potential adverse situations that may occur to the driver in the future. This information is used to assist electronic devices in determining which object handling strategy to adopt.

[0178] The future time period can refer to the time period from the current moment to the next preset deduction time, such as the next deduction cycle or the end time of the next travel task.

[0179] The probability of deduction failure refers to the likelihood that, within a preset future time period, the electronic device will fail to complete the deduction operation due to insufficient second object values ​​when performing deduction processing on the driver's second object value. This probability value is predicted and output by the language model based on historical behavioral information and credit parameters.

[0180] In some embodiments, extracting temporal features from historical behavioral information to obtain a behavioral feature sequence can be achieved as follows: The electronic device segments the historical behavioral information according to a preset time window (e.g., daily), extracts key feature data within each time window, including the total amount of a first object value received, the total amount of a second object value deducted, the number of successful deductions, the number of failed deductions, and the remaining amount of the second object value at the end of the window. The above feature data is then arranged in chronological order to form a behavioral feature sequence.

[0181] In some embodiments, converting the behavioral feature sequence and credit parameters to obtain a text sequence can be achieved as follows: The electronic device uses a preset text template containing multiple fillable semantic fields, each corresponding to a feature in the behavioral feature sequence and a credit parameter. The electronic device matches the numerical values ​​in the behavioral feature sequence with preset semantic mapping rules, converting the numerical values ​​into corresponding semantic descriptive phrases. Then, the semantic descriptive phrases and credit parameters are filled into the text template to generate a complete text sequence. For example, numerical behavioral features can be converted into natural language descriptions such as "The driver's average value of the second object over the past 30 days is high, and the fluctuation range is low."

[0182] In some embodiments, the electronic device takes a text sequence as input, invokes a pre-trained language model, and the language model performs semantic encoding and pattern recognition on the text sequence, outputting a prediction result for a future time period after deducting the probability of failure. This prediction result can be output directly as a probability value, or it can be output as structured information containing probability values ​​and risk levels.

[0183] In some embodiments, the electronic device may determine the object processing strategy based on the risk warning information in the following manner: when the risk warning information indicates that the probability of deduction failure is greater than or equal to a second threshold, the object processing strategy is to periodically deduct a first reduction from the second object value; when the risk warning information indicates that the probability of deduction failure is less than the second threshold, the object processing strategy is to determine a second reduction corresponding to the travel task and deduct the second reduction from the second object value.

[0184] The second threshold can refer to a preset probability cutoff value used to distinguish between high-risk and low-risk scenarios. If the probability of failure to deduct is greater than or equal to the second threshold, it indicates a higher risk that the driver's second target value will be insufficient in the future; if the probability of failure to deduct is less than the second threshold, it indicates a lower risk. The second threshold can be set based on historical experience data or dynamically adjusted by the electronic device according to the overall deduction success rate target.

[0185] The first reduction can refer to the object value of the technical service object deducted by the electronic device from the driver's second object value in each preset cycle under a periodic deduction strategy. This object value can be a fixed value or dynamically determined based on historical data from the previous cycle.

[0186] The second reduction can refer to the object value of the technical service object corresponding to the trip, which is deducted from the driver's second object value by the electronic device after each trip, under a single deduction strategy. This object value can be determined proportionally based on the first object value of the trip.

[0187] In some embodiments, periodically deducting the first reduction from the second object value is obtained through the following steps: obtaining the third reduction corresponding to each travel task within a plurality of historical preset periods, wherein the preset period includes a start time and an end time; determining the first reduction to be deducted in the current preset period based on the plurality of third reductions; and deducting the first reduction from the second object value when the current time is the start time of the preset period.

[0188] A preset period can refer to a time interval pre-set by an electronic device for periodically performing deduction processing, such as a calendar month or a settlement cycle.

[0189] The start time can refer to the beginning point of a preset cycle. When the current time is the start time, the electronic device triggers the deduction process for that cycle.

[0190] The termination time can refer to the end point of a preset cycle. This time is used to mark the end of the previous cycle, and the electronic device can begin calculating the relevant parameters for the next cycle after the termination time.

[0191] The third reduction can refer to the object value of the technical service object that should be deducted in a single trip within the previous preset period if a single deduction strategy is adopted.

[0192] In some embodiments, obtaining the third deduction corresponding to each travel task within the previous preset period can be achieved in the following way: At the end of each travel task within the previous preset period, the electronic device records the deduction value corresponding to that travel task as the third deduction, and stores the third deduction associated with the travel task identifier. When the first deduction needs to be determined in the current preset period, the electronic device queries the third deductions corresponding to all travel tasks within the previous preset period and summarizes them to form a third deduction set.

[0193] In some embodiments, determining the first reduction to be deducted in the current preset period based on a plurality of third reductions can be achieved in the following ways:

[0194] Method one is the trend prediction method. Specifically, the electronic device acquires third reduction data for multiple historical preset periods, analyzes the trend of the third reduction with each period, and predicts the first reduction for the current preset period based on this trend. For example, if the third reduction shows an upward trend, the first reduction is calculated by increasing the average value of the previous period by a preset percentage.

[0195] Method two is the model prediction method. Specifically, the electronic device inputs the third reduction sequence of multiple historical preset periods into a pre-trained prediction model to obtain the first reduction prediction value for the current preset period. This prediction model can be a time series prediction model or a regression model, which outputs prediction results by learning patterns from historical data.

[0196] In some embodiments, when the electronic device detects that the current time has reached the start time of a preset period, a deduction process is triggered. The electronic device calls the deduction execution interface, passing in parameters such as the authorization certificate, the identifier of the current period, and the first deduction, deducts the first deduction from the driver's second object value, and transfers the deducted first deduction to the electronic device's aggregation node.

[0197] In some embodiments, after the current trip is completed, the electronic device acquires a first object value corresponding to the trip and determines a second reduction based on a preset deduction ratio. For example, the preset deduction ratio is a preset percentage of the first object value; the first object value is multiplied by this preset percentage to obtain the second reduction. This preset percentage can be dynamically adjusted based on the driver's credit parameters; the higher the credit parameters, the lower the preset percentage can be.

[0198] After determining the second reduction, the electronic device calls the deduction execution interface, passing in the authorization credential, the identifier of this trip, and the second reduction. It deducts the second reduction from the driver's second object value and transfers the deducted second reduction to the electronic device's aggregation node. If the deduction is successful, the electronic device records the status of this deduction process as successful and stores the deduction result in association with this trip. If the deduction fails, the electronic device records the deduction failure status. This failure status does not affect the transfer processing of the first object value already completed in this trip. The electronic device can re-trigger the deduction process after a preset time or merge the deduction at the end of the next trip.

[0199] In some embodiments, the electronic device can also monitor and verify the driver's second object value before performing the deduction process. Specifically, this includes: before triggering the deduction process, the electronic device obtains the current available object value of the second object corresponding to the driver through an object value query interface provided by the service provider. The electronic device compares the current available object value with the first deduction. If the current available object value is greater than or equal to the sum of the first deduction and a preset verification benchmark value, the electronic device performs the deduction process normally. If the current available object value is less than the sum of the first deduction and the preset verification benchmark value but greater than the first deduction, the electronic device performs the deduction process and pushes a reminder message to the driver, prompting them to replenish the object value before the next cycle.

[0200] If the current available object value is less than the first reduction amount, the electronic device will temporarily suspend the deduction process, send a warning notification to the driver, and re-query and attempt the deduction after a preset delay. This preset verification benchmark value can be set according to the driver's historical object value fluctuations to ensure that the driver's second object still retains the basic object value after the deduction process, thus avoiding affecting the normal operation of subsequent travel tasks.

[0201] By monitoring the second object value of the driver's second object in real time, the risk of deduction failure can be identified in advance, reducing the problem of service collection failure due to insufficient second object value. Simultaneously, the early warning mechanism helps drivers proactively manage the liquidity of second object value, avoiding disruptions to order acceptance due to insufficient value. Furthermore, this mechanism reduces the reliance of electronic devices on retry processing or manual intervention after deduction failure, improving the system's automation level.

[0202] Below, through Figure 8 This application provides a detailed description of its object processing strategy.

[0203] Figure 8 A schematic diagram illustrating the timing comparison of the object processing strategies provided in this application. Please refer to... Figure 8 The object processing strategy of this application includes two methods, each corresponding to drivers with different risk levels.

[0204] like Figure 8 The upper section illustrates the periodic deduction strategy. This strategy uses a preset period (e.g., one month) as the time unit, deducting a first reduction amount at the beginning of the period. This first reduction amount is a fixed value corresponding to the preset period. Within each trip within the period, no separate deduction is performed; fluctuations in the number of trips and the first object value corresponding to each trip do not affect the first reduction amount within that period. The core characteristics of this strategy are a large single deduction amount, a low deduction frequency, and a fixed total amount for the technical service recipient. It is suitable for drivers with a high probability of deduction failure and ensures the certainty of the technical service recipient's payment.

[0205] like Figure 8 The lower section illustrates the single-trip deduction strategy. This strategy corresponds one-to-one with each trip, executing the deduction immediately after each trip, with the deduction frequency synchronized with the number of trips. The second reduction can be determined based on a preset ratio or a preset fixed value, depending on the first object value corresponding to that trip. The core features of this strategy are a direct correlation between the technical service object and the trip volume, a small single deduction value, and a high deduction frequency. It is suitable for drivers with a low probability of deduction failure and ensures that the deduction processing for the technical service object matches the driver's actual trip volume.

[0206] In summary, these two strategies correspond to differentiated processing methods in high-risk and low-risk scenarios, respectively. By adapting the deduction strategies to drivers with different risk levels, the reliability of the technical service recipients' collection is improved while also taking into account the liquidity of the driver's secondary object value.

[0207] The object processing method, apparatus, device, and storage medium provided in this application obtain credit parameters by performing credit assessment on the driver's attribute information, and combine this with a pre-trained language model to perform time-series analysis and risk prediction on historical behavior information to determine the object processing strategy. In this method, the electronic device can convert historical behavior information into a text sequence reflecting the driver's resource fluctuation characteristics at different times, and use the semantic understanding capability of the language model to predict the probability of failure to deduct the second object value in future periods. This avoids the problem of mismatch between the object processing strategy and the driver's actual resource situation caused by the use of fixed strategies or single rules in traditional methods. Furthermore, by comparing the probability of failure to deduction with a second threshold, a periodic deduction strategy is adopted in high-risk situations, and a single deduction strategy is adopted in low-risk situations, achieving dynamic adaptation of the object processing strategy. This ensures both the success rate of deduction processing in high-risk scenarios and the flexibility of deduction processing in low-risk scenarios. Based on improving the accuracy and reliability of the object processing strategy, it provides intelligent decision support for the independent collection of technical service objects.

[0208] Figure 9 A schematic diagram illustrating another object processing method provided in this application is shown below. Figure 9 As shown, the method includes:

[0209] S901. Receive the driver's registration request and verify the driver's business information.

[0210] Specifically, the driver submits a registration request to the electronic device via a second terminal, which includes the driver's business information. The electronic device verifies this information and, after confirming that the driver is qualified to undertake ride-hailing tasks, completes the driver's onboarding process.

[0211] S902. After verification, a corresponding object record carrier is established for the driver for subsequent object value recording and processing.

[0212] Specifically, after verification, the electronic device establishes an independent object record carrier for the driver. This object record carrier is used to record information such as the value of the first object value and the value of the second object value received by the driver, providing a data foundation for subsequent object value splitting and transfer processing.

[0213] S903: Receive travel requests from passengers, complete information matching between passengers and drivers, and generate travel tasks.

[0214] Specifically, passengers send a travel request to an electronic device via a primary terminal device, including passenger information, departure point, and destination. The electronic device then matches the travel request with available driver information to generate a travel assignment.

[0215] S904. After the trip is completed, the first object value of the first object corresponding to the passenger is transferred so that the first object value is directly routed from the resource node corresponding to the passenger to the resource receiving node corresponding to the driver.

[0216] Specifically, after the trip is completed, the electronic device calls the service interface of the target service resource and pushes a transfer page to the passenger's first terminal device. The recipient configured on this transfer page is the identifier of the target service resource corresponding to the driver; that is, the recipient is the driver, not the electronic device. After the passenger confirms through this transfer page, the first object value is directly transferred from the resource node corresponding to the passenger to the resource receiving node corresponding to the driver. During the transfer process, the electronic device does not participate in the flow of the first object value, and the first object value does not pass through any node of the electronic device.

[0217] S905, Subtract the value of the second object from the value of the second object.

[0218] Specifically, the electronic device deducts a second object value from the second object corresponding to the driver through a deduction channel independent of the transfer processing in S904, based on a determined object processing strategy. This deduction channel is established based on an authorization certificate pre-signed by the driver, and the triggering and execution of the deduction processing are independent of the transfer processing of the first object value.

[0219] In some embodiments, the electronic device may directly deduct the second object value from the second object corresponding to the driver and transfer the deducted second object value to the collection node of the electronic device, or it may first transfer the second object value from the first object value of the passenger to the electronic device and then transfer the remaining first object value to the resource receiving node corresponding to the driver.

[0220] S906. The retained value of the second object is included in the processing record.

[0221] Specifically, the electronic device will add the deducted second object value to its own processing record, thus completing the object processing flow corresponding to this travel task.

[0222] In some embodiments, after completing the transfer processing of the first object value and the deduction processing of the second object value, the electronic device records the associated travel task. The electronic device binds and stores the travel task identifier, the transfer processing identifier of the first object value, and the deduction processing identifier of the second object value, and records the status information of the deduction processing. By associating the transfer processing flow and the deduction processing flow with the travel task identifier respectively, it ensures that each processing link can be traced independently.

[0223] Furthermore, the electronic device can perform multi-dimensional verification of associated records. The electronic device acquires the value of the first object corresponding to the current travel task, the value of the first object actually transferred, and the value of the deducted second object, and compares these data. When the deviation between the value of the first object actually transferred and the value of the first object corresponding to the travel task exceeds a preset range, the electronic device generates an anomaly alert and triggers a review process. When the value of the deducted second object does not match the preset deduction rules, the electronic device marks the deduction record as abnormal and triggers a repair process.

[0224] In this way, the reliability and consistency of associated records can be improved through a multi-dimensional verification mechanism, reducing record anomalies caused by data deviations. Simultaneously, this mechanism enhances the monitoring capabilities of electronic devices over the processing chain, providing complete processing evidence for subsequent compliance reviews. This associated record is used solely for data recording and verification and does not alter the independence of the transfer processing chain and the deduction processing chain at the processing level.

[0225] Below, through Figure 10 This application provides a detailed description of the display interface of the passenger's first terminal device.

[0226] Figure 10 A schematic diagram of the display interface of the first terminal device provided in this application. Please refer to [link / reference]. Figure 10 The display interface of the first terminal device includes a travel task module, a first object value display module, a first object value receiving module, a service resource selection module, and a confirmation processing module.

[0227] The trip task module displays basic information about the trip, including the origin and destination of the trip and driver information.

[0228] The first object value display module is used to display the number of first object values ​​corresponding to this trip task and to indicate that the first object value will be directly routed to the resource receiving node corresponding to the driver.

[0229] The first object value receiving module is used to display the recipient information for this transfer process. The recipient is the driver himself, and a prompt message is attached, indicating that the first object value will be directly routed to the driver without going through electronic devices.

[0230] The service resource selection module displays multiple service resource options available to passengers, who can then select the target service resource for this transfer process.

[0231] The confirmation processing module is used for passengers to confirm this transfer process. In response to the passenger's operation on the confirmation processing module, the electronic device calls the service interface of the target service resource to perform transfer processing on the first object value, so that the first object value is directly routed from the resource node corresponding to the passenger to the resource receiving node corresponding to the driver.

[0232] Below, in conjunction with Figure 11 This application provides a detailed description of the display interface of the driver's second terminal device.

[0233] Figure 11 A schematic diagram of the display interface of the second terminal device provided in this application. Please refer to [link / reference]. Figure 11 The display interface of the second terminal device includes a first object value transfer module, a second object value deduction module, and a processing summary module.

[0234] The first object value transfer module is used to display the number of first object values ​​that are directly routed from the passenger to the driver's resource receiving node in this travel task, and to indicate that the transfer method of the first object value is direct routing, that is, the first object value is directly routed from the resource node corresponding to the passenger to the resource receiving node corresponding to the driver, without going through the collection node of the electronic device.

[0235] The second object value deduction module is used to display the deduction details of the second object value corresponding to this trip task, including the deduction ratio, the number of second object values ​​deducted, and to indicate that the deduction method is independent deduction, that is, the second object value is deducted from the second object corresponding to the driver through a deduction channel independent of the transfer processing.

[0236] The processing summary module is used to display the processing summary information for this trip, namely the difference between the amount transferred into the first object value and the amount deducted from the second object value.

[0237] The first object value transfer module and the second object value deduction module are displayed in separate areas on the display interface to visually distinguish the transfer processing link of the first object value and the deduction processing link of the second object value, intuitively reflecting the independence of the two processing links.

[0238] The object processing method, apparatus, device, and storage medium provided in this application achieve independent processing links in the object processing process by separating the transfer processing link of the first object value and the deduction processing link of the second object value. In the above method, the electronic device can cut off the mixing path of the first object value and the second object value from the source by not creating a merge transfer instruction when generating the travel task. Furthermore, by calling the service interface of the target service resource, the first object value is directly routed from the resource node corresponding to the passenger to the resource receiving node corresponding to the driver, without passing through the collection node of the electronic device. Moreover, the second object value of the driver is deducted through a deduction channel independent of the transfer processing, so that the collection of the second object value and the transfer of the first object value are in two independent processing links. This method solves the problem of object commingling caused by the first object value and the second object value being in the same processing link in the prior art. It can complete the independent collection of the second object value without the participation of electronic devices in the collection and distribution of the first object value. This ensures the real-time reception of the first object value by the driver and guarantees the independence of the deduction processing of the second object value. At the same time, it makes the processing records of the first object value and the second object value clearly separated. While improving the compliance and reliability of object processing, it enhances the adaptability of the processing link to different service resource types and driver behavior characteristics, and improves the overall efficiency of object processing.

[0239] Figure 12 This application provides a schematic diagram of the structure of an object processing device, as shown below. Figure 12 As shown, the object processing device 1200 provided in this embodiment includes: an acquisition module 1201, a first determination module 1202, a transfer module 1203, a second determination module 1204, and a deduction module 1205, wherein:

[0240] The acquisition module 1201 is used to acquire multiple first service resources corresponding to the driver, the type of each first service resource, and the driver's attribute information in response to the passenger's command to end the travel task.

[0241] The first determining module 1202 is used to determine the target service resource based on the attribute information, each first service resource and its corresponding type;

[0242] The transfer module 1203 is used to call the service interface of the target service resource to transfer the first object value of the first object corresponding to the passenger, so that the first object value is directly routed from the resource node corresponding to the passenger to the resource receiving node corresponding to the driver.

[0243] The second determining module 1204 is used to acquire the driver's historical behavior information and determine the object processing strategy based on the historical behavior information and attribute information.

[0244] The deduction module 1205 is used to execute the object processing strategy and deduct the second object value of the second object corresponding to the driver through a deduction channel independent of the transfer processing.

[0245] The object processing apparatus provided in this application embodiment can execute the technical solution shown in the above method embodiment. Its implementation principle and beneficial effects are similar, and will not be described again here.

[0246] In one possible implementation, the first determining module 1202 is specifically used for:

[0247] Based on attribute information, each first service resource and its corresponding type, determine the driver's activity level and object loss information when using each first service resource. The object loss information is the object loss value generated by the first service resource during object processing.

[0248] Based on activity level, object loss information, and the type of each primary service resource, the target service resource is determined.

[0249] In one possible implementation, the first determining module 1202 is specifically used for:

[0250] Based on activity level, a first weight is determined. The first weight is used to indicate the degree of influence of activity level on object processing of the first service resource.

[0251] Based on the object loss information, a second weight is determined. The second weight is used to indicate the degree of impact of the object loss information on the object processing of the first service resource.

[0252] The third weight is determined based on the type of each primary service resource;

[0253] Based on activity level, first weight, object loss information, second weight, and third weight, a first parameter is determined, and based on the first parameter, a target service resource is determined, wherein the first parameter of the target service resource is greater than a first threshold.

[0254] In one possible implementation, the second determining module 1204 is specifically used for:

[0255] Based on the attribute information, the driver's credit parameters are determined. These credit parameters are used to indicate the driver's creditworthiness.

[0256] Based on the pre-trained language model, historical behavior information, and credit parameters, an object processing strategy is obtained.

[0257] In one possible implementation, the second determining module 1204 is specifically used for:

[0258] Temporal features are extracted from historical behavioral information to obtain behavioral feature sequences;

[0259] The behavioral feature sequence and credit parameters are transformed to obtain a text sequence, which is a semantic description of the driver's resource fluctuation characteristics at different time periods.

[0260] The text sequence is input into a pre-trained language model to obtain risk warning information, which includes the probability of failure to deduct the second object value in the future time period.

[0261] Based on the risk warning information, determine the target handling strategy.

[0262] In one possible implementation, the second determining module 1204 is specifically used for:

[0263] When the risk warning information indicates that the probability of failure to deduct is greater than or equal to the second threshold, the object processing strategy is determined to be to periodically deduct the first reduction from the second object value;

[0264] When the risk warning information indicates that the probability of failure to deduct is less than the second threshold, the object processing strategy is to determine the second reduction corresponding to the travel task and deduct the second reduction from the second object value.

[0265] In one possible implementation, periodically subtracting the first deduction from the second object value is obtained through the following steps:

[0266] Get the third reduction corresponding to each travel task within multiple historical preset periods, where the preset periods include the start time and the end time;

[0267] Based on multiple third reductions, determine the first reduction to be deducted in the current preset period;

[0268] When the current time is the start time of the preset period, the first deduction is subtracted from the second object value.

[0269] The object processing device provided in this embodiment can execute the method provided in the above method embodiment. Its implementation principle and technical effect are similar, and will not be described in detail here.

[0270] Figure 13 A schematic diagram of the structure of the electronic device provided in this application. Figure 13 As shown, the electronic device 1300 provided in this embodiment includes at least one processor 1301 and a memory 1302. Optionally, the electronic device 1300 further includes a communication component 1303. The processor 1301, memory 1302, and communication component 1303 are connected via a bus.

[0271] In a specific implementation, at least one processor 1301 executes computer execution instructions stored in memory 1302, causing at least one processor 1301 to perform the above-described method.

[0272] The specific implementation process of processor 1301 can be found in the above method embodiments, and its implementation principle and technical effect are similar. It will not be repeated here.

[0273] In the above embodiments, it should be understood that the processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), etc. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the method disclosed in this invention can be directly implemented by a hardware processor, or implemented by a combination of hardware and software modules within the processor.

[0274] The memory may include random access memory (RAM) and may also include non-volatile memory (NVM), such as at least one disk storage device.

[0275] The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. Buses can be categorized as address buses, data buses, control buses, etc. For ease of illustration, the buses shown in the accompanying drawings are not limited to a single bus or a single type of bus.

[0276] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the above-described method.

[0277] This application also provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, implement the above-described method.

[0278] The aforementioned readable storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic storage, flash memory, magnetic disk, or optical disk. The readable storage medium can be any available medium accessible to a general-purpose or special-purpose computer.

[0279] An exemplary readable storage medium is coupled to a processor, enabling the processor to read information from and write information to the readable storage medium. Of course, the readable storage medium can also be a component of the processor. The processor and the readable storage medium can reside in an Application Specific Integrated Circuit (ASIC). Alternatively, the processor and the readable storage medium can exist as discrete components in the device.

[0280] The division of units is merely a logical functional division; in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be indirect coupling or communication connection through some interfaces, devices, or units, and may be electrical, mechanical, or other forms.

[0281] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0282] In addition, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0283] If a function is implemented as 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 this invention, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0284] Those skilled in the art will understand that all or part of the steps of the above-described method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When executed, the program performs the steps of the above-described method embodiments; and the aforementioned storage medium includes various media capable of storing program code, such as ROM, RAM, magnetic disks, or optical disks.

[0285] Finally, it should be noted that other embodiments of the invention will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This invention is intended to cover any variations, uses, or adaptations of the invention that follow the general principles of the invention and include common knowledge or customary techniques in the art not disclosed herein, and is not limited to the precise structures described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of the invention is limited only by the appended claims.

Claims

1. An object processing method, characterized in that, include: In response to the passenger's instruction to end the travel task, the system obtains multiple first service resources corresponding to the driver, the type of each first service resource, and the attribute information of the driver. The target service resource is determined based on the attribute information, each first service resource, and its corresponding type. The service interface of the target service resource is invoked to transfer the first object value of the first object corresponding to the passenger, so that the first object value is directly routed from the resource node corresponding to the passenger to the resource receiving node corresponding to the driver. Obtain the driver's historical behavior information, and determine the object processing strategy based on the historical behavior information and the attribute information; The object processing strategy is executed, and the second object value of the second object corresponding to the driver is deducted through a deduction channel independent of the transfer processing.

2. The method according to claim 1, characterized in that, Based on the attribute information, the first service resources, and their corresponding types, the target service resources are determined, including: Based on the attribute information, the first service resources and their corresponding types, the driver's activity level and object loss information in using the first service resources are determined, wherein the object loss information is the object loss value generated by the first service resources during object processing. The target service resource is determined based on the activity level, the object loss information, and the type of each first service resource.

3. The method according to claim 2, characterized in that, Based on the activity level, the object loss information, and the type of each first service resource, the target service resource is determined, including: Based on the activity level, a first weight is determined, which indicates the degree of influence of the activity level on the object processing of the first service resource. Based on the object loss information, a second weight is determined, which is used to indicate the degree of influence of the object loss information on the object processing of the first service resource. The third weight is determined based on the type of each of the first service resources; Based on the activity level, the first weight, the object loss information, the second weight, and the third weight, a first parameter is determined, and based on the first parameter, the target service resource is determined, wherein the first parameter of the target service resource is greater than a first threshold.

4. The method according to claim 1, characterized in that, Based on the historical behavior information and the attribute information, an object processing strategy is determined, including: Based on the attribute information, the driver's credit parameters are determined, and the credit parameters are used to indicate the driver's creditworthiness. The object processing strategy is obtained based on the pre-trained language model, the historical behavior information, and the credit parameters.

5. The method according to claim 4, characterized in that, Based on the pre-trained language model, the historical behavior information, and the credit parameters, the object processing strategy is obtained, including: Temporal features are extracted from the historical behavior information to obtain a behavior feature sequence; The behavioral feature sequence and the credit parameter are converted to obtain a text sequence, which is a semantic description of the driver's resource fluctuation characteristics in different time periods. The text sequence is input into the pre-trained language model to obtain risk warning information, which includes the probability of failure to deduct the value of the second object in the future time period. Based on the risk warning information, determine the object handling strategy.

6. The method according to claim 5, characterized in that, Based on the risk warning information, the object handling strategy is determined, including: When the risk warning information indicates that the probability of deduction failure is greater than or equal to the second threshold, the object processing strategy is determined to be to periodically deduct the first reduction from the second object value; When the risk warning information indicates that the probability of failure to deduct is less than the second threshold, the object processing strategy is determined to be to determine the second reduction corresponding to the travel task and deduct the second reduction from the second object value.

7. The method according to claim 5 or 6, characterized in that, The periodicity is obtained by subtracting the first deduction from the second object value through the following steps: Obtain the third reduction corresponding to each travel task within multiple historical preset periods, wherein the preset periods include a start time and an end time; Based on multiple third reductions, determine the first reduction to be deducted in the current preset period; When the current time is the start time of the preset period, the first reduction is subtracted from the second object value.

8. An object processing apparatus, characterized in that, include: The module comprises an acquisition module, a first determination module, a transfer module, a second determination module, and a deduction module, wherein: The acquisition module is used to acquire, in response to the passenger's instruction to end the travel task, multiple first service resources corresponding to the driver, the type of each first service resource, and the attribute information of the driver. The first determining module is used to determine the target service resource based on the attribute information, each first service resource, and the corresponding type; The transfer module is used to call the service interface of the target service resource to transfer the first object value of the first object corresponding to the passenger, so that the first object value is directly routed from the resource node corresponding to the passenger to the resource receiving node corresponding to the driver. The second determining module is used to acquire the driver's historical behavior information and determine the object processing strategy based on the historical behavior information and the attribute information; The deduction module is used to execute the object processing strategy and deduct the second object value of the second object corresponding to the driver through a deduction channel independent of the transfer processing.

9. An electronic device, characterized in that, include: Memory, processor; The memory stores computer-executed instructions; The processor executes computer execution instructions stored in the memory, causing the processor to perform the method as described in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions, which, when executed by a processor, are used to implement the method as described in any one of claims 1-7.

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