E-commerce compensation service processing method and device

Abstract

The invention discloses a processing method and device for an e-commerce compensation service, and relates to the technical field of e-commerce. According to one specific embodiment, the method comprises the steps that in response to a compensation request initiated by a user, compensation element information is acquired, and the compensation element information comprises compensation parameters; determining a compensation amount calculation formula through a pre-trained large model according to the compensation element information, and sending the compensation amount calculation formula to the customer service for verification; the compensation amount is calculated based on the target compensation amount calculation formula and the compensation parameters passing the customer service verification, and a compensation application form is generated according to the compensation amount; and carrying out e-commerce compensation based on the compensation application form. According to the embodiment, different compensation amount calculation formulas are obtained according to different compensation element information, and the compensation amount is calculated in combination with the compensation parameters, so that the compensation amount calculation efficiency and accuracy are improved, the compensation efficiency and accuracy are improved, and the compensation experience of a user is improved.

Description

Technical Field

[0001] This invention relates to the field of e-commerce technology, and in particular to a method and apparatus for processing e-commerce compensation claims. Background Technology

[0002] E-commerce compensation services refer to a service offered by e-commerce platforms to compensate users whose rights have been infringed upon during the shopping process due to issues such as product quality or logistics problems, in accordance with relevant laws, regulations, and platform rules. Currently, the e-commerce compensation service operates by having the e-commerce platform conduct a preliminary review of the user's complaint and then forward it to the merchant. The merchant verifies the complaint and returns relevant supporting documentation. Finally, the e-commerce platform conducts a detailed review of the user's complaint and supporting documentation before issuing compensation to the user.

[0003] However, the existing e-commerce compensation process suffers from low efficiency and accuracy, impacting the user's compensation experience. Summary of the Invention

[0004] In view of this, embodiments of the present invention provide a method and apparatus for processing e-commerce compensation business, which can obtain different compensation amount calculation formulas according to different compensation reasons, and calculate the compensation amount in combination with compensation element information, thereby improving the efficiency and accuracy of compensation amount calculation, thereby improving compensation efficiency and accuracy and improving the user's compensation experience.

[0005] To achieve the above objectives, according to one aspect of the present invention, a method for processing e-commerce compensation transactions is provided, comprising: In response to a user-initiated claim request, claim element information is obtained, including claim parameters; Based on the compensation element information, a compensation amount calculation formula is determined through a pre-trained large model, and the compensation amount calculation formula is sent to customer service for verification. The compensation amount is calculated based on the target compensation amount calculation formula verified by customer service and the compensation parameters, and a compensation application form is generated based on the compensation amount; E-commerce compensation will be processed based on the aforementioned compensation application form.

[0006] Optionally, the large model is trained by: acquiring historical payout records and extracting payout element features, payout formulas corresponding to the payout element features, and their scores from the historical payout records; the payout element features include payout reason features, payout scenario features, payout prompt features, and payout parameter features; and training the large model based on the payout reason features, the payout scenario features, the payout prompt features, the payout parameter features, the corresponding payout formulas, and their scores.

[0007] Optionally, the compensation element information further includes compensation reason information, compensation scenario information, and compensation prompt information; based on the compensation element information, a compensation amount calculation formula is determined through a pre-trained large model, including: extracting features from the compensation reason information, the compensation scenario information, the compensation prompt information, and the compensation parameters to obtain corresponding compensation reason features, compensation scenario features, compensation prompt features, and compensation parameter features; based on the extracted compensation reason features, compensation scenario features, compensation prompt features, and compensation parameter features, at least one compensation formula and its score are generated through the pre-trained large model, and the compensation formula whose score meets a preset score threshold is determined as the compensation amount calculation formula.

[0008] Optionally, sending the compensation amount calculation formula to customer service for verification includes: displaying the compensation amount calculation formula in a visual interface so that customer service can select a first compensation amount calculation formula from the compensation amount calculation formulas through the visual interface; and modifying the first compensation amount calculation formula in response to the modification instruction submitted by customer service through the visual interface to obtain the target compensation amount calculation formula verified by customer service.

[0009] Optionally, the method further includes: collecting the correspondence data between the compensation element information and the target compensation amount calculation formula for use in optimizing and training the large model.

[0010] Optionally, calculating the compensation amount based on the target compensation amount calculation formula verified by customer service and the compensation parameters includes: compiling the target compensation amount calculation formula into bytecode using an expression evaluation engine based on the target compensation amount calculation formula verified by customer service and the compensation parameters, and injecting the compensation parameters as variables into the bytecode to calculate the compensation amount.

[0011] Optionally, before generating a claim form based on the claim amount, the method further includes: viewing the calculation formula and calculation process details of the target claim amount through the page's calculation function to determine if the claim amount is accurate.

[0012] Optionally, e-commerce compensation based on the compensation application includes: obtaining compensation review and verification rules based on the compensation element information, reviewing the compensation application using the compensation review and verification rules, and making e-commerce compensation based on the review results.

[0013] Optionally, obtaining compensation review and verification rules based on the compensation element information includes: extracting compensation scenario information from the compensation element information, and obtaining corresponding compensation review and verification rules based on the compensation scenario information. The compensation review and verification rules are set using the factory pattern for different compensation scenarios.

[0014] According to another aspect of the present invention, an apparatus for processing e-commerce compensation services is provided, comprising: The request receiving module is used to respond to a user-initiated compensation request and obtain compensation element information, which includes compensation parameters; The data acquisition module is used to determine the compensation amount calculation formula through a pre-trained large model based on the compensation element information, and send the compensation amount calculation formula to customer service for verification. The compensation amount calculation module is used to calculate the compensation amount based on the target compensation amount calculation formula verified by customer service and the compensation parameters, and to generate a compensation application form based on the compensation amount; The e-commerce compensation module is used to process e-commerce compensation based on the compensation application form.

[0015] Optionally, the device further includes a large model training module, used to train a large model in the following ways: acquiring historical payout records, and extracting payout element features, payout formulas corresponding to the payout element features, and their scores from the historical payout records, wherein the payout element features include payout reason features, payout scenario features, payout prompt features, and payout parameter features; and training the large model based on the payout reason features, the payout scenario features, the payout prompt features, the payout parameter features, the corresponding payout formulas, and their scores.

[0016] Optionally, the compensation element information further includes compensation reason information, compensation scenario information, and compensation prompt information. The data acquisition module is further configured to: extract features from the compensation reason information, the compensation scenario information, the compensation prompt information, and the compensation parameters to obtain corresponding compensation reason features, compensation scenario features, compensation prompt features, and compensation parameter features; based on the extracted compensation reason features, compensation scenario features, compensation prompt features, and compensation parameter features, generate at least one compensation formula and its score through a pre-trained large model, and determine the compensation formula whose score meets a preset score threshold as the compensation amount calculation formula.

[0017] Optionally, the data acquisition module is further configured to: display the compensation amount calculation formula in a visualization interface, so that the customer service representative can select a first compensation amount calculation formula from the compensation amount calculation formulas through the visualization interface; and modify the first compensation amount calculation formula in response to the customer service representative's instruction to modify the parameters in the first compensation amount calculation formula submitted through the visualization interface, thereby obtaining the target compensation amount calculation formula verified by the customer service representative.

[0018] Optionally, the device further includes a large model optimization module, used to: collect the correspondence data between the compensation element information and the target compensation amount calculation formula for optimizing and training the large model.

[0019] Optionally, the compensation amount calculation module is further configured to: based on the target compensation amount calculation formula verified by customer service and the compensation parameters, compile the target compensation amount calculation formula into bytecode through an expression evaluation engine, and inject the compensation parameters as variables into the bytecode to calculate the compensation amount.

[0020] Optionally, the device further includes a compensation amount calibration module, used to: before generating a compensation claim form based on the compensation amount, view the calculation formula and calculation process details of the target compensation amount through the page trial calculation function to determine whether the compensation amount is accurate.

[0021] Optionally, the e-commerce compensation module is further configured to: obtain compensation review and verification rules based on the compensation element information, review the compensation application form using the compensation review and verification rules, and make e-commerce compensation based on the review results.

[0022] Optionally, the e-commerce compensation module is further configured to: extract compensation scenario information from the compensation element information, and obtain corresponding compensation review and verification rules based on the compensation scenario information, wherein the compensation review and verification rules are set using the factory pattern for different compensation scenarios.

[0023] According to another aspect of the present invention, an electronic device is provided, comprising: one or more processors; and a storage device for storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors implement the e-commerce compensation processing method provided in the embodiments of the present invention.

[0024] According to another aspect of the present invention, a computer-readable medium is provided having a computer program stored thereon, which, when executed by a processor, implements the e-commerce compensation processing method provided in the embodiments of the present invention.

[0025] According to another aspect of the present invention, a computer program product is provided, including a computer program that, when executed by a processor, implements the e-commerce compensation business processing method provided in the embodiments of the present invention.

[0026] One embodiment of the above invention has the following advantages or beneficial effects: In response to a user-initiated compensation request, compensation element information is obtained, including compensation parameters; based on the compensation element information, a compensation amount calculation formula is determined using a pre-trained large model, and this formula is sent to customer service for verification; the compensation amount is calculated based on the target compensation amount calculation formula verified by customer service and the compensation parameters, and a compensation application form is generated based on the compensation amount; this technical solution for e-commerce compensation based on the compensation application form can obtain different compensation amount calculation formulas based on different compensation element information, and calculate the compensation amount in combination with the compensation parameters, thereby improving the efficiency and accuracy of compensation amount calculation, and thus improving the user's compensation experience.

[0027] The further effects of the aforementioned unconventional alternative methods will be explained below in conjunction with specific implementation methods. Attached Figure Description

[0028] The accompanying drawings are provided to better understand the invention and are not intended to unduly limit the scope of the invention. Wherein: Figure 1 This is a schematic diagram of the main steps of the e-commerce compensation process according to an embodiment of the present invention; Figure 2 This is a schematic diagram of the configuration process for the compensation amount calculation formula according to an embodiment of the present invention; Figure 3 This is a schematic diagram of the compensation amount calculation process according to an embodiment of the present invention; Figure 4 This is a schematic diagram of the e-commerce compensation process according to an embodiment of the present invention; Figure 5 This is a schematic diagram of the main modules of an e-commerce compensation processing device according to an embodiment of the present invention; Figure 6 This is an exemplary system architecture diagram in which embodiments of the present invention can be applied; Figure 7 This is a schematic diagram of the structure of a computer system suitable for implementing terminal devices or servers of the present invention. Detailed Implementation

[0029] The following description, in conjunction with the accompanying drawings, illustrates exemplary embodiments of the present invention, including various details to aid understanding. These details should be considered merely exemplary. Therefore, those skilled in the art will recognize that various changes and modifications can be made to the embodiments described herein without departing from the scope and spirit of the invention. Similarly, for clarity and brevity, descriptions of well-known functions and structures are omitted in the following description.

[0030] It should be noted that the technical solutions disclosed in this invention, regarding the collection, updating, analysis, processing, use, transmission, and storage of user personal information, all comply with relevant laws and regulations, are used for legitimate purposes, and do not violate public order and good morals. Necessary measures are taken to prevent unauthorized access to user personal information data and to safeguard user personal information security, network security, and national security.

[0031] The main processes for handling e-commerce claims under existing technologies are as follows: 1. Complaint channels: E-commerce platforms usually have dedicated complaint channels. When users encounter problems during the shopping process, they can submit complaints through online customer service, telephone, application, etc. 2. Complaint review: After receiving a user complaint, the e-commerce platform will conduct a preliminary review to confirm the authenticity of the complaint, the target of the complaint, and other relevant information. 3. Merchant Negotiation: The e-commerce platform will forward the complaint information to the merchant, who needs to verify the complaint content and submit relevant evidence; 4. Compensation Review: The e-commerce platform conducts a detailed review of user complaints and merchant vouchers to determine whether the complaint is valid and to calculate the compensation amount; 5. Compensation Process: Based on the review results, the e-commerce platform will compensate the user, including refunds and compensation. 6. User Confirmation: After receiving the compensation, the user must confirm the compensation result and close the complaint case; 7. Case Archiving: E-commerce platforms archive complaint cases, summarize lessons learned, and improve after-sales service.

[0032] However, while the above e-commerce compensation process provides consumers and merchants with avenues for protecting their rights, it also has some drawbacks, as follows: 1. Inconsistent compensation standards: For compensation requests in the same or similar scenarios, different customer service representatives on the platform may provide different compensation standards, which can easily lead to user complaints and affect the user's compensation experience; 2. Inefficient compensation process: The compensation process in e-commerce involves many steps, such as complaints, reviews, and negotiations. The whole process may take a long time, which affects the rights and interests of consumers and merchants. 3. Inaccurate compensation amount: Due to the numerous rules in the compensation business, the compensation amount needs to take into account the price protection amount, the amount already compensated, the amount of the cancelled part of the order, coupon information, etc., which may lead to erroneous, under-compensated or over-compensated compensation when calculating the compensation amount, which may increase the merchant's financial losses. 4. E-commerce platform losses: During the compensation process, e-commerce platforms incur certain costs, such as customer service staff costs and verification costs. Some malicious acts may also damage the platform's reputation, thereby affecting its brand image and market share.

[0033] In summary, the existing e-commerce claims process suffers from low efficiency and accuracy, negatively impacting the user's claims experience.

[0034] To address at least one of the aforementioned technical problems, this invention provides a method for processing e-commerce compensation claims. This method improves the efficiency and accuracy of compensation claims in scenarios with a large number of users requesting compensation, and enhances the user experience. The technical solution of this invention can obtain different compensation amount calculation formulas based on different compensation reasons, and calculate the compensation amount by combining compensation element information. This improves the efficiency and accuracy of compensation amount calculation, effectively reducing financial losses for both the platform and users, thereby improving compensation efficiency and accuracy and enhancing the user's compensation experience. Simultaneously, an expression evaluation engine can be used to calculate the compensation amount by combining compensation element information and compensation amount calculation formulas, eliminating the need for manual intervention and significantly reducing customer service labor costs, thus improving the efficiency and accuracy of processing compensation applications. Combining historical compensation records to determine the compensation amount calculation formulas corresponding to different compensation reasons improves the accuracy of the compensation results calculated by the compensation amount calculation formulas, increasing user satisfaction. Finally, compensation applications can be automatically reviewed by setting compensation review and verification rules under different compensation scenarios, improving review efficiency and enhancing the user's compensation experience.

[0035] Figure 1 This is a schematic diagram illustrating the main steps of an e-commerce compensation processing method according to an embodiment of the present invention. Figure 1 As shown, the e-commerce compensation processing method of this embodiment of the invention mainly includes the following steps S101 to S104.

[0036] Step S101: In response to a user-initiated compensation request, obtain compensation element information, including compensation parameters. The compensation request can be initiated during a customer service consultation, through an order page, or through a front-end page provided by the compensation system. By initiating a compensation request, the user can inquire about the availability of compensation and the specific compensation amount. In this embodiment of the invention, compensation element information can be obtained based on the compensation request. This information includes, for example, compensation reason information, compensation scenario information, compensation prompt information, and compensation parameters, used to determine the compensation amount calculation formula. Compensation parameters include, for example, order information, price protection information, order cancellation information, and used coupon information, used to calculate the compensation amount in conjunction with the compensation amount calculation formula. The compensation amount can be cash rewards, virtual payment currency, coupons, points, etc.

[0037] In embodiments of the present invention, based on the compensation request, information such as the order number to be compensated, price protection information, and coupon information used can be obtained through the customer service consultation context or the order information that initiated the compensation request; the compensation reason summarized and extracted through the customer service consultation context or the compensation reason entered by the user; the compensation scenario; and compensation prompts. The compensation reason can be a textual description of the compensation reason or a specific problem encountered, information provided by images, or information provided through preset options, etc.

[0038] After receiving a compensation request from a user, customer service personnel can be assigned to perform parameter verification and business verification on the obtained compensation information to determine whether the compensation requirements are met. Parameter verification includes, for example, verifying the order number to be correct; business verification includes, for example, checking the specific logistics information of the product corresponding to the current order number, whether there are any previous compensation and after-sales records, whether the received goods are indeed defective, or whether the goods were indeed not received, etc. Only if the parameter verification and business verification pass will the subsequent process proceed to determine the compensation amount and make the compensation payment; if the parameter verification and business verification fail, a message will be returned to the user indicating that the compensation requirements are not met, to inform the user that the compensation request has not been approved.

[0039] Step S102: Based on the compensation element information, determine the compensation amount calculation formula through a pre-trained large model, and send the compensation amount calculation formula to customer service for verification.

[0040] According to one embodiment of the present invention, a large model can be pre-trained based on historical compensation records to determine the compensation amount calculation formula corresponding to different compensation scenarios, compensation reasons, and compensation prompts. Specifically, the large model is trained, for example, by: acquiring historical compensation records and extracting compensation element features, compensation formulas corresponding to the compensation element features, and their scores from the historical compensation records. The compensation element features include compensation reason features, compensation scenario features, compensation prompt features, compensation parameter features, and compensation parameter features; and training the large model based on the compensation reason features, compensation scenario features, compensation prompt features, compensation parameter features, corresponding compensation formulas, and their scores. The historical compensation records include, for example, when the user initiated the compensation request, the compensation element features corresponding to the compensation request, the compensation formula corresponding to the compensation request, and the score, which is generated, for example, based on the user's feedback on the historical compensation. The compensation element features corresponding to the compensation request may include compensation reason features, compensation scenario features, compensation prompt features, and compensation parameter features. The characteristics of the compensation reason are, for example, those input or selected by the user, or those summarized and extracted from the context of customer service consultation; the characteristics of the compensation scenario are determined based on the interface corresponding to which the user initiates the compensation, such as compensation requests initiated by the user through the order after-sales page interface, compensation requests initiated by the user through the order details page interface, or compensation requests initiated by the user through the customer service consultation page interface, etc.; the characteristics of the compensation prompt are, for example, the prompt information submitted by the user after initiating the compensation request regarding the compensation time, compensation requirements, etc.; the characteristics of the compensation parameter are, for example, the order number of the order to which the compensation request is targeted, whether coupons were used, whether red envelopes were used, whether after-sales service was applied for, etc.

[0041] By processing a large number of historical payout records, at least one payout formula corresponding to each payout element feature, and a score for each payout formula, can be obtained. Then, a large model can be trained based on the extracted payout reason features, payout scenario features, payout notification features, payout parameter features, corresponding payout formulas, and their scores.

[0042] According to one embodiment of the present invention, a compensation amount calculation formula is determined by a pre-trained large model based on compensation element information. Specifically, this may include: extracting features from compensation reason information, compensation scenario information, compensation prompt information, and compensation parameters to obtain corresponding compensation reason features, compensation scenario features, compensation prompt features, and compensation parameter features; based on the extracted compensation reason features, compensation scenario features, compensation prompt features, and compensation parameter features, generating at least one compensation formula and its score using the pre-trained large model, and determining the compensation formula whose score meets a preset score threshold as the compensation amount calculation formula. In specific implementation, features can be extracted from the compensation reason information, compensation scenario information, compensation prompt information, and compensation parameters included in the compensation element information. Then, based on the extracted features, at least one compensation formula and its score can be determined using a large model. Finally, at least one compensation formula that meets the set score threshold can be selected as the compensation amount calculation formula and returned to customer service. In addition, for the selected at least one compensation formula, it can be sorted according to the score, and a compensation formula of no more than the set number threshold can be selected from the sorted at least one compensation formula as the compensation amount calculation formula and returned to customer service.

[0043] In other embodiments of the present invention, the compensation amount calculation formula can also be determined according to set rules when determining the compensation amount calculation formula. For example, the compensation amount calculation formula can also be determined from a compensation formula configuration library based on the compensation reason. The compensation formula configuration library stores the correspondence between compensation element information and compensation amount calculation formulas. The correspondence between compensation element information and compensation amount calculation formulas is generated as follows: obtaining historical compensation records and user feedback information on historical compensation records, where each historical compensation record includes at least one compensation formula corresponding to each compensation element information; calculating a score for each compensation formula corresponding to each compensation element information based on user feedback information on the historical compensation records corresponding to the compensation formula; and determining the compensation amount calculation formula corresponding to each compensation element information from the at least one compensation formula corresponding to each compensation element information based on the score of each compensation formula corresponding to each compensation element information. In specific implementation, user feedback information on historical compensation records may include, for example, user satisfaction with the compensation amount calculated by the compensation formula corresponding to the historical compensation record, and the platform's determination of whether the compensation amount is within a reasonable range, etc. When calculating the score for the compensation formula, a weighted sum is used, for example, based on the user's satisfaction score with the compensation amount calculated using the compensation formula corresponding to historical compensation records and the platform's score determining whether the compensation amount is within a reasonable range. For each compensation element, the score for its corresponding compensation formula is calculated separately, and the compensation formula with the highest score is selected as the compensation amount calculation formula for that compensation element. Then, the correspondence between compensation element information and compensation amount calculation formulas can be established.

[0044] According to one embodiment of the present invention, sending the compensation amount calculation formula to customer service for verification may specifically include: displaying the compensation amount calculation formula in a visual interface, allowing customer service to select a first compensation amount calculation formula from the compensation amount calculation formulas through the visual interface; responding to the customer service's instruction to modify the parameters in the first compensation amount calculation formula submitted through the visual interface, modifying the first compensation amount calculation formula to obtain the target compensation amount calculation formula verified by customer service. In specific implementation, the compensation amount calculation formula determined by the large model is displayed in the visual interface so that customer service can select the first compensation amount calculation formula from it. Subsequently, customer service can also modify the parameters in the first compensation amount calculation formula to achieve rapid modification and flexible configuration of the compensation amount calculation formula to adapt to the needs of flexible and ever-changing operational rules.

[0045] In other embodiments, if the customer service representative does not need to modify the selected first compensation amount calculation formula, the selected first compensation amount calculation formula can be directly used as the target compensation amount calculation formula that has passed the verification.

[0046] Figure 2 This is a schematic diagram illustrating the configuration process of the compensation amount calculation formula according to an embodiment of the present invention. Figure 2 As shown, in one embodiment of the present invention, claims operations personnel (e.g., customer service) can configure the claims amount calculation formula in a visual interface. Specifically, claims operations personnel can set information such as claims reason, claims scenario, claims prompt, and claims parameters in the visual interface. Then, the claims system will combine the above information and historical claims records to recommend the optimal claims amount calculation formula and display it in the visual interface. Claims operations personnel can modify the parameters of the recommended optimal claims amount calculation formula in the visual interface to obtain the claims amount calculation formula corresponding to the claims element information and save it to the claims formula configuration library.

[0047] According to one embodiment of the present invention, the processing method for e-commerce compensation business may further include: collecting the correspondence data between compensation element information and the target compensation amount calculation formula for use in optimizing and training a large model. After obtaining the target compensation amount calculation formula verified by customer service, the correspondence between compensation element information and the target compensation amount calculation formula may also be collected for subsequent optimization and training of the large model, thereby improving the adaptability of the large model to different compensation scenarios and different compensation reasons.

[0048] Step S103: Calculate the compensation amount based on the target compensation amount calculation formula and compensation parameters verified by customer service, and generate a compensation application form based on the compensation amount. The compensation amount can be calculated based on the aforementioned compensation parameters and compensation amount calculation formula, thereby generating a compensation application form.

[0049] According to one embodiment of the present invention, calculating the compensation amount based on the target compensation amount calculation formula and compensation parameters verified by customer service may specifically include: compiling the target compensation amount calculation formula into bytecode using an expression evaluation engine, and injecting the compensation parameters as variables into the bytecode to calculate the compensation amount. In this embodiment of the present invention, the expression evaluation engine is, for example, the Aviator expression engine, which is an expression evaluation engine based on Java (a programming language) used to parse and calculate expressions. It supports common expression calculations such as mathematical operations, logical operations, and string operations. The compensation amount can be automatically calculated using the Aviator expression engine and filled into the compensation application page to generate a compensation application form.

[0050] According to one embodiment of the present invention, after calculating the compensation amount based on the target compensation amount calculation formula and compensation parameters verified by customer service, and before generating a compensation application form based on the compensation amount, the method may further include: viewing the target compensation amount calculation formula and calculation process details through a page trial calculation function to determine if the compensation amount is accurate. In specific implementation, if there is any doubt about the generated compensation amount, the target compensation amount calculation formula can be obtained and displayed on the page through the page trial calculation function. Clicking the "Trial Calculation" button on the page will call the corresponding interface to calculate the compensation amount based on the compensation parameters and compensation amount calculation formula, and display the calculation process details, thereby determining whether the calculated compensation amount is accurate. If the compensation amount is confirmed to be accurate, a compensation application form can be generated based on the compensation amount.

[0051] Figure 3 This is a schematic diagram illustrating the compensation amount calculation process according to an embodiment of the present invention. Figure 3 As shown, when calculating the compensation amount, compensation parameters can be obtained based on the order number, such as order information, price protection information, compensation information, order cancellation information, and coupon information used; and the compensation amount is calculated by combining the compensation parameters and the target compensation amount calculation formula, and a compensation application form is generated based on the compensation amount.

[0052] Step S104: Process e-commerce compensation based on the compensation application form. In an embodiment of the present invention, after generating the compensation application form, the compensation system can also review the compensation application form and process the e-commerce compensation after the review is approved. Specifically, the compensation system can automatically scan the compensation application form to be reviewed and review it.

[0053] According to one embodiment of the present invention, e-commerce compensation based on a compensation application form may specifically include: obtaining compensation review and verification rules based on compensation element information, reviewing the compensation application form using the compensation review and verification rules, and making e-commerce compensation based on the review results. Specifically, if the review is approved, e-commerce compensation can be made directly based on the compensation application form; otherwise, customer service personnel are prompted that the review has failed and that the compensation amount calculation formula needs to be redefined and the compensation amount calculated.

[0054] According to one embodiment of the present invention, obtaining compensation review and verification rules based on compensation element information may specifically include: extracting compensation scenario information from the compensation element information, and obtaining corresponding compensation review and verification rules based on the compensation scenario information. The compensation review and verification rules are set using a factory pattern for different compensation scenarios. Specifically, the present invention can pre-store the correspondence between compensation element information and compensation scenario information, and use a factory pattern to set compensation review and verification rules for different compensation scenarios. This allows the compensation application to be reviewed when the corresponding compensation review and verification rules are obtained based on the compensation element information.

[0055] After reviewing the claim application, relevant processing log information will be recorded to facilitate subsequent problem analysis and business data analysis, and the review results will be automatically notified to the user.

[0056] Figure 4 This is a schematic diagram of the e-commerce compensation process according to an embodiment of the present invention. Figure 4 As shown, the processing flow of e-commerce compensation business in this embodiment of the invention is mainly as follows: 1. Users send compensation requests through the e-commerce system and obtain compensation element information, which includes compensation parameters; 2. The compensation system performs a preliminary verification of the compensation request. If the verification passes, step 3 below is executed; otherwise, a message indicating that the compensation requirements are not met is returned to the user. 3. The compensation system determines the compensation amount calculation formula based on the compensation element information using a pre-trained large model and sends it to customer service; 4. Determine the target compensation amount calculation formula that has been verified by customer service. Customer service can directly select the target compensation amount calculation formula from the compensation amount calculation formula, or modify the parameters of the compensation amount calculation formula to generate the target compensation amount calculation formula. 5. The compensation system uses an expression evaluation engine to calculate the compensation amount based on the compensation parameters and the target compensation amount calculation formula, and then fills the compensation amount into the compensation application page to generate a compensation application form; 6. The compensation system determines the compensation scenario based on the compensation element information, obtains the compensation review and verification rules based on the compensation scenario, and then uses the compensation review and verification rules to review the compensation application form; 7. If the review is approved, e-commerce compensation will be processed according to the compensation application form; otherwise, the user will be given a message indicating that the compensation review has not been approved.

[0057] Figure 5 This is a schematic diagram of the main modules of a processing device for e-commerce compensation services according to an embodiment of the present invention. Figure 5 As shown, the e-commerce compensation processing device 500 of this embodiment mainly includes a request receiving module 501, a data acquisition module 502, a compensation amount calculation module 503, and an e-commerce compensation module 504.

[0058] The request receiving module 501 is used to respond to the compensation request initiated by the user and obtain compensation element information, including compensation parameters. The data acquisition module 502 is used to determine the compensation amount calculation formula based on the compensation element information through a pre-trained large model, and send the compensation amount calculation formula to customer service for verification. The compensation amount calculation module 503 is used to calculate the compensation amount based on the target compensation amount calculation formula and compensation parameters verified by customer service, and generate a compensation application form based on the compensation amount; The e-commerce compensation module 504 is used to process e-commerce compensation based on compensation application forms.

[0059] According to an embodiment of the present invention, the processing device 500 for e-commerce compensation business may further include a large model training module (not shown in the figure), which is used to train a large model in the following manner: acquiring historical compensation records, and extracting compensation element features, compensation formulas corresponding to the compensation element features and their scores from the historical compensation records, wherein the compensation element features include compensation reason features, compensation scenario features, compensation prompt features and compensation parameter features; and training the large model based on the compensation reason features, compensation scenario features, compensation prompt features, compensation parameter features, corresponding compensation formulas and their scores.

[0060] According to one embodiment of the present invention, the compensation element information further includes compensation reason information, compensation scenario information, and compensation prompt information. The data acquisition module 502 can specifically be used to: extract features from the compensation reason information, compensation scenario information, compensation prompt information, and compensation parameters respectively to obtain corresponding compensation reason features, compensation scenario features, compensation prompt features, and compensation parameter features; based on the extracted compensation reason features, compensation scenario features, compensation prompt features, and compensation parameter features, generate at least one compensation formula and its score through a pre-trained large model, and determine the compensation formula whose score meets a preset score threshold as the compensation amount calculation formula.

[0061] According to one embodiment of the present invention, the data acquisition module 502 can be specifically used to: display the compensation amount calculation formula in a visual interface, so that the customer service representative can select a first compensation amount calculation formula from the compensation amount calculation formulas through the visual interface; and in response to the customer service representative's instruction to modify the parameters in the first compensation amount calculation formula submitted through the visual interface, modify the first compensation amount calculation formula to obtain the target compensation amount calculation formula verified by the customer service representative.

[0062] According to an embodiment of the present invention, the e-commerce compensation processing device 500 may further include a large model optimization module (not shown in the figure), which is used to: collect the correspondence data between compensation element information and the target compensation amount calculation formula for optimizing and training the large model.

[0063] According to one embodiment of the present invention, the compensation amount calculation module 503 can be specifically used to: based on the target compensation amount calculation formula and compensation parameters verified by customer service, compile the target compensation amount calculation formula into bytecode through an expression evaluation engine, and inject the compensation parameters as variables into the bytecode to calculate the compensation amount.

[0064] According to an embodiment of the present invention, the e-commerce compensation processing device 500 further includes a compensation amount calibration module (not shown in the figure), which is used to: before generating a compensation application form based on the compensation amount, view the calculation formula and calculation process details of the target compensation amount through the page calculation function to determine that the compensation amount is accurate.

[0065] According to one embodiment of the present invention, the e-commerce compensation module 504 can be specifically used to: obtain compensation review and verification rules based on compensation element information, review the compensation application form using the compensation review and verification rules, and make e-commerce compensation based on the review results.

[0066] According to an embodiment of the present invention, the e-commerce compensation module 504 can also be used to: extract compensation scenario information from compensation element information, and obtain corresponding compensation review and verification rules according to the compensation scenario information. The compensation review and verification rules are set using the factory pattern for different compensation scenarios.

[0067] According to the technical solution of this invention, in response to a user-initiated compensation request, compensation element information is obtained, including compensation parameters. Based on the compensation element information, a compensation amount calculation formula is determined using a pre-trained large model, and the compensation amount calculation formula is sent to customer service for verification. Based on the target compensation amount calculation formula verified by customer service and the compensation parameters, the compensation amount is calculated, and a compensation application form is generated based on the compensation amount. This technical solution for e-commerce compensation based on the compensation application form can obtain different compensation amount calculation formulas according to different compensation element information, and calculate the compensation amount in combination with compensation parameters, thereby improving the efficiency and accuracy of compensation amount calculation, thus improving compensation efficiency and accuracy, and enhancing the user's compensation experience.

[0068] Figure 6 An exemplary system architecture 600 is shown, which can be used to process e-commerce compensation business according to embodiments of the present invention.

[0069] like Figure 6 As shown, system architecture 600 may include terminal devices 601, 602, and 603, a network 604, and a server 605. Network 604 serves as the medium for providing communication links between terminal devices 601, 602, and 603 and server 605. Network 604 may include various connection types, such as wired or wireless communication links or fiber optic cables, etc.

[0070] Users can use terminal devices 601, 602, and 603 to interact with server 605 via network 604 to receive or send messages, etc. Various communication client applications can be installed on terminal devices 601, 602, and 603, such as shopping applications, web browser applications, search applications, instant messaging tools, email clients, social media platform software, etc. (for example only).

[0071] Terminal devices 601, 602, and 603 can be various electronic devices with displays and web browsing capabilities, including but not limited to smartphones, tablets, laptops, and desktop computers.

[0072] Server 605 can be a server providing various services, such as a backend management server supporting shopping websites browsed by users using terminal devices 601, 602, and 603 (for example only). The backend management server can process received data such as compensation requests by obtaining compensation element information and compensation amount calculation formulas, calculating compensation amounts, generating and reviewing compensation application forms, and feeding back the processing results (such as the review results of compensation application forms - for example only) to the terminal devices.

[0073] It should be noted that the e-commerce compensation processing method provided in this embodiment of the invention is generally executed by server 605, and correspondingly, the e-commerce compensation processing device is generally set in server 605.

[0074] It should be understood that Figure 6 The number of terminal devices, networks, and servers shown is merely illustrative. Depending on implementation needs, any number of terminal devices, networks, and servers can be included.

[0075] The following is for reference. Figure 7 It shows a schematic diagram of the structure of a computer system 700 suitable for implementing terminal devices or servers of the present invention. Figure 7 The terminal device or server shown is merely an example and should not impose any limitation on the functionality and scope of use of the embodiments of the present invention.

[0076] like Figure 7 As shown, the computer system 700 includes a central processing unit (CPU) 701, which can perform various appropriate actions and processes based on programs stored in read-only memory (ROM) 702 or programs loaded from storage section 708 into random access memory (RAM) 703. The RAM 703 also stores various programs and data required for the operation of the system 700. The CPU 701, ROM 702, and RAM 703 are interconnected via a bus 704. An input / output (I / O) interface 705 is also connected to the bus 704.

[0077] The following components are connected to the I / O interface 705: an input section 706 including a keyboard, mouse, etc.; an output section 707 including a cathode ray tube (CRT), liquid crystal display (LCD), etc., and speakers, etc.; a storage section 708 including a hard disk, etc.; and a communication section 709 including a network interface card such as a LAN card, modem, etc. The communication section 709 performs communication processing via a network such as the Internet. A drive 710 is also connected to the I / O interface 705 as needed. A removable medium 711, such as a disk, optical disk, magneto-optical disk, semiconductor memory, etc., is installed on the drive 710 as needed so that computer programs read from it can be installed into the storage section 708 as needed.

[0078] In particular, according to the embodiments disclosed in this invention, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments disclosed in this invention include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via communication section 709, and / or installed from removable medium 711. When the computer program is executed by central processing unit (CPU) 701, it performs the functions defined above in the system of this invention.

[0079] It should be noted that the computer-readable medium shown in this invention can be a computer-readable signal medium or a computer-readable storage medium, or any combination thereof. A computer-readable storage medium can be, for example,—but not limited to—an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of a computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fiber, portable compact disk read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this invention, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. In this invention, a computer-readable signal medium can include a data signal propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. Computer-readable signal media can also be any computer-readable medium other than computer-readable storage media, which can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium can be transmitted using any suitable medium, including but not limited to: wireless, wire, optical fiber, RF, etc., or any suitable combination thereof.

[0080] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of the present invention. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram or flowchart, and combinations of blocks in a block diagram or flowchart, may be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0081] The units or modules described in the embodiments of the present invention can be implemented in software or hardware. The described units or modules can also be housed in a processor; for example, a processor can be described as including a request receiving module, a data acquisition module, a compensation amount calculation module, and an e-commerce compensation module. The names of these units or modules do not necessarily limit the specific unit or module itself; for example, a request receiving module can also be described as "a module for receiving compensation requests sent by users."

[0082] In another aspect, the present invention also provides a computer-readable medium, which may be included in the device described in the above embodiments; or it may exist independently and not assembled into the device. The computer-readable medium carries one or more programs, which, when executed by the device, cause the device to: respond to a user-initiated compensation request, obtain compensation element information, including compensation parameters; determine a compensation amount calculation formula based on the compensation element information using a pre-trained large model, and send the compensation amount calculation formula to customer service for verification; calculate the compensation amount based on the target compensation amount calculation formula and compensation parameters verified by customer service, generate a compensation application form based on the compensation amount, and perform e-commerce compensation based on the compensation application form.

[0083] According to the technical solution of this invention, in response to a user-initiated compensation request, compensation element information is obtained, including compensation parameters. Based on the compensation element information, a compensation amount calculation formula is determined using a pre-trained large model, and the compensation amount calculation formula is sent to customer service for verification. Based on the target compensation amount calculation formula verified by customer service and the compensation parameters, the compensation amount is calculated, and a compensation application form is generated based on the compensation amount. This technical solution for e-commerce compensation based on the compensation application form can obtain different compensation amount calculation formulas according to different compensation element information, and calculate the compensation amount in combination with compensation parameters, thereby improving the efficiency and accuracy of compensation amount calculation, thus improving compensation efficiency and accuracy, and enhancing the user's compensation experience.

[0084] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can occur depending on design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A method for processing e-commerce compensation claims, characterized in that, include: In response to a user-initiated claim request, claim element information is obtained, including claim parameters; Based on the compensation element information, a compensation amount calculation formula is determined through a pre-trained large model, and the compensation amount calculation formula is sent to customer service for verification. The compensation amount is calculated based on the target compensation amount calculation formula verified by customer service and the compensation parameters, and a compensation application form is generated based on the compensation amount; E-commerce compensation will be processed based on the aforementioned compensation application form.

2. The method according to claim 1, characterized in that, The large model was trained in the following way: Obtain historical claims records, and extract claims element features, claims formulas corresponding to the claims element features, and their scores from the historical claims records. The claims element features include claims reason features, claims scenario features, claims prompt features, and claims parameter features. The large model is trained based on the features of the cause of compensation, the features of the scenario of compensation, the features of the prompt of compensation, the features of the parameters of compensation, the corresponding compensation formula and its score.

3. The method according to claim 2, characterized in that, The compensation element information also includes compensation reason information, compensation scenario information, and compensation reminder information; Based on the aforementioned compensation element information, a formula for calculating the compensation amount is determined using a pre-trained large model, including: Feature extraction is performed on the claim reason information, the claim scenario information, the claim prompt information, and the claim parameters respectively to obtain the corresponding claim reason features, claim scenario features, claim prompt features, and claim parameter features; Based on the extracted features of compensation cause, compensation scenario, compensation prompt and compensation parameter, at least one compensation formula and its score are generated by a pre-trained large model, and the compensation formula that meets the preset score threshold is determined as the compensation amount calculation formula.

4. The method according to claim 3, characterized in that, Send the compensation calculation formula to customer service for verification, including: The compensation amount calculation formula is displayed in the visualization interface so that customer service can select the first compensation amount calculation formula from the compensation amount calculation formula through the visualization interface; In response to the customer service representative's instruction to modify the parameters in the first compensation amount calculation formula submitted through the visual interface, the first compensation amount calculation formula is modified to obtain the target compensation amount calculation formula verified by the customer service representative.

5. The method according to claim 4, characterized in that, The method further includes: Collect the correspondence data between the compensation element information and the target compensation amount calculation formula to optimize and train the large model.

6. The method according to claim 1, characterized in that, The compensation amount is calculated based on the target compensation amount calculation formula verified by customer service and the aforementioned compensation parameters, including: Based on the target compensation amount calculation formula verified by customer service and the compensation parameters, the target compensation amount calculation formula is compiled into bytecode by the expression evaluation engine, and the compensation parameters are injected into the bytecode as variables to calculate the compensation amount.

7. The method according to claim 1, characterized in that, Before generating a claim form based on the stated compensation amount, the process also includes: View the calculation formula and detailed calculation process for the target compensation amount using the page's trial calculation function to confirm that the compensation amount is accurate.

8. The method according to claim 1, characterized in that, E-commerce compensation based on the aforementioned compensation claim form includes: Based on the compensation element information, compensation review and verification rules are obtained, the compensation application is reviewed using the compensation review and verification rules, and e-commerce compensation is made according to the review results.

9. The method according to claim 8, characterized in that, Based on the aforementioned compensation element information, compensation review and verification rules are obtained, including: The compensation scenario information is extracted from the compensation element information, and the corresponding compensation review and verification rules are obtained based on the compensation scenario information. The compensation review and verification rules are set using the factory pattern for different compensation scenarios.

10. A processing device for e-commerce compensation business, characterized in that, include: The request receiving module is used to respond to a user-initiated compensation request and obtain compensation element information, which includes compensation parameters; The data acquisition module is used to determine the compensation amount calculation formula through a pre-trained large model based on the compensation element information, and send the compensation amount calculation formula to customer service for verification. The compensation amount calculation module is used to calculate the compensation amount based on the target compensation amount calculation formula verified by customer service and the compensation parameters, and to generate a compensation application form based on the compensation amount; The e-commerce compensation module is used to process e-commerce compensation based on the compensation application form.

11. An electronic device, characterized in that, include: One or more processors; Storage device for storing one or more programs. When the one or more programs are executed by the one or more processors, the one or more processors implement the method as described in any one of claims 1-9.

12. A computer-readable medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the method as described in any one of claims 1-9.

13. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by a processor, it implements the method as described in any one of claims 1-9.

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