A method and system for collaborative processing of service data based on dual-channel synchronization

Abstract

The application discloses a kind of based on double channel synchronization's service data collaborative processing method and system, it is related to computer technology field, solve the problem that rebate system user experience is poor, the click rate and conversion rate of right and interests link are low.The method comprises: detecting the user payment success event in first channel system, record the user ID corresponding to the user payment success event;According to the user ID, the scene characteristic data of current user is collected, and the scene characteristic data at least includes site information, time information, user basic information and user historical behavior label;The scene characteristic data is input to the attention model trained in advance, and the target right and interests platform with the highest matching degree of current scene is calculated and output by the attention model;The target right and interests link of the target right and interests platform is pushed to the client of user.

Description

Technical Field

[0001] This invention relates to the field of computer technology, and in particular to a method and system for collaborative processing of business data based on dual-channel synchronization. Background Technology

[0002] Currently, CPS (Cost Per Sales) based revenue sharing technology is widely used. Under the CPS model, promoters (such as cashback platforms and shopping guide websites) promote product or service links on e-commerce platforms (such as Taobao, JD.com, Meituan, Ele.me, etc.), guiding users to complete transactions and receiving a percentage of commission from the e-commerce platform. Currently, various types of CPS cashback platforms exist in the market, such as cashback websites, What's Worth Buying, and various coupon aggregation apps.

[0003] However, the existing CPS cashback platforms mentioned above have the following significant shortcomings in terms of technical implementation and business model:

[0004] Existing cashback platforms typically employ a passive distribution model of "user-initiated browsing and self-clicking." This means users browse various products or coupons within the platform and then manually click on links to benefits they are interested in. The platform itself does not proactively perceive the user's current context (such as time, location, or ongoing business activities) or assess their potential needs. Consequently, the correlation between recommended benefits and the user's real-time situation is weak. This fixed, context-insensitive distribution method forces users to sift through massive amounts of irrelevant benefit information, resulting in a poor user experience and low click-through and conversion rates for benefit links. Summary of the Invention

[0005] In view of this, this application provides an adaptive benefits distribution method, apparatus, server, and storage medium to solve the problems of poor user experience and low click-through rate and conversion rate of benefits links in rebate systems.

[0006] This application provides an adaptive rights distribution method in its first aspect, the method comprising:

[0007] Upon detecting a successful user payment event within the first channel system, the user ID corresponding to the successful user payment event is recorded.

[0008] The scene feature data of the current user is collected based on the user ID. The scene feature data includes at least the venue information, time information, basic user information, and user historical behavior tags.

[0009] The scene feature data is input into a pre-trained attention model, which calculates and outputs the target rights platform that best matches the current scene.

[0010] The target benefits link of the target benefits platform is pushed to the user's client.

[0011] In one possible implementation, the method further includes:

[0012] Configure multiple interfaces to obtain a second-channel system;

[0013] Pushing the target benefits link of the target benefits platform to the user's client includes:

[0014] The target benefits link of the target benefits platform is pushed to the user's client through the second channel system.

[0015] In one possible implementation, the target rights link of the target rights platform is pushed to the user's client via the second channel system, including:

[0016] Through the standardized adapter instance, the target CPS platform is requested and the target benefit link is obtained by following the interface protocol of the target CPS platform;

[0017] The target benefit link is pushed to the user's client.

[0018] In one possible implementation, after pushing the target benefits link of the target benefits platform to the user's client, the method further includes:

[0019] Once a user clicks on a benefit link, the system locates the storage location of the user's historical behavior tags by using the user identifier corresponding to the clicked benefit link.

[0020] Query the user ID at the tag storage location to obtain the storage address corresponding to the user's historical behavior tags that stored the user's clicks on the rights and benefits links;

[0021] Add a record of the user clicking the rights link at the storage address.

[0022] In one possible implementation, the standardized adapter instance requests and obtains the target benefits link from the target CPS platform according to the target CPS platform's interface protocol, including:

[0023] The rules engine performs risk control checks on the current user's request behavior.

[0024] When the risk control detection result triggers the preset abnormal interception condition, the request sent to the target CPS platform is intercepted, and a risk control interception prompt message is returned to the main business system;

[0025] When the risk control detection result does not trigger the preset abnormal interception conditions, the target benefit link is requested and obtained from the target CPS platform through the standardized adapter instance in accordance with the interface protocol of the target CPS platform.

[0026] A second aspect of this application provides an adaptive rights distribution apparatus, the apparatus comprising:

[0027] The detection module is used to record the user ID corresponding to the user payment success event when a successful user payment event is detected in the first channel system.

[0028] The data acquisition module is used to collect scene feature data of the current user based on the user ID. The scene feature data includes at least venue information, time information, basic user information, and user historical behavior tags.

[0029] The data calculation module is used to input the scene feature data into a pre-trained attention model, and the attention model calculates and outputs the target rights platform with the highest matching degree with the current scene;

[0030] The push module is used to push the target benefits link of the target benefits platform to the user's client.

[0031] In one possible implementation, the apparatus further includes:

[0032] The configuration module is used to configure multiple interfaces to obtain the second-channel system.

[0033] The push module is specifically used to push the target benefits link of the target benefits platform to the user's client through the second channel system.

[0034] In one possible implementation, the push module includes:

[0035] The request submodule is used to request and obtain the target benefit link from the target CPS platform through the standardized adapter instance, according to the interface protocol of the target CPS platform;

[0036] The push module is used to push the target benefit link to the user's client.

[0037] In one possible implementation, the apparatus includes:

[0038] The location module is used to detect when a user clicks on a benefit link and locate the storage location of the user's historical behavior tags by using the user identifier corresponding to the clicked benefit link.

[0039] The address acquisition module is used to query the user ID at the tag storage location and obtain the storage address corresponding to the user's historical behavior tag that stores the user's clicked rights link.

[0040] Add a module to add records of user clicks on the rights and benefits link at the storage address.

[0041] In one possible implementation, the request submodule is specifically used to: perform risk control detection on the current user's request behavior through a rules engine;

[0042] When the risk control detection result triggers the preset abnormal interception condition, the request sent to the target CPS platform is intercepted, and a risk control interception prompt message is returned to the main business system;

[0043] When the risk control detection result does not trigger the preset abnormal interception conditions, the target benefit link is requested and obtained from the target CPS platform through the standardized adapter instance in accordance with the interface protocol of the target CPS platform.

[0044] A third aspect of this application provides a server, comprising: a processor and a memory, the processor and the memory being connected via a communication bus; wherein the processor is configured to call and execute a program stored in the memory; and the memory is configured to store the program, the program being configured to implement the adaptive rights distribution method provided in the first aspect of this application.

[0045] A fourth aspect of this application provides a computer-readable storage medium storing computer-executable instructions for performing the adaptive rights distribution method provided in the first aspect of this application.

[0046] Compared to existing technologies, this application provides an adaptive benefits distribution method, apparatus, server, and storage medium. Its advantages are as follows: The adaptive benefits distribution method proposed in this application establishes a second-channel system, which configures interfaces for multiple consumer platforms. Through the second-channel system, benefits links from different platforms can be invoked, breaking down platform barriers between the main business platform and the rebate system. The system monitors the operation of the first-channel system. Upon detecting a successful user payment event within the first-channel system, it extracts user information and current scenario information. Using a pre-trained attention model, it predicts the target benefits platform that meets the user's current needs. The second-channel system then obtains the benefits link of the target benefits platform and sends it to the user's client, establishing a communication channel between the rebate platform and the regular consumption scenario, increasing the click-through rate and conversion rate of the benefits link. Simultaneously, after a user clicks on a benefits link, the system stores the click record and updates the input data of the attention model, enabling adaptive adjustment and updating of the basis for the attention model's prediction of the target benefits platform, thus improving the accuracy of the target benefits platform's output. Attached Figure Description

[0047] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of this application. For those skilled in the art, other drawings can be obtained based on the provided drawings without creative effort.

[0048] Figure 1 This is a flowchart illustrating the steps of the adaptive rights distribution method proposed in the embodiments of this application;

[0049] Figure 2 This is an example of an interaction sequence diagram for pushing target benefit links in this application;

[0050] Figure 3 This is a functional block diagram of the adaptive rights distribution device proposed in the embodiments of this application. Detailed Implementation

[0051] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of this application.

[0052] In this application, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes the element.

[0053] Figure 1 This is a flowchart illustrating the steps of the adaptive rights distribution method proposed in this application, applied to a server, such as... Figure 1 As shown, the steps include:

[0054] S101: A successful user payment event is detected in the first channel system, and the user ID corresponding to the successful user payment event is recorded.

[0055] In one example, the system server receives an HTTP network request message from the payment platform stating "User XXXX's YY amount received." After the first-channel system successfully modifies the hard drive, it submits a transaction commit instruction to the database. The database records the successful transaction and returns a "confirmation message." Upon receiving the "confirmation message," the first-channel system sends a JSON message to the asynchronous communication message queue. The system detects the JSON message submitted by the database after the user's successful payment; the JSON message includes the user ID, order number, payment amount, timestamp, etc.

[0056] The first channel system is the main business system, which refers to a digital platform or application system that provides core basic services to users. It possesses an independent user system, business processing flow, and data storage capabilities, and can complete the main operational loops for users within their business scenarios. The main business system includes, but is not limited to, parking management platforms, property management platforms, banking and financial clients, office collaboration systems, healthcare service platforms, food delivery platforms, and other various industry-specific vertical application systems.

[0057] The system server is the server of the first-tier system. For example, if the current software is a parking app, the first-tier system's server is the parking app's server; if the current software is a restaurant app, the first-tier system's server is the restaurant app's server. Therefore, detecting the JSON message submitted by the database after the user's payment is successful indicates that the user's payment was successful.

[0058] Asynchronous communication message queues can be used to store data generated during the operation of the first-channel system. Business data or event notifications generated in the first-channel system can be placed in the asynchronous communication message queue, such as order data, payment notifications, user information, logistics information notifications, etc.

[0059] Recording the user ID corresponding to the successful payment event is the first step in the rights distribution process. Therefore, the rights distribution process is triggered when the event is detected through the above step S101.

[0060] In one implementation, the application service of the first channel system and the second channel system are packaged into independent container images and deployed on the same physical server cluster via a container orchestration platform (such as Kubernetes). The application service of the first channel system and the second channel system run in their respective independent container instances, and communicate across containers via network protocols (such as HTTP / gRPC). When the container containing the second channel system exits or restarts abnormally, the application service container of the first channel system is unaffected, thereby ensuring the availability of the core functions of the first channel system.

[0061] S102: Collect the current user's scene feature data based on the user ID. The scene feature data includes at least the location information, time information, user basic information, and user historical behavior tags.

[0062] Site information may include one or more of the following types of data: location data, site information of the main business system, for example, if the main business system is a parking APP, the site information of the main business system is the location of the parking APP.

[0063] In one embodiment, the bound user ID and user historical behavior tags are stored in a relational database or an in-memory database, and the user historical behavior tags can be retrieved through the user ID.

[0064] User historical behavior tags include at least one or more of the following data types:

[0065] (a) User click behavior records in the first channel system distribution link

[0066] (b) Successful order records and payment conversion records after users are redirected to the target CPS platform via the benefit link.

[0067] (c) Records of the frequency of use, time of use and expiration of the rights and benefits claimed by the user.

[0068] (d) After the user's historical rights usage period, the first channel system generates a record of repurchase behavior.

[0069] User basic information includes at least one or more of the following: user age, user gender, user membership level, user registration duration, user's total historical spending, user device information, user's real-name authentication status, and user's frequently used city information.

[0070] S103: Input the scene feature data into a pre-trained attention model, and the attention model calculates and outputs the target rights platform with the highest matching degree with the current scene.

[0071] One example employs a multi-head self-attention network to establish an attention model. This model converts site information, time information, basic user information, and user historical behavior tags into feature vectors, which serve as input sequences for four modalities. The attention mechanism learns the interaction relationships between these features, ultimately outputting a matching score for each candidate rights platform. The specific training methods and computation processes for the attention model can refer to conventional methods in the field, and this application does not impose any limitations.

[0072] In one example, the location information is "underground parking lot of an office building in the city center," the time information is "12:08," the user's basic information includes "male, 28 years old, gold membership level," and the user's historical behavior tags include "15 clicks on group-buying links, 6 orders; 8 clicks on food delivery platform links, 2 orders; 1 click on e-commerce platform links, 0 orders." The location information, time information, user's basic information, and user historical behavior tags are converted into feature vectors. The attention model encodes these four feature vectors into fixed-dimensional vectors. These feature vectors are then input into the attention model, which performs attention weight allocation calculations, weighting and aggregating the four encoded features to obtain a comprehensive representation V_pool for the current scenario. The model predicts that "user historical behavior (high preference for food delivery)" is the dominant factor in this decision. Combined with the time signal of "12 noon," the comprehensive representation V_pool is pushed towards "instant food delivery consumption," outputting the target benefit platform as a specific food delivery platform.

[0073] S104: Push the target rights link of the target rights platform to the user's client.

[0074] This application embodiment provides a specific process for executing S104, which includes the following sub-steps:

[0075] S1041: Configure multiple interfaces to obtain a second-channel system.

[0076] The process of configuring multiple interfaces to obtain the second-channel system includes: detecting input commands, filling the user-input data into a pre-set configuration table, and creating metadata; creating metadata, which includes interface addresses, parameter mapping relationships, and signature rules; instantiating interface objects according to the metadata configuration content, and constructing the second-channel system. Input commands are entered by backend operations personnel via computer devices; for example, the input command could be a request to create an e-commerce platform.

[0077] The second channel system constructed in this application embodiment can be considered a CPS adapter engine, a middleware service component deployed on the server side, used to aggregate standardized interfaces of multiple heterogeneous CPS platforms (including but not limited to e-commerce platforms, food delivery platforms, ride-hailing platforms, and local life service platforms) to provide unified rights distribution capabilities for the main business system. The CPS adapter engine adopts a metadata-driven configurable architecture, and by maintaining the routing mapping relationship between platform identifiers and adapter instances, it realizes unified invocation, protocol conversion, and data adaptation of interfaces of different CPS platforms.

[0078] The interface address can represent the interface address of the e-commerce platform to be connected; the parameter mapping relationship represents the rules for converting the data format of the first channel system into the data format of the e-commerce platform; the signature rule represents the algorithm of the authentication code and the signature key for the request parameters sent by the system.

[0079] The above method obtains the second-channel system. This system can then use the interface objects within the second-channel system to call links from any registered e-commerce platform. For example, if e-commerce platform A registers in the second-channel system, its corresponding interface is interface object A. The system locates interface object A using the identifier of e-commerce platform A, and through interface object A, executes a network request interaction with the target e-commerce platform to retrieve the benefits link.

[0080] Because the engine is based on metadata, when a new consumer platform needs to be added: there is no need to modify the underlying Java code of the engine; there is no need to recompile, repackage, or deploy; the operators only need to fill in the platform's interface address, parameter mapping relationship, and signature rules in the backend, and the data of the platform can be obtained through the second channel system.

[0081] S1042: The target rights link of the target rights platform is pushed to the user's client through the second channel system.

[0082] Using the methods described above, the second channel system has interfaces for various consumer platforms, such as e-commerce platforms and food delivery platforms. Therefore, by building a value-added service system through the second channel system, it is possible to obtain the rights and interests links of any platform registered in the second channel system. When an interface of a certain consumer platform times out or becomes unavailable, the engine failure is limited to the adapter instance of that platform and will not disrupt the core payment process of the first channel system.

[0083] Executing S1042, through the second channel system, pushes the target rights link of the target rights platform to the user's client, including the following steps:

[0084] M11: Through the standardized adapter instance, in accordance with the interface protocol of the target CPS platform, request and obtain the target rights link from the target CPS platform;

[0085] M12: Push the target benefit link to the user's client.

[0086] One example of this application is to effectively identify and block high-frequency, abnormal requests with non-human behavioral characteristics, thereby eliminating the ineffective consumption of marketing funds caused by malicious order brushing and machine arbitrage. An interception layer is set up, and the rule engine is automatically run through the interception layer to detect whether the user's IP is abnormal and whether the order frequency is too high. If risk control is triggered, the request is automatically blocked, eliminating the need for programmers to repeatedly write if statements in every business method.

[0087] Execution step M12, through the standardized adapter instance, requests and obtains the target rights link from the target CPS platform according to the interface protocol of the target CPS platform, including performing the following sub-steps:

[0088] M121: Performs risk control detection on the current user's request behavior through the rules engine.

[0089] The risk control detection includes at least one of IP anomaly detection and request frequency anomaly detection.

[0090] M122: When the risk control detection result triggers the preset abnormal interception condition, the request sent to the target CPS platform is intercepted, and a risk control interception prompt message is returned to the main business system.

[0091] M123: When the risk control detection result does not trigger the preset abnormal interception condition, the target benefit link is requested and obtained from the target CPS platform through the standardized adapter instance in accordance with the interface protocol of the target CPS platform.

[0092] The rule engine triggers an exception interception condition when any one or more of the following conditions are met:

[0093] (a) Within a preset time window T, the number of rights distribution requests N from the same client IP address exceeds a preset threshold K (e.g., the time window T can be 60 seconds, 30 seconds, etc.).

[0094] (b) Within a preset time window T, the number of rights requests triggered by the same user ID across the entire platform exceeds a preset threshold L;

[0095] (c) The client's IP address hits the abnormal IP blacklist maintained locally by the system.

[0096] Figure 2 This is an example of an interaction sequence diagram for pushing target benefit links in this application, such as... Figure 2 As shown,

[0097] K11: The first channel system calls the interface of the target rights platform from the second channel system.

[0098] K12: The second channel system reads metadata, which includes interface address, parameter mapping relationship, and signature rules.

[0099] K13: The second channel system constructs request parameters according to the parameter mapping relationship and signs the request parameters according to the signature rules.

[0100] K14: Send request parameters to the target rights platform via HTTP POST according to the interface address.

[0101] K15: The target rights platform returns a rights link to the second channel system.

[0102] K16: The second channel system forwards the target rights link to the first channel system.

[0103] K17: The first channel system recommends the target benefits link to the user's client.

[0104] This application embodiment provides another process for executing an adaptive rights distribution method, the steps of which include:

[0105] S201: A successful user payment event is detected in the first channel system, and the user ID corresponding to the successful user payment event is recorded.

[0106] S202: Collect the current user's scene feature data based on the user ID. The scene feature data includes at least the location information, time information, user basic information, and user historical behavior tags.

[0107] S203: Input the scene feature data into a pre-trained attention model, and the attention model calculates and outputs the target rights platform with the highest matching degree with the current scene.

[0108] S204: Push the target benefits link of the target benefits platform to the user's client.

[0109] S205: The system detects that a user clicked on a benefits link. The system locates the storage location of the user's historical behavior tags by using the user identifier corresponding to the clicked benefits link.

[0110] S206: Query the user ID at the tag storage location to obtain the storage address corresponding to the user's historical behavior tags that the user clicked on the rights and benefits link.

[0111] S207: Add a record of the user clicking the rights link at the storage address.

[0112] Tag storage can be in a relational database or an in-memory database. At the storage location, the user ID from the first-channel system is bound to the user's mobile phone number and a third-party user identifier. This allows the system to find the user ID using the user identifier, locate the storage location of the user's historical behavior tags, update the historical behavior tags, and enrich the input data for the attention model's next calculation of the target benefit platform. This increases the reliability of the attention model's output and ensures that the system's recommended target benefit platform better meets the user's needs. On the other hand, by binding the user ID to the user's mobile phone number and a third-party user identifier, a unified, unique user identification system is constructed across the entire chain. This enables continuous collection, correlation analysis, and deep reuse of user behavior data throughout the entire lifecycle, from primary business consumption to benefit usage and repeat purchases, improving benefit matching accuracy without requiring manual export / import processing.

[0113] The adaptive benefits distribution method proposed in this application, upon detecting a successful user payment event within the first-channel system, obtains the user ID to acquire data corresponding to the user's consumption habits, basic user information, and historical behavior tags. Based on the user's consumption habits and the current scenario within the first-channel system, it intelligently matches the target benefits platform to the user's needs, obtains the benefits link of the target platform, and pushes it to the user, increasing the probability of the user clicking on the benefits link. This process does not require manual verification. Because the attention model can dynamically learn the different weights of different scenario features (such as time and location) on the user's benefits preferences, the benefits recommendation results possess both scenario adaptability and individual personalization capabilities. Compared to fixed-rule benefits delivery methods, this significantly improves the probability of users clicking on the pushed benefits link and the subsequent conversion rate, thereby enhancing the efficiency of the first-channel system through the CPS model.

[0114] Adding records of users clicking on the benefits link in the storage address can serve as the basis for issuing benefits to users, solving the problem of repetitive operations such as manually exporting CPS platform bills, manually verifying order status, and manually updating user profile tags in the traditional model.

[0115] The adaptive benefits distribution method proposed in this application establishes a second-channel system. This second-channel system configures interfaces for multiple consumer platforms, allowing access to benefits links from different platforms and breaking down platform barriers between the main business platform and the rebate system. The system monitors the operation of the first-channel system. Upon detecting a successful user payment event within the first-channel system, it extracts user information and current scenario information. Using a pre-trained attention model, it predicts a target benefits platform that meets the user's current needs. The second-channel system then retrieves the benefits link of the target platform and sends it to the user's client, establishing a communication channel between the rebate platform and the regular consumption scenario, increasing the click-through rate and conversion rate of the benefits link. Simultaneously, after a user clicks a benefits link, the system stores the click record and updates the input data of the attention model, enabling adaptive adjustments and updates to the basis for the attention model's prediction of the target benefits platform, thus improving the accuracy of the target benefits platform's output.

[0116] Example 2

[0117] Based on the adaptive rights distribution method provided in Embodiment 1 of this application, Embodiment 2 of this application also provides an adaptive rights distribution device. Figure 3 This is a functional block diagram of the adaptive rights distribution device proposed in the embodiments of this application, such as... Figure 3 As shown, the device includes:

[0118] The detection module 301 is used to record the user ID corresponding to the user payment success event when a user payment success event is detected in the first channel system.

[0119] The acquisition module 302 is used to acquire scene feature data of the current user based on the user ID. The scene feature data includes at least venue information, time information, user basic information and user historical behavior tags.

[0120] The data calculation module 303 is used to input the scene feature data into a pre-trained attention model, and the attention model calculates and outputs the target rights platform with the highest matching degree with the current scene;

[0121] The push module 304 is used to push the target rights link of the target rights platform to the user's client.

[0122] In one possible implementation, the device further includes:

[0123] The configuration module is used to configure multiple interfaces to obtain the second-channel system.

[0124] The push module is specifically used to push the target benefits link of the target benefits platform to the user's client through the second channel system.

[0125] In one possible implementation, the push module includes:

[0126] The request submodule is used to request and obtain the target benefit link from the target CPS platform through the standardized adapter instance, according to the interface protocol of the target CPS platform;

[0127] The push module is used to push the target benefit link to the user's client.

[0128] In one possible implementation, the apparatus includes:

[0129] The location module is used to detect when a user clicks on a benefit link and locate the storage location of the user's historical behavior tags by using the user identifier corresponding to the clicked benefit link.

[0130] The address acquisition module is used to query the user ID at the tag storage location and obtain the storage address corresponding to the user's historical behavior tag that stores the user's clicked rights link.

[0131] Add a module to add records of user clicks on the rights and benefits link at the storage address.

[0132] In one possible implementation, the request submodule is specifically used to: perform risk control detection on the current user's request behavior through a rules engine;

[0133] When the risk control detection result triggers the preset abnormal interception condition, the request sent to the target CPS platform is intercepted, and a risk control interception prompt message is returned to the main business system;

[0134] When the risk control detection result does not trigger the preset abnormal interception conditions, the target benefit link is requested and obtained from the target CPS platform through the standardized adapter instance in accordance with the interface protocol of the target CPS platform.

[0135] Example 3

[0136] Embodiment 3 of this application provides a server, including: a processor and a memory, the processor and the memory being connected via a communication bus; wherein, the processor is used to call and execute a program stored in the memory; the memory is used to store the program, the program being used to implement the adaptive rights distribution method provided in Embodiment 1 of this application.

[0137] Example 4

[0138] Embodiment 4 of this application provides a computer-readable storage medium storing computer-executable instructions for executing the adaptive rights distribution method provided in Embodiment 1 of this application.

[0139] Those skilled in the art will further recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, computing software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the components and steps of the various examples have been generally described in terms of functionality in the foregoing description. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0140] Although preferred embodiments of the invention have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including both the preferred embodiments and all changes and modifications falling within the scope of the invention.

[0141] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.

Claims

1. An adaptive rights distribution method, characterized in that, Applied to a server, the method includes: Upon detecting a successful user payment event within the first channel system, the user ID corresponding to the successful user payment event is recorded. The scene feature data of the current user is collected based on the user ID. The scene feature data includes at least the venue information, time information, basic user information, and user historical behavior tags. The scene feature data is input into a pre-trained attention model, which calculates and outputs the target rights platform that best matches the current scene. The target benefits link of the target benefits platform is pushed to the user's client.

2. The method according to claim 1, characterized in that, The method further includes: Configure multiple interfaces to obtain a second-channel system; Pushing the target benefits link of the target benefits platform to the user's client includes: The target benefits link of the target benefits platform is pushed to the user's client through the second channel system.

3. The method according to claim 2, characterized in that, Through the second channel system, the target benefits link of the target benefits platform is pushed to the user's client, including: Through the standardized adapter instance, the target CPS platform is requested and the target benefit link is obtained by following the interface protocol of the target CPS platform; The target benefit link is pushed to the user's client.

4. The method according to claim 1, characterized in that, After pushing the target benefits link of the target benefits platform to the user's client, the method further includes: Once a user clicks on a benefit link, the system locates the storage location of the user's historical behavior tags by using the user identifier corresponding to the clicked benefit link. Query the user ID at the tag storage location to obtain the storage address corresponding to the user's historical behavior tags that stored the user's clicks on the rights and benefits links; Add a record of the user clicking the rights link at the storage address.

5. The method according to claim 3, characterized in that, Through the standardized adapter instance, and in accordance with the interface protocol of the target CPS platform, the system requests and obtains the target benefits link from the target CPS platform, including: The rules engine performs risk control checks on the current user's request behavior. When the risk control detection result triggers the preset abnormal interception condition, the request sent to the target CPS platform is intercepted, and a risk control interception prompt message is returned to the main business system; When the risk control detection result does not trigger the preset abnormal interception conditions, the target benefit link is requested and obtained from the target CPS platform through the standardized adapter instance in accordance with the interface protocol of the target CPS platform.

6. An adaptive rights distribution device, characterized in that, The device, located on a server, includes: The detection module is used to record the user ID corresponding to the user payment success event when a successful user payment event is detected in the first channel system. The data acquisition module is used to collect scene feature data of the current user based on the user ID. The scene feature data includes at least venue information, time information, basic user information, and user historical behavior tags. The data calculation module is used to input the scene feature data into a pre-trained attention model, and the attention model calculates and outputs the target rights platform with the highest matching degree with the current scene; The push module is used to push the target benefits link of the target benefits platform to the user's client.

7. The apparatus according to claim 6, characterized in that, The device further includes: The configuration module is used to configure multiple interfaces to obtain the second-channel system. The push module is specifically used to push the target benefits link of the target benefits platform to the user's client through the second channel system.

8. The apparatus according to claim 7, characterized in that, The push module includes: The request submodule is used to request and obtain the target benefit link from the target CPS platform through the standardized adapter instance, according to the interface protocol of the target CPS platform; The push module is used to push the target benefit link to the user's client.

9. The apparatus according to claim 6, characterized in that, The device includes: The location module is used to detect when a user clicks on a benefit link and locate the storage location of the user's historical behavior tags by using the user identifier corresponding to the clicked benefit link. The address acquisition module is used to query the user ID at the tag storage location and obtain the storage address corresponding to the user's historical behavior tag that stores the user's clicked rights link. Add a module to add records of user clicks on the rights and benefits link at the storage address.

10. The apparatus according to claim 8, characterized in that, The request submodule is specifically used to: perform risk control detection on the current user's request behavior through the rule engine; When the risk control detection result triggers the preset abnormal interception condition, the request sent to the target CPS platform is intercepted, and a risk control interception prompt message is returned to the main business system; When the risk control detection result does not trigger the preset abnormal interception conditions, the target benefit link is requested and obtained from the target CPS platform through the standardized adapter instance in accordance with the interface protocol of the target CPS platform.

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