A resource allocation method and device, a server and a storage medium

Abstract

Embodiments of the present application disclose a resource allocation method and device, a server and a storage medium, and relate to the technical field of computers. The method comprises: obtaining the demand degree and user characteristics of a user to be allocated in a current service, inputting the demand degree and user characteristics of the user to be allocated into a pre-trained resource type determination model, so that the resource type determination model determines the resource type of the user to be allocated; determining the resource allocation amount of the user to be allocated according to the total amount of resources, the resource type and the demand degree and user characteristics of the user to be allocated in the current service; and allocating resources corresponding to the resource allocation amount to the user to be allocated in a form corresponding to the resource type. The above technical solution allocates resources corresponding to the resource allocation amount that is more matched to the user to be allocated to the user to be allocated in a form corresponding to the resource type that is more matched to the user to be allocated, thereby realizing accurate allocation of resources, improving user experience, and further improving the probability of the user using the resources to perform the current service.

Description

Technical Field

[0001] The present invention relates to the field of computer technology, and in particular to a resource allocation method, apparatus, server and storage medium. Background Technology

[0002] When service providers allocate service resources, they often face resource shortages. Therefore, how to rationally allocate resources under such circumstances becomes an urgent problem to be solved.

[0003] In existing technologies, when resources are insufficient, a random allocation method can usually be used to distribute resources to users.

[0004] In the process of realizing this invention, the inventors discovered at least the following technical problems in the prior art:

[0005] The allocation of resources is neither reasonable nor fair, making it difficult to meet the personalized needs of different users. Summary of the Invention

[0006] This invention provides a resource allocation method, apparatus, server, and storage medium to achieve rational allocation of resources.

[0007] In a first aspect, embodiments of the present invention provide a resource allocation method, including:

[0008] Obtain the demand level and user characteristics of users to be assigned in the current business, and input the demand level and user characteristics of users to be assigned into a pre-trained resource type determination model so that the resource type determination model can determine the resource type of the users to be assigned.

[0009] Based on the total amount of resources for the current business, the resource type, and the demand and characteristics of the users to be allocated, determine the resource allocation amount for the users to be allocated;

[0010] The resources corresponding to the resource allocation amount are allocated to the users to be allocated in the form corresponding to the resource type.

[0011] Secondly, embodiments of the present invention also provide a resource allocation device, comprising:

[0012] The acquisition module is used to acquire the demand and user characteristics of users to be assigned in the current business, and input the demand and user characteristics of the users to be assigned into a pre-trained resource type determination model so that the resource type determination model can determine the resource type of the users to be assigned.

[0013] The determination module is used to determine the resource allocation amount for the user to be allocated based on the total resource amount of the current business, the resource type, and the demand and user characteristics of the user to be allocated.

[0014] The allocation module is used to allocate the resources corresponding to the resource allocation amount to the users to be allocated in the form corresponding to the resource type.

[0015] Thirdly, embodiments of the present invention also provide a server, the server comprising:

[0016] One or more processors;

[0017] Storage device for storing one or more programs.

[0018] When the one or more programs are executed by the one or more processors, the one or more processors implement the resource allocation method as described in any of the first aspects.

[0019] Fourthly, embodiments of the present invention also provide a storage medium containing computer-executable instructions, characterized in that the computer-executable instructions, when executed by a computer processor, are used to perform the resource allocation method as described in any of the first aspects.

[0020] The embodiments of the above invention have the following advantages or beneficial effects:

[0021] This invention provides a resource allocation method, comprising: acquiring the demand level and user characteristics of users to be allocated in the current business; inputting the demand level and user characteristics of users to be allocated into a pre-trained resource type determination model, so that the resource type determination model determines the resource type of the users to be allocated; determining the resource allocation amount of the users to be allocated based on the total resource amount of the current business, the resource type, and the demand level and user characteristics of the users to be allocated; and allocating the resources corresponding to the resource allocation amount to the users to be allocated in a form corresponding to the resource type. The above technical solution firstly determines a resource type more suitable for the users to be allocated based on their demand level and user characteristics in the current business; secondly, it determines a resource allocation amount more suitable for the users to be allocated based on the total resource amount of the current business, the resource type of the users to be allocated, and the demand level and user characteristics of the users to be allocated; and then allocates the resources corresponding to the resource allocation amount more suitable for the users to be allocated to the users in a form corresponding to the resource type more suitable for the users to be allocated, thereby achieving precise resource allocation, improving user experience, increasing the probability of users using resources, and increasing the probability of users using resources to perform the current business, further promoting the current business. Attached Figure Description

[0022] Figure 1 A flowchart of a resource allocation method provided in an embodiment of the present invention;

[0023] Figure 2 A flowchart of another resource allocation method provided in an embodiment of the present invention;

[0024] Figure 3 This is a schematic diagram of the structure of a resource allocation device provided in an embodiment of the present invention;

[0025] Figure 4 This is a schematic diagram of the structure of a server provided in an embodiment of the present invention. Detailed Implementation

[0026] The present invention will now be described in further detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and not intended to limit it. Furthermore, it should be noted that, for ease of description, the accompanying drawings show only the parts relevant to the present invention, and not all of the structures.

[0027] Before discussing the exemplary embodiments in more detail, it should be noted that some exemplary embodiments are described as processes or methods depicted as flowcharts. Although the flowcharts describe the operations (or steps) as sequential processes, many of these operations can be performed in parallel, concurrently, or simultaneously. Furthermore, the order of the operations can be rearranged. The process can be terminated when its operation is completed, but may also have additional steps not included in the figures. The process can correspond to a method, function, procedure, subroutine, subroutine, etc. Moreover, embodiments and features in the embodiments of the present invention can be combined with each other without conflict.

[0028] When conducting promotional activities, trading websites often face the problem of insufficient marketing rights resources. Since trading websites have multiple businesses, these marketing rights resources can be understood as business resources. How to rationally allocate resources when they are insufficient becomes a pressing issue. Existing technologies typically employ allocation methods such as queuing order, random allocation, and allocation based on reputation level to distribute resources to users. On the one hand, a queuing mechanism can be used. When resources are insufficient, users are queued according to their waiting time, and when new resources are released, they are allocated to users in the queue order. This solution can avoid excessive consumption of resources, but the user experience is poor because users have to wait for a period of time to obtain resources. On the other hand, a random allocation mechanism can be used. When resources are insufficient, the remaining resources are randomly allocated to users. This solution can avoid resource waste, but lacks fairness and may cause user dissatisfaction. Finally, a reputation-based allocation mechanism can be used. When resources are insufficient, they can be allocated according to users' reputation levels. Users with higher reputation levels are more likely to receive more resources. This solution can incentivize users to conduct business transactions based on their better reputation levels, while also avoiding resource waste.

[0029] The aforementioned resource allocation methods all lack data-driven decision support: they lack sufficient data mining and utilization, and cannot adjust resource allocation in real time based on user behavior and feedback, resulting in inaccurate and inefficient resource allocation. They also fail to meet the needs of diverse channels and personalization: providing only a single, standardized solution makes it difficult to meet the personalized needs of different channels and user groups, and thus cannot achieve refined resource allocation.

[0030] Therefore, this application proposes a resource allocation method to achieve reasonable allocation of resources and improve user experience.

[0031] The resource allocation method proposed in this application will be described in detail below with reference to the illustrations and embodiments.

[0032] Figure 1 This is a flowchart illustrating a resource allocation method provided by an embodiment of the present invention. This embodiment is applicable to situations requiring reasonable resource allocation. The method can be executed by a resource allocation device, which can be implemented in software and / or hardware. Figure 1 The method specifically includes the following steps:

[0033] Step 110: Obtain the demand level and user characteristics of the users to be assigned in the current business, and input the demand level and user characteristics of the users to be assigned into the pre-trained resource type determination model so that the resource type determination model can determine the resource type of the users to be assigned.

[0034] In this context, users to be allocated can be understood as users whose resources are to be allocated under the current business. Users to be allocated can be determined based on the credit rating of each user under the current business, or based on the activity level of each user under the current business, without any specific restrictions here.

[0035] User demand can be understood as the degree to which users need marketing resources, which can be determined based on the number of times users are allocated resources and the number of times they use those resources. User characteristics can include at least location information, behavioral sequences, lifecycle, and reputation information. The lifecycle can include new user registration, interaction conversion, repeat purchase, or churn and return. Resources can be understood as promotional resources, and resource types can include direct discounts, discounts for purchases over a certain amount, tiered discounts, restrictions on item ownership, restrictions on product category, restrictions on brand, restrictions on item type, etc.

[0036] Specifically, the first step is to identify the users to be assigned in the current business process. This process requires understanding the demand level of each user within the current business. Therefore, after identifying the users to be assigned, their demand levels and user characteristics can be obtained. These demand levels and user characteristics are then input into a pre-trained resource type determination model. This model is trained based on the demand levels and user characteristics of multiple users, as well as the actual resource types. After inputting the demand levels and user characteristics, it outputs the resource type, thus revealing the resource type for each user to be assigned.

[0037] The resource type determination model can determine the resource type of the user to be assigned by referring to the user's demand and user characteristics, so that the determined resource type of the user to be assigned is more matched with the user to be assigned.

[0038] In this embodiment of the invention, the resource type of the user to be assigned is determined based on the demand and user characteristics of the user to be assigned in the current business, so that the resource type of the determined user to be assigned is more matched with the user to be assigned, thereby improving the user experience and further increasing the probability of the user using the resource.

[0039] Step 120: Determine the resource allocation amount for the user to be allocated based on the total resource amount of the current service, the resource type, and the demand and user characteristics of the user to be allocated.

[0040] The total amount of resources for the current business can be understood as the total amount of the discount. The resource allocation amount can be understood as the discount amount; for example, when the resource type is a discount based on purchase amount, the resource allocation amount can be the discount amount.

[0041] User characteristics may also include the time a user spends focusing on current business, the user's usage of historical resources, and the user's execution of historical business.

[0042] Specifically, firstly, the total resource allocation for each resource type can be determined based on the current total resource volume. Then, based on the total resource allocation for each resource type, the demand of users to be allocated resources, the time users spend focusing on the current business, users' historical resource usage, and users' historical business execution, the resource allocation for each user to be allocated can be determined. This determined total resource allocation for users to be allocated at this stage attracts users to use resources while keeping the current business's resource utilization rate at a low level.

[0043] Of course, the amount of resources allocated to a user to be assigned shall not exceed the resource allocation range of the user's resource type.

[0044] In this embodiment of the invention, the resource allocation amount for each user to be allocated is determined based on the total amount of resources for the current business, the resource type of the user to be allocated, and the user's demand and characteristics. This ensures that the determined resource allocation amount for each user to be allocated can attract the user to use resources to execute the current business, thereby increasing the probability of the current business being executed.

[0045] Step 130: Allocate the resources corresponding to the resource allocation amount to the users to be allocated in the form corresponding to the resource type.

[0046] Specifically, after determining the resource type and resource allocation amount for the user to be assigned, the resources corresponding to the resource allocation amount can be allocated to the user to be assigned in the form of corresponding resource types, thereby realizing resource allocation. Furthermore, the resource type and resource allocation amount allocated to the user to be assigned are matched with the user to be assigned, thus achieving accurate resource allocation.

[0047] In this embodiment of the invention, resources corresponding to the resource allocation amount matched with the user to be allocated are allocated to the user in a form that matches the resource type matched with the user to be allocated. This achieves accurate resource allocation, improves user experience, and increases the probability that the user will use the resources to perform the current business, thereby further promoting the current business.

[0048] The resource allocation method provided in this invention includes: obtaining the demand level and user characteristics of users to be allocated in the current business; inputting the demand level and user characteristics of users to be allocated into a pre-trained resource type determination model, so that the resource type determination model determines the resource type of the users to be allocated; determining the resource allocation amount of the users to be allocated based on the total resource amount of the current business, the resource type, and the demand level and user characteristics of the users to be allocated; and allocating the resources corresponding to the resource allocation amount to the users to be allocated in a form corresponding to the resource type. This technical solution firstly determines a resource type that is more suitable for the users to be allocated based on their demand level and user characteristics in the current business; secondly, it determines a resource allocation amount that is more suitable for the users to be allocated based on the total resource amount of the current business, the resource type of the users to be allocated, and the demand level and user characteristics of the users to be allocated; and then it allocates the resources corresponding to the resource allocation amount that is more suitable for the users to be allocated to the users in a form corresponding to the resource type that is more suitable for the users to be allocated, thereby achieving accurate resource allocation, improving user experience, increasing the probability of users using resources, and increasing the probability of users using resources to perform the current business, further promoting the current business.

[0049] Figure 2This is a flowchart of another resource allocation method provided by an embodiment of the present invention, which is applicable to situations requiring reasonable resource allocation. Based on the above embodiments, before obtaining the demand level and user characteristics of users to be allocated in the current business, this embodiment adds the following steps: "Obtaining user characteristics and user behavior data of each user in the current business; determining the demand level of each user based on the user behavior data, and determining the users to be allocated based on the resource allocation rules of the current business, the demand level of each user, and the user characteristics." It also adds the step of "Determining the resource usage of the current business based on the usage of the allocated resources by each user to be allocated." Furthermore, it includes the training process for the resource type determination model and the demand level determination model. Explanations of terms that are the same as or corresponding to those in the above embodiments are not repeated here. See also Figure 2 The resource allocation method provided in this embodiment of the invention includes:

[0050] Step 210: Obtain user characteristics and user behavior data for each user in the current business.

[0051] User behavior data can include user access to current services, user acquisition of various resource types within the current services, and user execution of current services based on resources of each resource type.

[0052] Specifically, user characteristics can include basic characteristics and behavioral characteristics. Basic characteristics can include at least location information and lifecycle, which can include new user acquisition / registration, interaction conversion, order repurchase, or churn / return. Behavioral characteristics can be understood as the sequence of behaviors and reputation information generated by users during the execution of the current business. The behavioral sequence consists of multiple user behavior data, which can be obtained through event tracking in the current business. The current business can record user information for each user accessing the current business; therefore, user characteristics can be determined based on the user information and user behavior data recorded by the current business.

[0053] In this embodiment of the invention, user characteristics and user behavior data of each user in the current business are obtained.

[0054] Step 220: Determine the demand level of each user based on their user behavior data.

[0055] In one implementation, step 220 may specifically include:

[0056] The user behavior data of each user is input into a pre-trained demand determination model so that the demand determination model can determine the demand of each user.

[0057] Specifically, user behavior data of each user can be input into a pre-trained demand determination model. The demand determination model is trained based on user behavior data of multiple users and the actual demand. After inputting user behavior data, it can output the demand degree. Therefore, the demand degree of each user can be obtained.

[0058] Demand models can determine a user's demand level based on user behavior data, making the determined demand level more accurate.

[0059] Furthermore, the training process of the demand determination model includes:

[0060] Acquire user behavior data from multiple users, and determine the actual demand level of each user based on the resource acquisition and resource usage data in the user behavior data; use the user behavior data as training input and the demand level of the user as the training output to train the network and obtain the demand level determination model.

[0061] Resource allocation data can be understood as behavioral data generated by users clicking on allocated resources, while resource usage data can be understood as behavioral data generated by users using allocated resources. The ratio of resource usage data to resource allocation data can determine the user's true demand level. Therefore, we can first obtain user behavior data from multiple business units, and determine the user's true demand level based on the ratio of resource usage data to resource allocation data in each user's behavior data, thus preparing training data. Furthermore, the user behavior data and true demand level of each user can be used as training data to train a neural network model. Specifically, user behavior data can be used as training input, and the demand level can guide the training output to obtain a demand level determination model.

[0062] In this embodiment of the invention, the demand level of each user is determined based on the user behavior data of each user in the current business.

[0063] Step 230: Determine the users to be allocated based on the resource allocation rules of the current business, the demand level of each user, and user characteristics.

[0064] In one implementation, step 230 may specifically include:

[0065] Users whose user characteristics in the current business match the resource allocation rules, and / or whose demand meets preset conditions, are identified as the users to be allocated.

[0066] The resource allocation rules can be pre-set by the current business operations personnel to determine the users to be allocated resources. These rules can include preset credit ratings, preset regions, and preset demand ranges. The resource allocation rules also include restrictions on duplicate allocations, such as preventing duplicate allocations based on user identifiers, device identifiers, financial accounts, and contact information. Furthermore, multiple dimensions can be used individually or in combination.

[0067] Specifically, user characteristics and resource allocation rules can be compared among users to identify those whose characteristics match the rules. Users whose needs are within the preset range can also be identified as potential users. Alternatively, users whose needs both match the rules and whose needs fall within the preset range can also be identified as potential users.

[0068] In this embodiment of the invention, the user to be assigned in the current business is determined, that is, the object to which resources are allocated in the current business.

[0069] Step 240: Obtain the demand level and user characteristics of the users to be assigned in the current business, and input the demand level and user characteristics of the users to be assigned into the pre-trained resource type determination model so that the resource type determination model can determine the resource type of the users to be assigned.

[0070] Specifically, the demand level and user characteristics of the users to be assigned are input into a pre-trained resource type determination model. The resource type determination model is trained based on the demand level and user characteristics of multiple users and the actual resource types. After inputting the demand level and user characteristics, it can output the resource type. Therefore, the resource type of the users to be assigned can be obtained.

[0071] The resource type determination model can determine the resource type of the user to be assigned by referring to the user's demand and user characteristics, so that the determined resource type of the user to be assigned is more matched with the user to be assigned.

[0072] Resources can be coupons, and resource types can be direct discounts, discounts for purchases over a certain amount, tiered discounts, restrictions on the type of item owner, restrictions on the type of product category, restrictions on the type of brand, restrictions on the type of item, etc. Therefore, resources can be coupons of the following types: direct discounts, discounts for purchases over a certain amount, tiered discounts, restrictions on the type of item owner, restrictions on the type of product category, restrictions on the type of brand, restrictions on the type of item, etc.

[0073] In one implementation, the training process of the resource type determination model includes:

[0074] Obtain the demand level, user characteristics, and actual resource types of multiple users; use the demand level and user characteristics of the users as training inputs and use the actual resource types of the users to guide the training output for network training to obtain the resource type determination model.

[0075] The neural network model is trained using the demand level, user characteristics, and actual resource type of each user to be assigned as training data. Specifically, the network can be trained using demand level and user behavior data as training input and resource type as the training output to obtain a resource type determination model.

[0076] In this embodiment of the invention, the resource type of each user to be assigned is determined based on the user's demand level and user characteristics.

[0077] Step 250: Determine the resource allocation amount for the user to be allocated based on the total resource amount of the current service, the resource type, and the demand and user characteristics of the user to be allocated.

[0078] In one implementation, step 250 may specifically include:

[0079] The total resource allocation amount for the resource type is determined based on the total resource amount; the resource allocation quantity is determined based on the total resource allocation amount, the demand level of the users to be allocated, and the user characteristics.

[0080] Specifically, firstly, the total resource allocation for each resource type can be determined based on the current total resource volume. Then, based on the total resource allocation for each resource type, the demand of users to be allocated resources, the time users spend focusing on the current business, users' historical resource usage, and users' historical business execution, the resource allocation for each user to be allocated can be determined. This determined total resource allocation for users to be allocated at this stage attracts users to use resources while keeping the current business's resource utilization rate at a low level.

[0081] Of course, the amount of resources allocated to a user to be assigned shall not exceed the resource allocation range of the user's resource type.

[0082] In this embodiment of the invention, the resource allocation amount for each user to be allocated is determined based on the total amount of resources for the current business, the resource type of the user to be allocated, and the user's demand and characteristics. This ensures that the determined resource allocation amount for each user to be allocated can attract the user to use resources to execute the current business, thereby increasing the probability of the current business being executed.

[0083] Step 260: Allocate the resources corresponding to the resource allocation amount to the users to be allocated in the form corresponding to the resource type.

[0084] Specifically, after determining the resource type and resource allocation amount for the user to be assigned, the resources corresponding to the resource allocation amount can be allocated to the user to be assigned in the form of corresponding resource types, thereby realizing resource allocation. Furthermore, the resource type and resource allocation amount allocated to the user to be assigned are matched with the user to be assigned, thus achieving accurate resource allocation.

[0085] Developing personalized promotional strategies for different users and allocating resources reasonably based on user characteristics and needs can improve promotional effectiveness and user satisfaction.

[0086] In this embodiment of the invention, resources corresponding to the resource allocation amount matched with the user to be allocated are allocated to the user in a form that matches the resource type matched with the user to be allocated. This achieves fair and accurate allocation of resources, while ensuring the effectiveness of resource allocation, improving user experience, and thus increasing the probability of users using resources to perform current business, thereby further promoting the current business.

[0087] Step 270: Determine the resource usage of the current service based on the usage of the allocated resources by each of the users to be assigned.

[0088] Specifically, the resource usage of the current business can be determined based on the usage of the allocated resources by each user to be assigned. Furthermore, the resource utilization rate of the current business can be determined based on the ratio of the current business's resource usage to the total resources, which facilitates real-time monitoring of the current business's resource usage by the operations personnel and further enables timely adjustments to the current business's promotion strategies.

[0089] In this embodiment of the invention, the promotion effect can be evaluated and optimized in real time through a real-time monitoring and feedback mechanism, thereby further improving the promotion effect and user satisfaction.

[0090] The resource allocation method provided in this embodiment of the invention includes: acquiring user characteristics and user behavior data of each user in the current service; determining the demand level of each user based on the user behavior data; determining the users to be allocated based on the resource allocation rules of the current service, the demand level of each user, and the user characteristics; acquiring the demand level and user characteristics of the users to be allocated in the current service, and inputting the demand level and user characteristics of the users to be allocated into a pre-trained resource type determination model, so that the resource type determination model determines the resource type of the users to be allocated; determining the resource allocation amount of the users to be allocated based on the total resources of the current service, the resource type, and the demand level and user characteristics of the users to be allocated; allocating the resources corresponding to the resource allocation amount to the users to be allocated in the form corresponding to the resource type; and determining the resource usage of the current service based on the usage of the allocated resources by each user to be allocated. The above technical solution first acquires user characteristics and behavior data of each user in the current business. Based on this data, it determines the demand level of each user. Then, based on the resource allocation rules, user demand, and user characteristics, it identifies the users to be allocated resources, thus determining the recipients of resources in the current business. Secondly, it determines the resource type that best matches the users based on their demand and characteristics. Then, based on the total resources of the current business, the resource types of the users to be allocated, and their demand and characteristics, it determines the resource allocation amount that best matches the users. Finally, it allocates the resources corresponding to the allocation amount best matched to the users, in the form of resource types best matched to the users, to the users. For example, it allocates coupons to the users who most need that type of coupon, achieving precise resource allocation, improving user experience, increasing the probability of users using resources, and increasing the probability of users using resources to perform the current business, thereby further promoting the current business.

[0091] Furthermore, the resource usage of the current business can be determined based on the usage of allocated resources by each user. Then, the resource utilization rate of the current business can be determined based on the ratio of current resource usage to total resources. This allows the operations staff of the current business to view the resource usage in real time, further facilitating timely adjustments to the promotion strategy of the current business.

[0092] By analyzing user behavior data, promotional strategies can be adjusted in real time, improving promotional efficiency and user satisfaction. Through multi-channel integration and personalized recommendations, the individual needs of different channels and user groups can be met, improving both promotional and user relationship management efficiency. Timely identification and resolution of problems during the promotion process, along with real-time monitoring and feedback mechanisms, allows for real-time evaluation and optimization of promotional effectiveness, further enhancing promotional results and user satisfaction.

[0093] Figure 3 This is a schematic diagram of a resource allocation device provided in an embodiment of the present invention. This device belongs to the same inventive concept as the resource allocation methods in the above embodiments. Details not described in detail in the embodiments of the resource allocation device can be found in the embodiments of the resource allocation methods described above.

[0094] The specific structure of the resource allocation device is as follows: Figure 3 As shown, it includes:

[0095] The acquisition module 310 is used to acquire the demand and user characteristics of users to be assigned in the current business, and input the demand and user characteristics of the users to be assigned into a pre-trained resource type determination model so that the resource type determination model can determine the resource type of the users to be assigned.

[0096] The determining module 320 is used to determine the resource allocation amount for the user to be allocated based on the total resource amount of the current service, the resource type, and the demand and user characteristics of the user to be allocated.

[0097] The allocation module 330 is used to allocate the resources corresponding to the resource allocation amount to the user to be allocated in the form corresponding to the resource type.

[0098] Based on the above embodiments, the device further includes:

[0099] The user identification module is used to acquire user characteristics and user behavior data of each user in the current business; determine the demand level of each user based on the user behavior data of each user; and determine the user to be assigned based on the resource allocation rules of the current business, the demand level of each user, and the user characteristics.

[0100] In one implementation, determining the demand level of each user based on their user behavior data includes:

[0101] The user behavior data of each user is input into a pre-trained demand determination model so that the demand determination model can determine the demand of each user.

[0102] In one implementation, determining the users to be assigned based on the resource allocation rules of the current service, the demand level of each user, and user characteristics includes:

[0103] Users whose user characteristics in the current business match the resource allocation rules, and / or whose demand meets preset conditions, are identified as the users to be allocated.

[0104] Based on the above embodiments, module 320 is specifically used for:

[0105] The total resource allocation amount for the resource type is determined based on the total resource amount; the resource allocation quantity is determined based on the total resource allocation amount, the demand level of the users to be allocated, and the user characteristics.

[0106] Based on the above embodiments, the device further includes:

[0107] The statistics module is used to determine the resource usage of the current service based on the usage of the allocated resources by each of the users to be assigned.

[0108] Based on the above embodiments, the device further includes:

[0109] The first training module is used to acquire the demand level and user characteristics of multiple users, as well as the actual resource types; using the demand level and user characteristics of the users as training inputs and the actual resource types of the users as training outputs to train the network and obtain the resource type determination model.

[0110] The second training module is used to acquire user behavior data from multiple users, determine the actual demand level of each user based on the resource acquisition and resource usage data in the user behavior data, and train the network using the user behavior data as training input and the demand level of the user as the training output to obtain the demand level determination model.

[0111] The resource allocation device provided in the embodiments of the present invention can execute the resource allocation method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects for executing the resource allocation method.

[0112] It is worth noting that in the above-described embodiments of the resource allocation device, the various units and modules included are only divided according to functional logic, but are not limited to the above division, as long as the corresponding functions can be achieved; in addition, the specific names of each functional unit are only for easy differentiation and are not used to limit the scope of protection of the present invention.

[0113] This invention provides a resource allocation system, which should have the following functions: automatic resource allocation: automatically allocating resources to users to be allocated according to the resource allocation method; user restriction management: preventing the same user from enjoying resources multiple times and restricting the scope of resources based on user identifier, device identifier, financial account, contact information, etc.; designing and implementing system interface and user interaction functions, such as user login, event registration, resource collection, etc.

[0114] In practical applications, comprehensive testing can be conducted on the developed system to ensure its quality and stability. The algorithm model and system functions can also be optimized and adjusted based on the test results, such as adjusting the algorithm model parameters. Furthermore, user acceptance testing can be performed to collect user feedback and further optimize the system's user experience and ease of use.

[0115] The optimized system can be deployed to a server, ensuring its stability and security. It can be used to publish the system and notify users of promotional information regarding resource allocation, such as via email or SMS, to inform them of event details and resource redemption. The system's operation can be monitored in real time, allowing for timely handling of user feedback and system failures, ensuring normal system operation and service quality.

[0116] This system enables data analysis of marketing campaigns, including metrics such as participation, conversion rates, and sales. It can also generate reports based on the data analysis results to support operational decisions, such as providing evaluation metrics and recommendations regarding the effectiveness of marketing equity inventory allocation.

[0117] Of course, the system can continuously iterate and upgrade its marketing strategies and algorithm models based on feedback from reported data. This includes updating campaign themes and optimizing algorithm parameters. Continuous optimization of system functionality will improve performance and security, such as adding new monitoring metrics and enhancing system stability.

[0118] The resource allocation system provided in this invention improves allocation efficiency: Through algorithmic models and automatic inventory allocation, allocation efficiency is significantly improved, reducing manual intervention and errors, and ensuring the rational allocation and utilization of inventory. It optimizes user experience: By predicting the discount amount for each user based on user attributes and scenarios, a more personalized discount experience can be provided, increasing user satisfaction and loyalty. It increases conversion rates: Through precise allocation of marketing rights inventory and personalized discount strategies, user participation and conversion can be better attracted, improving the company's sales and conversion rates. It reduces costs: Through algorithmic models and automatic inventory allocation, manual intervention and errors are reduced, lowering operating and management costs. It enhances competitiveness: Through precise allocation of marketing rights inventory and personalized discount strategies, more users are attracted.

[0119] Figure 4 This is a schematic diagram of the structure of a server provided in an embodiment of the present invention. Figure 4 A block diagram of an exemplary server 4 suitable for implementing embodiments of the present invention is shown. Figure 4 The server 4 shown is merely an example and should not impose any limitations on the functionality and scope of use of the embodiments of the present invention.

[0120] like Figure 4 As shown, server 4 is represented in the form of a general-purpose computing electronic device. The components of server 4 may include, but are not limited to: one or more processors or processing units 16, system memory 28, and bus 18 connecting different system components (including system memory 28 and processing unit 16).

[0121] Bus 18 represents one or more of several bus architectures, including a memory bus or memory controller, a peripheral bus, a graphics acceleration port, a processor, or a local bus using any of the various bus architectures. For example, these architectures include, but are not limited to, the Industry Standard Architecture (ISA) bus, the Micro Channel Architecture (MAC) bus, the Enhanced ISA bus, the Video Electronics Standards Association (VESA) local bus, and the Peripheral Component Interconnect (PCI) bus.

[0122] Server 4 typically includes a variety of computer system readable media. These media can be any available media that can be accessed by Server 4, including volatile and non-volatile media, and removable and non-removable media.

[0123] System memory 28 may include computer system readable media in the form of volatile memory, such as random access memory (RAM) 30 and / or cache memory 32. Server 4 may further include other removable / non-removable, volatile / non-volatile computer system storage media. By way of example only, storage system 34 may be used to read and write non-removable, non-volatile magnetic media (… Figure 4 Not shown; usually referred to as a "hard drive"). Although Figure 4 Not shown, a disk drive for reading and writing to a removable non-volatile disk (e.g., a "floppy disk") and an optical disk drive for reading and writing to a removable non-volatile optical disk (e.g., a CD-ROM, DVD-ROM, or other optical media) may be provided. In these cases, each drive may be connected to bus 18 via one or more data media interfaces. System memory 28 may include at least one program product having a set (e.g., at least one) of program modules configured to perform the functions of the embodiments of the present invention.

[0124] A program / utility 40 having a set (at least one) of program modules 42 may be stored, for example, in system memory 28. Such program modules 42 include, but are not limited to, an operating system, one or more application programs, other program modules, and program data. Each or some combination of these examples may include an implementation of a network environment. Program modules 42 typically perform the functions and / or methods described in the embodiments of the present invention.

[0125] Server 4 can also communicate with one or more external devices 14 (e.g., keyboard, pointing device, display 24, etc.), and with one or more devices that enable users to interact with server 4, and / or with any device that enables server 4 to communicate with one or more other computing devices (e.g., network card, modem, etc.). This communication can be performed through input / output (I / O) interface 22. Furthermore, server 4 can also communicate with one or more networks (e.g., local area network (LAN), wide area network (WAN), and / or public networks, such as the Internet) via network adapter 20. Figure 4 As shown, network adapter 20 communicates with other modules of server 4 via bus 18. It should be understood that, although... Figure 4 As not shown in the diagram, it can be combined with other hardware and / or software modules, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.

[0126] Processing unit 16 executes various functional applications and page displays by running programs stored in system memory 28, such as implementing the resource allocation method provided in this embodiment of the invention, which includes:

[0127] Obtain the demand level and user characteristics of users to be assigned in the current business, and input the demand level and user characteristics of users to be assigned into a pre-trained resource type determination model so that the resource type determination model can determine the resource type of the users to be assigned.

[0128] Based on the total amount of resources for the current business, the resource type, and the demand and characteristics of the users to be allocated, determine the resource allocation amount for the users to be allocated;

[0129] The resources corresponding to the resource allocation amount are allocated to the users to be allocated in the form corresponding to the resource type.

[0130] Of course, those skilled in the art will understand that the processor can also implement the technical solutions of the resource allocation method provided in any embodiment of the present invention.

[0131] This invention provides a computer-readable storage medium storing a computer program thereon. When executed by a processor, the program implements, for example, the resource allocation method provided in this invention, which includes:

[0132] Obtain the demand level and user characteristics of users to be assigned in the current business, and input the demand level and user characteristics of users to be assigned into a pre-trained resource type determination model so that the resource type determination model can determine the resource type of the users to be assigned.

[0133] Based on the total amount of resources for the current business, the resource type, and the demand and characteristics of the users to be allocated, determine the resource allocation amount for the users to be allocated;

[0134] The resources corresponding to the resource allocation amount are allocated to the users to be allocated in the form corresponding to the resource type.

[0135] The computer storage medium of this invention can be any combination of one or more computer-readable media. A computer-readable medium can be a computer-readable signal medium or a computer-readable storage medium. For example, a computer-readable storage medium can be, but is not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples (a non-exhaustive list) of computer-readable storage media include: 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 document, a computer-readable storage medium can be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.

[0136] Computer-readable signal media may include data signals propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such propagated data signals may take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. Computer-readable signal media may also be any computer-readable medium other than computer-readable storage media, capable of sending, propagating, or transmitting programs for use by or in connection with an instruction execution system, apparatus, or device.

[0137] Program code contained on a computer-readable medium may be transmitted using any suitable medium, including but not limited to: wireless, wire, optical fiber, RF, etc., or any suitable combination thereof.

[0138] Computer program code for performing the operations of this invention can be written in one or more programming languages ​​or a combination thereof. Programming languages ​​include object-oriented programming languages ​​such as Java, Smalltalk, and C++, as well as conventional procedural programming languages—such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In cases involving remote computers, the remote computer can be connected to the user's computer via any type of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0139] Those skilled in the art will understand that the modules or steps of the present invention described above can be implemented using general-purpose computing devices. They can be centralized on a single computing device or distributed across a network of multiple computing devices. Optionally, they can be implemented using computer-executable program code, thereby allowing them to be stored in a storage device for execution by a computing device, or they can be fabricated as separate integrated circuit modules, or multiple modules or steps can be fabricated as a single integrated circuit module. Thus, the present invention is not limited to any particular combination of hardware and software.

[0140] It should be noted that the collection, gathering, updating, analysis, processing, use, transmission, and storage of user personal information involved in this disclosed technical solution 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.

[0141] For example, after collecting user characteristics, we will use technical means to de-identify the data.

[0142] Note that the above description is merely a preferred embodiment of the present invention and the technical principles employed. Those skilled in the art will understand that the present invention is not limited to the specific embodiments described herein, and various obvious changes, readjustments, and substitutions can be made without departing from the scope of protection of the present invention. Therefore, although the present invention has been described in detail through the above embodiments, the present invention is not limited to the above embodiments, and may include many other equivalent embodiments without departing from the concept of the present invention, the scope of which is determined by the scope of the appended claims.

Claims

1. A resource allocation method, characterized in that, include: Obtain the demand level and user characteristics of users to be assigned in the current business, and input the demand level and user characteristics of users to be assigned into a pre-trained resource type determination model so that the resource type determination model can determine the resource type of the users to be assigned. Based on the total amount of resources for the current business, the resource type, and the demand and characteristics of the users to be allocated, determine the resource allocation amount for the users to be allocated; The resources corresponding to the resource allocation amount are allocated to the users to be allocated in the form corresponding to the resource type.

2. The resource allocation method according to claim 1, characterized in that, Before obtaining the demand and user characteristics of users to be assigned in the current business, the following is also included: Obtain user characteristics and user behavior data for each user in the current business; The demand level of each user is determined based on the user behavior data of each user, and the user to be allocated is determined based on the resource allocation rules of the current business, the demand level of each user, and user characteristics.

3. The resource allocation method according to claim 2, characterized in that, Determining the demand level of each user based on their user behavior data includes: The user behavior data of each user is input into a pre-trained demand determination model so that the demand determination model can determine the demand of each user.

4. The resource allocation method according to claim 2, characterized in that, The users to be assigned are determined based on the current business resource allocation rules, the demand level of each user, and user characteristics, including: Users whose user characteristics in the current business match the resource allocation rules, and / or whose demand meets preset conditions, are identified as the users to be allocated.

5. The resource allocation method according to claim 1, characterized in that, Based on the total resource volume of the current business, the resource type, and the demand and characteristics of the users to be allocated resources, the resource allocation amount for the users to be allocated is determined, including: The total resource allocation for the resource type is determined based on the total resource amount. The resource allocation amount is determined based on the total resource allocation amount, the demand level of the users to be allocated, and their user characteristics.

6. The resource allocation method according to claim 1, characterized in that, Also includes: The resource usage of the current service is determined based on the usage of the allocated resources by each of the users to be assigned.

7. The resource allocation method according to claim 1, characterized in that, The training process for the resource type determination model includes: Obtain the demand level, user characteristics, and actual resource types of multiple users; The network is trained by using the user's demand level and user characteristics as training inputs and the user's actual resource type as the training output, to obtain the resource type determination model.

8. The resource allocation method according to claim 3, characterized in that, The training process of the demand determination model includes: Acquire user behavior data from multiple users, and determine the actual demand level of each user based on the resource acquisition data and resource usage data in the user behavior data of each user. The network is trained using the user's behavior data as training input and the user's demand level as the training output to obtain the demand level determination model.

9. A resource allocation device, characterized in that, include: The acquisition module is used to acquire the demand and user characteristics of users to be assigned in the current business, and input the demand and user characteristics of the users to be assigned into a pre-trained resource type determination model so that the resource type determination model can determine the resource type of the users to be assigned. The determination module is used to determine the resource allocation amount for the user to be allocated based on the total resource amount of the current business, the resource type, and the demand and user characteristics of the user to be allocated. The allocation module is used to allocate the resources corresponding to the resource allocation amount to the users to be allocated in the form corresponding to the resource type.

10. A server, characterized in that, The server includes: 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 resource allocation method as described in any one of claims 1-8.

11. A storage medium containing computer-executable instructions, characterized in that, The computer-executable instructions, when executed by a computer processor, are used to perform the resource allocation method as described in any one of claims 1-8.

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