CN117196703A - Resource distribution method, device, computer equipment and storage medium - Google Patents
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Abstract
The application relates to a resource issuing method, a resource issuing device, computer equipment and a storage medium, relates to the technical field of artificial intelligence, and can be applied to the financial field or other technical fields. The method comprises the following steps: determining the resource value of the resources to be released according to the resource information of the resources to be released in the target mechanism, determining the user evaluation value of the target user according to the user information of the target user in the target mechanism through a user evaluation model, and releasing the resources to be released to the account of the target user under the condition that the user evaluation value of the target user is larger than the resource value of the resources to be released. By adopting the method, the efficiency of resource distribution can be improved.
Description
Technical Field
The present application relates to the field of artificial intelligence, and in particular, to a resource issuing method, apparatus, computer device, and storage medium, which can be applied to the financial field or other technical fields.
Background
In order to improve the purchasing desire of the user, each financial institution can provide preferential resources (such as coupons) for the user, and in order to ensure accurate issuing of the preferential resources, a manual mode can be adopted to pre-configure white lists corresponding to various preferential resources, and then resource issuing is carried out according to the white lists.
However, with the increase of the types of resources, the current resource allocation method is adopted, so that the efficiency of resource allocation is reduced, and a large amount of human resources are consumed, so that improvement is needed.
Disclosure of Invention
In view of the foregoing, it is desirable to provide a resource issuing method, apparatus, computer device, and storage medium capable of improving resource issuing efficiency.
In a first aspect, the present application provides a resource allocation method. The method comprises the following steps:
determining the resource value of the resources to be transmitted according to the resource information of the resources to be transmitted in the target mechanism;
determining a user evaluation value of a target user according to user information of the target user in the target mechanism through a user evaluation model;
and issuing the to-be-issued resource to the account of the target user under the condition that the user evaluation value of the target user is larger than the resource value of the to-be-issued resource.
In one embodiment, the user evaluation model is trained by:
inputting user information of the sample user into the initial model to obtain a user prediction evaluation value of the sample user; determining training loss according to the user prediction evaluation value and the user real evaluation value of the sample user; and training the initial model by adopting the training loss to obtain a user evaluation model.
In one embodiment, determining, by the user evaluation model, the user evaluation value of the target user according to the user information of the target user in the target institution includes:
determining user characteristics corresponding to a target user according to user information of the target user in the target mechanism; the user information comprises basic information of a target user, a resource use record and a credit level; and determining the user evaluation value of the target user according to the user characteristics of the target user through the user evaluation model.
In one embodiment, determining the user characteristics corresponding to the target user according to the user information of the target user in the target mechanism includes:
determining user basic characteristics of a target user according to basic information of the target user in the target mechanism; determining the resource use characteristics of the target user according to the resource use records of the target user; determining the user credit characteristics of the target user according to the credit grade of the target user; and determining the user characteristics corresponding to the target user according to the user basic characteristics, the resource use characteristics and the user credit characteristics.
In one embodiment, determining the user characteristics corresponding to the target user according to the user basic characteristics, the resource usage characteristics and the user credit characteristics includes:
and carrying out weighted fusion on the user basic characteristics, the resource use characteristics and the user credit characteristics to obtain the user characteristics corresponding to the target user.
In one embodiment, the resource information includes a resource attribute and a resource release value, and determining a resource value of the to-be-released resource according to the resource information of the to-be-released resource in the target mechanism includes:
weighting the resource attribute by adopting a weight value corresponding to the resource attribute; weighting the resource release value by adopting a weight value corresponding to the resource release value; and determining the resource value of the resources to be transmitted according to the weighted resource attribute and the resource transmitting value.
In a second aspect, the application further provides a resource issuing device. The device comprises:
the first determining module is used for determining the resource value of the resources to be transmitted according to the resource information of the resources to be transmitted in the target mechanism;
the second determining module is used for determining the user evaluation value of the target user according to the user information of the target user in the target mechanism through the user evaluation model;
and the resource issuing module is used for issuing the resources to be issued to the account of the target user under the condition that the user evaluation value of the target user is greater than the resource value of the resources to be issued.
In a third aspect, the present application also provides a computer device. The computer device comprises a memory storing a computer program and a processor which when executing the computer program performs the steps of:
determining the resource value of the resources to be transmitted according to the resource information of the resources to be transmitted in the target mechanism;
determining a user evaluation value of a target user according to user information of the target user in the target mechanism through a user evaluation model;
and issuing the to-be-issued resource to the account of the target user under the condition that the user evaluation value of the target user is larger than the resource value of the to-be-issued resource.
In a fourth aspect, the present application also provides a computer-readable storage medium. The computer readable storage medium having stored thereon a computer program which when executed by a processor performs the steps of:
determining the resource value of the resources to be transmitted according to the resource information of the resources to be transmitted in the target mechanism;
determining a user evaluation value of a target user according to user information of the target user in the target mechanism through a user evaluation model;
and issuing the to-be-issued resource to the account of the target user under the condition that the user evaluation value of the target user is larger than the resource value of the to-be-issued resource.
In a fifth aspect, the present application also provides a computer program product. The computer program product comprises a computer program which, when executed by a processor, implements the steps of:
determining the resource value of the resources to be transmitted according to the resource information of the resources to be transmitted in the target mechanism;
determining a user evaluation value of a target user according to user information of the target user in the target mechanism through a user evaluation model;
and issuing the to-be-issued resource to the account of the target user under the condition that the user evaluation value of the target user is larger than the resource value of the to-be-issued resource.
The resource issuing method, the device, the computer equipment and the storage medium introduce the resource value of the resource to be issued and the user evaluation value of the target user, and issue the resource to be issued to the account of the target user under the condition that the user evaluation value of the target user is greater than the resource value of the resource to be issued. Compared with the method for manually distributing resources in the related art, by adopting the method, the method can automatically determine whether to distribute the resources to be distributed to the target user or not by comparing the resource value of the resources to be distributed with the user evaluation value of the target user, thereby improving the efficiency of resource distribution and saving human resources.
Drawings
FIG. 1 is an application environment diagram of a resource provisioning method in one embodiment;
FIG. 2 is a flow diagram of a resource provisioning method in one embodiment;
FIG. 3 is a flow chart of determining a user evaluation value in one embodiment;
FIG. 4 is a flowchart of a resource allocation method according to another embodiment;
FIG. 5 is a block diagram showing a configuration of a resource issuing apparatus in one embodiment;
FIG. 6 is a block diagram showing a configuration of a resource issuing apparatus according to another embodiment;
fig. 7 is an internal structural diagram of a computer device in one embodiment.
Detailed Description
The present application will be described in further detail with reference to the drawings and examples, in order to make the objects, technical solutions and advantages of the present application more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the application.
The resource issuing method provided by the embodiment of the application can be applied to an application environment shown in figure 1. Wherein the terminal 102 communicates with the server 104 via a network. The data storage system may store data that the server 104 needs to process. For example, resource information of resources to be released. The data storage system may be integrated on the server 104 or may be located on a cloud or other network server. For example, the server 104 determines the resource value of the to-be-issued resource according to the resource information of the to-be-issued resource in the target mechanism, determines the user evaluation value of the target user according to the user information of the target user in the target mechanism through the user evaluation model, and issues the to-be-issued resource to the account of the target user when the user evaluation value of the target user is greater than the resource value of the to-be-issued resource; further, the target user can view the release condition of the resource through the terminal 102. The terminal 102 may be, but is not limited to, various personal computers, notebook computers, smart phones, tablet computers, and internet of things devices. The server 104 may be implemented as a stand-alone server or as a server cluster of multiple servers.
In order to improve the purchasing desire of users, each financial institution can provide preferential resources for the users, and in order to ensure the accurate distribution of the preferential resources, a manual mode can be adopted to pre-configure white lists corresponding to various preferential resources, and then the resource distribution is carried out according to the white lists.
However, with the increase of the kinds of resources, the current resource allocation method is adopted, which reduces the efficiency of resource allocation and consumes a great deal of human resources.
In one embodiment, as shown in fig. 2, a resource issuing method is provided, and the method is applied to the server in fig. 1 for illustration, and includes the following steps:
s201, determining the resource value of the to-be-played resource according to the resource information of the to-be-played resource in the target mechanism.
Where the resource to be released refers to a preferential resource, such as a coupon, that can target the product under the institution. For example, the target institution relates to a financial product and the resource to be released may be a coupon for purchasing the financial product. The resource information refers to detailed information of the resources to be released, and may include a resource usage rule, a resource release value, and the like; the resource value is used for representing the contribution degree of the to-be-issued resource to the target mechanism; alternatively, the higher the resource value, the greater the contribution of the resources to be released.
Alternatively, the resource information of the to-be-issued resource in the target mechanism may be input into a trained value determination model, and the value determination model determines the resource value of the to-be-issued resource according to the resource information of the to-be-issued resource and the model parameters.
Alternatively, in the case that the resource information includes a resource attribute and a resource release value, the resource attribute may be weighted by a weight value corresponding to the resource attribute, the resource release value may be weighted by a weight value corresponding to the resource release value, and the resource value of the resource to be released may be determined according to the resource attribute and the resource release value after the weighted processing.
Wherein, the resource attribute refers to the applicable product type of the to-be-released resource, such as financial products and the like; the resource issuing value refers to the preferential strength of the resource to be issued, for example, a financial coupon can be withheld by 200 yuan, and then 200 is the resource issuing value.
Optionally, corresponding weight values can be set for the resource attribute and the resource release value of the resource to be released according to the type of each resource attribute and the size of the resource release value in advance; then, weighting the resource attribute by adopting a weight value corresponding to the resource attribute, and weighting the resource issuing value by adopting a weight value corresponding to the resource issuing value; and finally, adding and fusing the weighted resource attribute and the resource release value to obtain the resource value of the resource to be released.
S202, determining a user evaluation value of the target user according to the user information of the target user in the target mechanism through the user evaluation model.
The user evaluation model is a neural network model for determining the importance degree of the user; the target user refers to a user who has registered on the corresponding platform of the target institution. The user evaluation value is used for representing the purchasing power of the user; alternatively, the higher the user evaluation value, the stronger the purchasing power of the user.
Alternatively, the user information of the target user may be input into the user evaluation model, and the user evaluation value of the target user may be determined by the user evaluation model according to the user information of the target user and the model parameters.
It is to be understood that, in order to facilitate comparison of the user evaluation value of the target user with the resource value of the to-be-released resource, the user evaluation value of the target user and the resource value of the to-be-released resource may be set within the same range. For example, the ranges of the user evaluation value and the resource value are each set in the range of 0 to 1.
S203, issuing the to-be-issued resource to the account of the target user under the condition that the user evaluation value of the target user is larger than the resource value of the to-be-issued resource.
It can be understood that in order to avoid the problem of low utilization rate of resources, when the resources are issued, resources matched with the purchasing power of each user need to be issued, so that the resources to be issued can be issued according to the matching condition of the user evaluation value of the target user and the resource value of the resources to be issued. For example, the to-be-released resource having a high resource value may be transmitted to the user having a high user evaluation value.
Optionally, in order to meet the matching between the user evaluation value of the target user and the resource value of the resource to be issued, the user evaluation value of the target user and the resource value of the resource to be issued may be compared, and if the user evaluation value of the target user is greater than the resource value of the resource to be issued, the importance degree of the target user is higher, so that the resource to be issued may be issued to the account of the target user; if the user evaluation value of the target user is smaller than or equal to the resource value of the resources to be issued, the importance degree of the target user is lower, so that the resources to be issued cannot be issued to the account of the target user.
For example, the target mechanism has to-be-issued resources A and B, wherein the resource value of the to-be-issued resource A is 0.6, and the resource value of the to-be-issued resource B is 0.9; further, if the user evaluation value of the target user is 0.7, the to-be-released resource a can be released to the target user; if the user evaluation value of the target user is 0.95, the to-be-issued resource A and the to-be-issued resource B can be issued to the target user.
In the resource issuing method, the resource value of the to-be-issued resource and the user evaluation value of the target user are introduced, and the to-be-issued resource is issued to the account of the target user under the condition that the user evaluation value of the target user is larger than the resource value of the to-be-issued resource. Compared with the method for manually distributing resources in the related art, by adopting the method, the method can automatically determine whether to distribute the resources to be distributed to the target user or not by comparing the resource value of the resources to be distributed with the user evaluation value of the target user, thereby improving the efficiency of resource distribution and saving human resources.
In order to ensure the accuracy of the user evaluation model, in the embodiment, an optional method for model training is provided, specifically, the user information of the sample user is input into the initial model to obtain the user prediction evaluation value of the sample user; determining training loss according to the user prediction evaluation value and the user real evaluation value of the sample user; and training the initial model by adopting the training loss to obtain a user evaluation model.
The sample users refer to part of users registered on a platform corresponding to a target mechanism; the initial model refers to an untrained model, which may be a neural network; the user predicted evaluation value refers to a predicted user evaluation value; the user true evaluation value refers to the evaluation value which is used for model training supervision and is true for the user.
Optionally, user information of the sample user may be input into the initial model to obtain a user prediction evaluation value of the sample user; and substituting the user predicted evaluation value and the user real evaluation value of the sample user into a preset loss function to determine training loss, and training the initial model by adopting the training loss if the training loss is larger than a preset loss threshold value until the training loss between the user predicted evaluation value and the user real evaluation value is smaller than or equal to the loss threshold value, thereby obtaining the user evaluation model. The loss threshold refers to a numerical value for judging the training loss.
In the embodiment, the initial model is trained by adopting the user information of the sample user and the actual evaluation value of the user, so that the accuracy of the user evaluation model can be ensured.
In order to ensure the accuracy of the user evaluation value determination, in the embodiment, an alternative method for determining the user evaluation value is provided, as shown in fig. 3, and specifically includes the following steps:
s301, determining user characteristics corresponding to the target user according to user information of the target user in the target mechanism.
Wherein the user information includes basic information of the target user, resource usage records, and credit levels.
Alternatively, the user information of the target user in the target mechanism is input into the feature determination model, and the feature determination model determines the user feature corresponding to the target user according to the user information of the target user in the target mechanism and the model parameters.
Alternatively, determining user basic characteristics of the target user according to basic information of the target user in the target mechanism; determining the resource use characteristics of the target user according to the resource use records of the target user; determining the user credit characteristics of the target user according to the credit grade of the target user; and determining the user characteristics corresponding to the target user according to the user basic characteristics, the resource use characteristics and the user credit characteristics.
Optionally, the user basic characteristics of the target user can be determined according to the character strings corresponding to the basic information such as gender, age, occupation and the like of the target user; determining the resource use characteristics of the target user according to the resource use type and the character string corresponding to the resource use times in the resource use record of the target user; and determining the user credit characteristics of the target user according to the character string corresponding to the credit rating of the target user.
Further, after the user basic characteristics, the resource use characteristics and the user credit characteristics are determined, the user basic characteristics, the resource use characteristics and the user credit characteristics can be directly spliced, and the user characteristics corresponding to the target user are determined; or, the user basic characteristics, the resource using characteristics and the user credit characteristics are weighted and fused to obtain the user characteristics corresponding to the target user.
For example, the user basic feature M, the resource usage feature N, and the user credit feature S may be respectively set with corresponding weight values T M 、T N And T S The method comprises the steps of carrying out a first treatment on the surface of the Subsequently, T is taken M *M+T N *N+T S * S is as the orderAnd marking the user characteristics corresponding to the user.
S302, determining a user evaluation value of the target user according to the user characteristics of the target user through the user evaluation model.
Alternatively, the user characteristics of the target user may be input into the user evaluation model, and the user evaluation value of the target user may be determined by the user evaluation model according to the user characteristics of the target user and the model parameters.
In this embodiment, the user characteristics corresponding to the target user are introduced, and the user evaluation value is determined by the user characteristics corresponding to the target user, so that the accuracy of determining the user evaluation value can be ensured.
Fig. 4 is a schematic flow chart of a resource allocation method in another embodiment, and on the basis of the foregoing embodiment, this embodiment provides an alternative example of the resource allocation method. With reference to fig. 4, the specific implementation procedure is as follows:
s401, inputting user information of the sample user into the initial model to obtain a user prediction evaluation value of the sample user.
S402, determining training loss according to the user predicted evaluation value and the user real evaluation value of the sample user.
S403, training the initial model by using the training loss to obtain a user evaluation model.
S404, determining the resource value of the to-be-played resource according to the resource information of the to-be-played resource in the target mechanism.
Optionally, weighting the resource attribute by adopting a weight value corresponding to the resource attribute; weighting the resource release value by adopting a weight value corresponding to the resource release value; and determining the resource value of the resources to be transmitted according to the weighted resource attribute and the resource transmitting value.
S405, determining the user characteristics corresponding to the target user according to the user information of the target user in the target mechanism.
Wherein the user information includes basic information of the target user, resource usage records, and credit levels.
Optionally, determining user basic characteristics of the target user according to basic information of the target user in the target mechanism; determining the resource use characteristics of the target user according to the resource use records of the target user; and determining the user credit characteristics of the target user according to the credit grade of the target user.
Further, according to the user basic characteristics, the resource use characteristics and the user credit characteristics, determining the user characteristics corresponding to the target user; or, the user basic characteristics, the resource using characteristics and the user credit characteristics are weighted and fused to obtain the user characteristics corresponding to the target user.
S406, determining the user evaluation value of the target user according to the user characteristics of the target user through the user evaluation model.
S407, issuing the to-be-issued resource to the account of the target user under the condition that the user evaluation value of the target user is larger than the resource value of the to-be-issued resource.
The specific process of S401 to S407 may refer to the description of the foregoing method embodiment, and its implementation principle and technical effect are similar, and are not repeated herein.
It should be understood that, although the steps in the flowcharts related to the embodiments described above are sequentially shown as indicated by arrows, these steps are not necessarily sequentially performed in the order indicated by the arrows. The steps are not strictly limited to the order of execution unless explicitly recited herein, and the steps may be executed in other orders. Moreover, at least some of the steps in the flowcharts described in the above embodiments may include a plurality of steps or a plurality of stages, which are not necessarily performed at the same time, but may be performed at different times, and the order of the steps or stages is not necessarily performed sequentially, but may be performed alternately or alternately with at least some of the other steps or stages.
Based on the same inventive concept, the embodiment of the application also provides a resource issuing device for realizing the above-mentioned resource issuing method. The implementation of the solution provided by the device is similar to the implementation described in the above method, so the specific limitation in one or more embodiments of the resource release device provided below may refer to the limitation of the resource release method hereinabove, and will not be repeated herein.
In one embodiment, as shown in fig. 5, there is provided a resource issuing apparatus 1 including: a first determination module 10, a second determination module 20, and a resource issuance module 30, wherein:
a first determining module 10, configured to determine a resource value of a resource to be issued according to resource information of the resource to be issued in the target mechanism;
a second determining module 20, configured to determine, according to the user information of the target user in the target institution, a user evaluation value of the target user through the user evaluation model;
the resource issuing module 30 is configured to issue the to-be-issued resource to the account of the target user in a case where the user evaluation value of the target user is greater than the resource value of the to-be-issued resource.
In one embodiment, the resource issuing device 1 further comprises a model training module, wherein the model training module is specifically configured to:
inputting user information of the sample user into the initial model to obtain a user prediction evaluation value of the sample user; determining training loss according to the user prediction evaluation value and the user real evaluation value of the sample user; and training the initial model by adopting the training loss to obtain a user evaluation model.
In one embodiment, as shown in fig. 6, the second determining module 20 includes:
a feature determining unit 21, configured to determine a user feature corresponding to the target user according to user information of the target user in the target mechanism; the user information comprises basic information of a target user, a resource use record and a credit level;
the evaluation value determining unit 22 is configured to determine a user evaluation value of the target user according to the user characteristics of the target user through the user evaluation model.
In one embodiment, the feature determination unit 21 includes:
the first subunit is used for determining user basic characteristics of the target user according to basic information of the target user in the target mechanism;
a second subunit, configured to determine a resource usage feature of the target user according to the resource usage record of the target user;
a third subunit, configured to determine a user credit characteristic of the target user according to the credit rating of the target user;
and the fourth subunit is used for determining the user characteristics corresponding to the target user according to the user basic characteristics, the resource use characteristics and the user credit characteristics.
In one embodiment, the fourth subunit is specifically configured to:
and carrying out weighted fusion on the user basic characteristics, the resource use characteristics and the user credit characteristics to obtain the user characteristics corresponding to the target user.
In one embodiment, the first determining module 10 is specifically configured to:
weighting the resource attribute by adopting a weight value corresponding to the resource attribute; weighting the resource release value by adopting a weight value corresponding to the resource release value; and determining the resource value of the resources to be transmitted according to the weighted resource attribute and the resource transmitting value.
The respective modules in the above-described resource issuing apparatus may be implemented in whole or in part by software, hardware, and combinations thereof. The above modules may be embedded in hardware or may be independent of a processor in the computer device, or may be stored in software in a memory in the computer device, so that the processor may call and execute operations corresponding to the above modules.
In one embodiment, a computer device is provided, which may be a server, the internal structure of which may be as shown in fig. 7. The computer device includes a processor, a memory, an Input/Output interface (I/O) and a communication interface. The processor, the memory and the input/output interface are connected through a system bus, and the communication interface is connected to the system bus through the input/output interface. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage media. The database of the computer device is used for storing resource information data of the resources to be released. The input/output interface of the computer device is used to exchange information between the processor and the external device. The communication interface of the computer device is used for communicating with an external terminal through a network connection. The computer program is executed by a processor to implement a resource allocation method.
It will be appreciated by those skilled in the art that the structure shown in FIG. 7 is merely a block diagram of some of the structures associated with the present inventive arrangements and is not limiting of the computer device to which the present inventive arrangements may be applied, and that a particular computer device may include more or fewer components than shown, or may combine some of the components, or have a different arrangement of components.
In one embodiment, a computer device is provided comprising a memory and a processor, the memory having stored therein a computer program, the processor when executing the computer program performing the steps of:
determining the resource value of the resources to be transmitted according to the resource information of the resources to be transmitted in the target mechanism;
determining a user evaluation value of a target user according to user information of the target user in the target mechanism through a user evaluation model;
and issuing the to-be-issued resource to the account of the target user under the condition that the user evaluation value of the target user is larger than the resource value of the to-be-issued resource.
In one embodiment, the processor, when executing logic in a computer program for training a user evaluation model, specifically implements the steps of:
inputting user information of the sample user into the initial model to obtain a user prediction evaluation value of the sample user; determining training loss according to the user prediction evaluation value and the user real evaluation value of the sample user; and training the initial model by adopting the training loss to obtain a user evaluation model.
In one embodiment, when the processor executes logic in the computer program for determining the user evaluation value of the target user according to the user information of the target user in the target institution through the user evaluation model, the following steps are specifically implemented:
determining user characteristics corresponding to a target user according to user information of the target user in the target mechanism; the user information comprises basic information of a target user, a resource use record and a credit level; and determining the user evaluation value of the target user according to the user characteristics of the target user through the user evaluation model.
In one embodiment, when the processor executes logic in the computer program for determining a user feature corresponding to a target user according to user information of the target user in the target mechanism, the following steps are specifically implemented:
determining user basic characteristics of a target user according to basic information of the target user in the target mechanism; determining the resource use characteristics of the target user according to the resource use records of the target user; determining the user credit characteristics of the target user according to the credit grade of the target user; and determining the user characteristics corresponding to the target user according to the user basic characteristics, the resource use characteristics and the user credit characteristics.
In one embodiment, when the processor executes logic of determining a user feature corresponding to a target user according to a user basic feature, a resource usage feature and a user credit feature in the computer program, the following steps are specifically implemented:
and carrying out weighted fusion on the user basic characteristics, the resource use characteristics and the user credit characteristics to obtain the user characteristics corresponding to the target user.
In one embodiment, when the processor executes the logic that the resource information in the computer program includes the resource attribute and the resource release value, and determines the resource value of the resource to be released according to the resource information of the resource to be released in the target mechanism, the following steps are specifically implemented:
weighting the resource attribute by adopting a weight value corresponding to the resource attribute; weighting the resource release value by adopting a weight value corresponding to the resource release value; and determining the resource value of the resources to be transmitted according to the weighted resource attribute and the resource transmitting value.
In one embodiment, a computer readable storage medium is provided having a computer program stored thereon, which when executed by a processor, performs the steps of:
determining the resource value of the resources to be transmitted according to the resource information of the resources to be transmitted in the target mechanism;
determining a user evaluation value of a target user according to user information of the target user in the target mechanism through a user evaluation model;
and issuing the to-be-issued resource to the account of the target user under the condition that the user evaluation value of the target user is larger than the resource value of the to-be-issued resource.
In one embodiment, this code logic in the computer program for training the user evaluation model, when executed by the processor, embodies the steps of:
inputting user information of the sample user into the initial model to obtain a user prediction evaluation value of the sample user; determining training loss according to the user prediction evaluation value and the user real evaluation value of the sample user; and training the initial model by adopting the training loss to obtain a user evaluation model.
In one embodiment, the code logic in the computer program for determining the user rating value of the target user based on the user information of the target user in the target institution via the user rating model is executed by the processor to implement the steps of:
determining user characteristics corresponding to a target user according to user information of the target user in the target mechanism; the user information comprises basic information of a target user, a resource use record and a credit level; and determining the user evaluation value of the target user according to the user characteristics of the target user through the user evaluation model.
In one embodiment, the code logic in the computer program for determining the user characteristics corresponding to the target user according to the user information of the target user in the target mechanism is executed by the processor, and specifically implements the following steps:
determining user basic characteristics of a target user according to basic information of the target user in the target mechanism; determining the resource use characteristics of the target user according to the resource use records of the target user; determining the user credit characteristics of the target user according to the credit grade of the target user; and determining the user characteristics corresponding to the target user according to the user basic characteristics, the resource use characteristics and the user credit characteristics.
In one embodiment, the code logic in the computer program for determining the user characteristic corresponding to the target user based on the user basic characteristic, the resource usage characteristic and the user credit characteristic, when executed by the processor, specifically implements the steps of:
and carrying out weighted fusion on the user basic characteristics, the resource use characteristics and the user credit characteristics to obtain the user characteristics corresponding to the target user.
In one embodiment, the resource information in the computer program includes a resource attribute and a resource release value, and the code logic for determining the resource value of the resource to be released according to the resource information of the resource to be released in the target mechanism is executed by the processor, and specifically implements the following steps:
weighting the resource attribute by adopting a weight value corresponding to the resource attribute; weighting the resource release value by adopting a weight value corresponding to the resource release value; and determining the resource value of the resources to be transmitted according to the weighted resource attribute and the resource transmitting value.
In one embodiment, a computer program product is provided comprising a computer program which, when executed by a processor, performs the steps of:
determining the resource value of the resources to be transmitted according to the resource information of the resources to be transmitted in the target mechanism;
determining a user evaluation value of a target user according to user information of the target user in the target mechanism through a user evaluation model;
and issuing the to-be-issued resource to the account of the target user under the condition that the user evaluation value of the target user is larger than the resource value of the to-be-issued resource.
In one embodiment, the computer program, when executed by the processor, performs the operations of training the user assessment model, specifically implements the steps of:
inputting user information of the sample user into the initial model to obtain a user prediction evaluation value of the sample user; determining training loss according to the user prediction evaluation value and the user real evaluation value of the sample user; and training the initial model by adopting the training loss to obtain a user evaluation model.
In one embodiment, the computer program is executed by the processor to determine the user rating value of the target user based on the user information of the target user in the target institution through the user rating model, and specifically implement the following steps:
determining user characteristics corresponding to a target user according to user information of the target user in the target mechanism; the user information comprises basic information of a target user, a resource use record and a credit level; and determining the user evaluation value of the target user according to the user characteristics of the target user through the user evaluation model.
In one embodiment, when the computer program is executed by the processor to determine the user characteristics corresponding to the target user according to the user information of the target user in the target mechanism, the following steps are specifically implemented:
determining user basic characteristics of a target user according to basic information of the target user in the target mechanism; determining the resource use characteristics of the target user according to the resource use records of the target user; determining the user credit characteristics of the target user according to the credit grade of the target user; and determining the user characteristics corresponding to the target user according to the user basic characteristics, the resource use characteristics and the user credit characteristics.
In one embodiment, when the computer program is executed by the processor to determine the user characteristics corresponding to the target user according to the user basic characteristics, the resource usage characteristics and the user credit characteristics, the following steps are specifically implemented:
and carrying out weighted fusion on the user basic characteristics, the resource use characteristics and the user credit characteristics to obtain the user characteristics corresponding to the target user.
In one embodiment, when the computer program is executed by the processor to determine the resource value of the to-be-issued resource according to the resource information of the to-be-issued resource in the target mechanism, the following steps are specifically implemented:
weighting the resource attribute by adopting a weight value corresponding to the resource attribute; weighting the resource release value by adopting a weight value corresponding to the resource release value; and determining the resource value of the resources to be transmitted according to the weighted resource attribute and the resource transmitting value.
The data (including but not limited to resource information of the resources to be transmitted, etc.) related to the present application are information and data authorized by the user or sufficiently authorized by each party.
Those skilled in the art will appreciate that implementing all or part of the above described methods may be accomplished by way of a computer program stored on a non-transitory computer readable storage medium, which when executed, may comprise the steps of the embodiments of the methods described above. Any reference to memory, database, or other medium used in embodiments provided herein may include at least one of non-volatile and volatile memory. The nonvolatile Memory may include Read-Only Memory (ROM), magnetic tape, floppy disk, flash Memory, optical Memory, high density embedded nonvolatile Memory, resistive random access Memory (ReRAM), magnetic random access Memory (Magnetoresistive Random Access Memory, MRAM), ferroelectric Memory (Ferroelectric Random Access Memory, FRAM), phase change Memory (Phase Change Memory, PCM), graphene Memory, and the like. Volatile memory can include random access memory (Random Access Memory, RAM) or external cache memory, and the like. By way of illustration, and not limitation, RAM can be in the form of a variety of forms, such as static random access memory (Static Random Access Memory, SRAM) or dynamic random access memory (Dynamic Random Access Memory, DRAM), and the like. The databases referred to in the embodiments provided herein may include at least one of a relational database and a non-relational database. The non-relational database may include, but is not limited to, a blockchain-based distributed database, and the like. The processor referred to in the embodiments provided in the present application may be a general-purpose processor, a central processing unit, a graphics processor, a digital signal processor, a programmable logic unit, a data processing logic unit based on quantum computing, or the like, but is not limited thereto.
The technical features of the above embodiments may be arbitrarily combined, and all possible combinations of the technical features in the above embodiments are not described for brevity of description, however, as long as there is no contradiction between the combinations of the technical features, they should be considered as the scope of the description.
The foregoing examples illustrate only a few embodiments of the application and are described in detail herein without thereby limiting the scope of the application. It should be noted that it will be apparent to those skilled in the art that several variations and modifications can be made without departing from the spirit of the application, which are all within the scope of the application. Accordingly, the scope of the application should be assessed as that of the appended claims.
Claims (10)
1. A resource distribution method, the method comprising:
determining the resource value of the resources to be transmitted according to the resource information of the resources to be transmitted in the target mechanism;
determining a user evaluation value of the target user according to the user information of the target user in the target mechanism through a user evaluation model;
and issuing the resources to be issued to the account of the target user under the condition that the user evaluation value of the target user is larger than the resource value of the resources to be issued.
2. The method of claim 1, wherein the user evaluation model is trained by:
inputting user information of a sample user into an initial model to obtain a user prediction evaluation value of the sample user;
determining training loss according to the user predicted evaluation value and the user real evaluation value of the sample user;
and training the initial model by adopting the training loss to obtain the user evaluation model.
3. The method of claim 1, wherein the determining, by the user rating model, the user rating value of the target user based on the user information of the target user in the target institution, comprises:
determining user characteristics corresponding to a target user in the target mechanism according to the user information of the target user; wherein the user information comprises basic information of a target user, a resource use record and a credit level;
and determining the user evaluation value of the target user according to the user characteristics of the target user through a user evaluation model.
4. A method according to claim 3, wherein said determining the user characteristics corresponding to the target user based on the user information of the target user in the target institution comprises:
determining user basic characteristics of a target user according to basic information of the target user in the target mechanism;
determining the resource use characteristics of the target user according to the resource use records of the target user;
determining the user credit characteristics of the target user according to the credit grade of the target user;
and determining the user characteristics corresponding to the target user according to the user basic characteristics, the resource use characteristics and the user credit characteristics.
5. The method of claim 4, wherein said determining the user characteristic corresponding to the target user based on the user base characteristic, the resource usage characteristic, and the user credit characteristic comprises:
and carrying out weighted fusion on the user basic characteristics, the resource use characteristics and the user credit characteristics to obtain the user characteristics corresponding to the target user.
6. The method according to claim 1, wherein the resource information includes a resource attribute and a resource release value, and the determining the resource value of the to-be-released resource according to the resource information of the to-be-released resource in the target institution includes:
weighting the resource attribute by adopting a weight value corresponding to the resource attribute;
weighting the resource release value by adopting a weight value corresponding to the resource release value;
and determining the resource value of the resources to be issued according to the weighted resource attribute and the resource issuing value.
7. A resource issuing apparatus, characterized in that the apparatus comprises:
the first determining module is used for determining the resource value of the resources to be transmitted according to the resource information of the resources to be transmitted in the target mechanism;
the second determining module is used for determining a user evaluation value of the target user according to the user information of the target user in the target mechanism through a user evaluation model;
and the resource issuing module is used for issuing the resources to be issued to the account of the target user under the condition that the user evaluation value of the target user is larger than the resource value of the resources to be issued.
8. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that the processor implements the steps of the method of any of claims 1 to 6 when the computer program is executed.
9. A computer readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, implements the steps of the method of any of claims 1 to 6.
10. A computer program product comprising a computer program, characterized in that the computer program, when being executed by a processor, implements the steps of the method of any of claims 1 to 6.
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| CN202310927660.3A CN117196703A (en) | 2023-07-26 | 2023-07-26 | Resource distribution method, device, computer equipment and storage medium |
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| CN202310927660.3A CN117196703A (en) | 2023-07-26 | 2023-07-26 | Resource distribution method, device, computer equipment and storage medium |
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| CN202310927660.3A Pending CN117196703A (en) | 2023-07-26 | 2023-07-26 | Resource distribution method, device, computer equipment and storage medium |
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