Virtual resource determination method, device, server and storage medium

Abstract

The present disclosure relates to a virtual resource determination method, device, server and storage medium, and the method comprises: generating at least one virtual resource parameter group in response to a virtual resource determination request; the virtual resource parameter group comprises a plurality of virtual resource parameters that meet preset conditions; then inputting the at least one virtual resource parameter group into a pre-built evaluation model to obtain a resource evaluation result output by the evaluation model for the at least one virtual resource parameter group; then, according to the resource evaluation result, obtaining a target virtual resource parameter group from a plurality of virtual resource parameter groups as a virtual resource determination result for the virtual resource determination request; comprehensively considering the resource evaluation results of different virtual resource parameter groups, and determining the one with the best effect from the different virtual resource parameter groups as the virtual resource determination result; avoiding the inaccuracy of determining virtual resources based only on historical experience, and improving the effect of issuing virtual resources.

Description

Technical Field

[0001] The present disclosure relates to the field of computer technology, and in particular to a method, device, server and storage medium for determining virtual resources. Background Art

[0002] Virtual resources are a type of business data that is dynamically distributed by the platform based on business conditions.

[0003] In related technologies, platforms usually manually determine specific parameters of virtual resources based on historical experience, but it is difficult to predict the effects of virtual resources after they are issued, resulting in low efficiency and poor effects of issuing virtual resources. Summary of the invention

[0004] The present disclosure provides a virtual resource determination method, device, server and storage medium to at least solve the problem that the effect of issuing virtual resources in the related art is still poor. The technical solution of the present disclosure is as follows:

[0005] According to a first aspect of an embodiment of the present disclosure, a method for determining a virtual resource is provided, comprising:

[0006] In response to the virtual resource determination request, generating at least one virtual resource parameter group; the virtual resource parameter group includes a plurality of virtual resource parameters that meet preset conditions;

[0007] Inputting at least one of the virtual resource parameter groups into a pre-built evaluation model to obtain a resource evaluation result output by the evaluation model for at least one of the virtual resource parameter groups;

[0008] According to the resource evaluation result, a target virtual resource parameter group is obtained from the plurality of virtual resource parameter groups as a virtual resource determination result for the virtual resource determination request.

[0009] In an exemplary embodiment, the virtual resource parameter group includes a conversion parameter, a condition parameter, and an adjustment parameter;

[0010] The generating at least one virtual resource parameter group comprises:

[0011] Acquire at least one conversion parameter within a first preset range and at least one resource parameter group within a second preset range; the resource parameter group includes a condition parameter and an adjustment parameter, and the adjustment parameter is less than or equal to the condition parameter;

[0012] The at least one conversion parameter is combined with the at least one resource parameter group to obtain the at least one virtual resource parameter group.

[0013] In an exemplary embodiment, acquiring a target virtual resource parameter group from a plurality of virtual resource parameter groups according to the resource evaluation result includes:

[0014] Obtaining evaluation values ​​corresponding to each of the virtual resource parameter groups from the resource evaluation results;

[0015] A virtual resource parameter group whose evaluation value is greater than a preset threshold is obtained as the target virtual resource parameter group; the preset threshold is determined according to the evaluation values ​​corresponding to each of the virtual resource parameter groups.

[0016] In an exemplary embodiment, the step of obtaining the virtual resource parameter group whose evaluation value is greater than a preset threshold as the target virtual resource parameter group includes:

[0017] If there are multiple virtual resource parameter groups whose evaluation values ​​are greater than the preset threshold, a virtual resource parameter group whose evaluation value is greater than the target preset threshold is obtained as the target virtual resource parameter group.

[0018] In an exemplary embodiment, before inputting at least one of the virtual resource parameter groups into a pre-built evaluation model, the method further includes:

[0019] Acquire historical data of virtual resources corresponding to the virtual resource determination request;

[0020] Evaluation parameters are determined according to the historical data, and the evaluation model is constructed according to the evaluation parameters.

[0021] In an exemplary embodiment, the historical data includes an account type identifier;

[0022] Determining the evaluation parameters according to the historical data includes:

[0023] Acquire target historical data within a preset time range, where the account type identifier is a preset account type;

[0024] The preset indicators are analyzed according to the target historical data to obtain the evaluation parameters.

[0025] In an exemplary embodiment, before inputting at least one of the virtual resource parameter groups into a pre-built evaluation model, the method further includes:

[0026] Identifying the type of virtual resource to be determined in the virtual resource determination request;

[0027] From a plurality of evaluation models, an evaluation model matching the type is acquired as the pre-built evaluation model.

[0028] According to a second aspect of an embodiment of the present disclosure, a virtual resource determination device is provided, including:

[0029] A parameter group generating unit is configured to generate at least one virtual resource parameter group in response to a virtual resource determination request; the virtual resource parameter group includes a plurality of virtual resource parameters that meet preset conditions;

[0030] An evaluation result output unit, configured to input at least one of the virtual resource parameter groups into a pre-built evaluation model to obtain a resource evaluation result output by the evaluation model for at least one of the virtual resource parameter groups;

[0031] The resource result determination unit is configured to obtain a target virtual resource parameter group from the plurality of virtual resource parameter groups according to the resource evaluation result as a virtual resource determination result for the virtual resource determination request.

[0032] In an exemplary embodiment, the virtual resource parameter group includes a conversion parameter, a condition parameter, and an adjustment parameter;

[0033] The parameter group generation unit is further configured to execute acquisition of at least one conversion parameter within a first preset range and at least one resource parameter group within a second preset range; the resource parameter group includes a condition parameter and an adjustment parameter, and the adjustment parameter is less than or equal to the condition parameter; and the at least one conversion parameter is combined with the at least one resource parameter group to obtain the at least one virtual resource parameter group.

[0034] In an exemplary embodiment, the resource result determination unit is further configured to obtain evaluation values ​​corresponding to each of the virtual resource parameter groups from the resource evaluation results; obtain a virtual resource parameter group whose evaluation value is greater than a preset threshold as the target virtual resource parameter group; and the preset threshold is determined based on the evaluation values ​​corresponding to each of the virtual resource parameter groups.

[0035] In an exemplary embodiment, the resource result determination unit is further configured to execute, if there are multiple virtual resource parameter groups whose evaluation values ​​are greater than a preset threshold, obtaining a virtual resource parameter group whose evaluation value is greater than a target preset threshold as the target virtual resource parameter group.

[0036] In an exemplary embodiment, the evaluation result output unit is further configured to obtain historical data of the virtual resource corresponding to the virtual resource determination request; determine evaluation parameters according to the historical data, and construct the evaluation model according to the evaluation parameters.

[0037] In an exemplary embodiment, the historical data includes an account type identifier;

[0038] The evaluation result output unit is further configured to execute acquisition of target historical data within a preset time range, in which the account type identifier is a preset account type; and to analyze preset indicators according to the target historical data to obtain the evaluation parameters.

[0039] In an exemplary embodiment, the evaluation result output unit is further configured to identify the type of the virtual resource to be determined in the virtual resource determination request; and obtain an evaluation model matching the type from multiple evaluation models as the pre-built evaluation model.

[0040] According to a third aspect of an embodiment of the present disclosure, a server is provided, including:

[0041] processor;

[0042] a memory for storing instructions executable by the processor;

[0043] The processor is configured to execute the instructions to implement the virtual resource determination method as described in any one of the embodiments of the first aspect.

[0044] According to a fourth aspect of an embodiment of the present disclosure, a computer-readable storage medium is provided. When instructions in the computer-readable storage medium are executed by a processor of a server, the server is enabled to execute the virtual resource determination method as described in any one of the embodiments of the first aspect.

[0045] According to a fifth aspect of an embodiment of the present disclosure, a computer program product is provided, and when the instructions are executed by a processor of a server, the server is able to execute the virtual resource determination method as described in any one of the embodiments of the first aspect.

[0046] The technical solution provided by the embodiments of the present disclosure brings at least the following beneficial effects:

[0047] At least one virtual resource parameter group is generated in response to a virtual resource determination request; the virtual resource parameter group includes multiple virtual resource parameters that meet preset conditions; then at least one virtual resource parameter group is input into a pre-built evaluation model to obtain a resource evaluation result output by the evaluation model for at least one virtual resource parameter group; then, based on the resource evaluation result, a target virtual resource parameter group is obtained from multiple virtual resource parameter groups as a virtual resource determination result for the virtual resource determination request; resource evaluation results of different virtual resource parameter groups are comprehensively considered, and the best virtual resource parameter group is determined from different virtual resource parameter groups as the virtual resource determination result; the inaccuracy of determining virtual resources based only on historical experience is avoided, thereby improving the effect of issuing virtual resources.

[0048] It is to be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] The drawings herein are incorporated into and constitute a part of the specification, illustrate embodiments consistent with the present disclosure, and together with the description are used to explain the principles of the present disclosure, and do not constitute improper limitations on the present disclosure.

[0050] Figure 1 The diagram is an application environment diagram of a method for determining virtual resources according to an exemplary embodiment.

[0051] Figure 2 The figure is a flowchart of a method for determining a virtual resource according to an exemplary embodiment.

[0052] Figure 3 The present invention is a flowchart showing the steps of generating at least one virtual resource parameter group according to an exemplary embodiment.

[0053] Figure 4 It is a block diagram of a device for determining a virtual resource according to an exemplary embodiment.

[0054] Figure 5 It is a block diagram of a server according to an exemplary embodiment. DETAILED DESCRIPTION

[0055] In order to enable ordinary persons in the art to better understand the technical solutions of the present disclosure, the technical solutions in the embodiments of the present disclosure will be clearly and completely described below in conjunction with the accompanying drawings.

[0056] It should be noted that the terms "first", "second", etc. in the specification and claims of the present disclosure and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments of the present disclosure described herein can be implemented in an order other than those illustrated or described herein. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with the present disclosure. Instead, they are merely examples of devices and methods consistent with some aspects of the present disclosure as detailed in the appended claims.

[0057] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data for display, data for analysis, etc.) involved in this disclosure are all information and data authorized by the user or fully authorized by all parties.

[0058] The virtual resource determination method provided in the present disclosure can be applied to Figure 1In the application environment shown. Among them, the terminal 110 interacts with the server 120 through the network, and the terminal 110 generates a virtual resource determination request in response to the user's operation and sends it to the server 120; the server 120 generates at least one virtual resource parameter group in response to the virtual resource determination request; the virtual resource parameter group includes multiple virtual resource parameters that meet the preset conditions; the server 120 inputs at least one virtual resource parameter group into a pre-built evaluation model to obtain a resource evaluation result output by the evaluation model for at least one virtual resource parameter group; the server 120 obtains a target virtual resource parameter group from multiple virtual resource parameter groups according to the resource evaluation result as a virtual resource determination result for the virtual resource determination request; the server 120 returns the virtual resource determination result to the terminal 110. Among them, the terminal 110 can be but not limited to various smart phones, tablet computers or laptops, etc., and the server 120 can be implemented by an independent server or a server cluster composed of multiple servers.

[0059] Figure 2 is a flowchart of a method for determining a virtual resource according to an exemplary embodiment. Figure 2 As shown, the virtual resource determination method is used in the server 120 and includes the following steps.

[0060] In step S210, in response to a virtual resource determination request, at least one virtual resource parameter group is generated; the virtual resource parameter group includes a plurality of virtual resource parameters that meet preset conditions.

[0061] Among them, virtual resources are virtual items that can reduce the resources paid when performing a certain behavior; the virtual resource parameter group is a combination of parameters used to define and limit the virtual resources; for example, the three parameters of pre-set user conversion rate, virtual resource effectiveness conditions, and the amount of virtual resources that can be adjusted can constitute a virtual resource parameter group; virtual resource parameters can also include parameters such as effective time, expiration time, and identification; preset conditions can correspond to multiple virtual resource parameters respectively, such as the value range of each virtual resource parameter, the size relationship between virtual resource parameters, etc.

[0062] Among them, the virtual resource determination request refers to a request instruction generated for a virtual resource parameter group, which may include restriction information for the generated virtual resource parameter group, and further includes restriction information for each virtual resource parameter in the virtual resource parameter group; to ensure that the generated virtual resource parameter group complies with the virtual resource determination request.

[0063] Specifically, the server receives a virtual resource determination request sent by the terminal, parses the virtual resource determination request, and determines the value range of each virtual resource parameter generated and restriction information such as additional conditions based on the virtual resource determination request; the server randomly generates each virtual resource parameter that meets the restriction information and forms a corresponding virtual resource parameter group.

[0064] In step S220, at least one virtual resource parameter group is input into a pre-built evaluation model to obtain a resource evaluation result output by the evaluation model for the at least one virtual resource parameter group.

[0065] The evaluation model is a model that can process the input virtual resource parameter group and obtain the corresponding resource evaluation result; the evaluation model includes multiple types, and different evaluation models will be obtained for calculation according to different virtual resource determination requests.

[0066] Specifically, the server inputs at least one virtual resource parameter group into a pre-built evaluation model, and the evaluation model outputs the results calculated for each virtual resource parameter group as a resource evaluation result; the resource evaluation result can be a numerical value, and the effect of the actual application of the virtual resource parameter group can be predicted or evaluated based on the size and positive or negative of the numerical value.

[0067] In step S230, according to the resource evaluation result, a target virtual resource parameter group is obtained from a plurality of virtual resource parameter groups as a virtual resource determination result for the virtual resource determination request.

[0068] Specifically, the server first determines whether each resource evaluation result meets the minimum standard as a virtual resource determination result, and then selects the virtual resource parameter group corresponding to the optimal resource evaluation result from the resource evaluation results that meet the minimum standard as the virtual resource determination result of the virtual resource determination request.

[0069] In the above-mentioned virtual resource determination method, at least one virtual resource parameter group is generated in response to a virtual resource determination request; the virtual resource parameter group includes multiple virtual resource parameters that meet preset conditions; then at least one virtual resource parameter group is input into a pre-constructed evaluation model to obtain a resource evaluation result output by the evaluation model for at least one virtual resource parameter group; then, based on the resource evaluation result, a target virtual resource parameter group is obtained from multiple virtual resource parameter groups as a virtual resource determination result for the virtual resource determination request; resource evaluation results of different virtual resource parameter groups are comprehensively considered, and the best virtual resource parameter group is determined from different virtual resource parameter groups as the virtual resource determination result; the inaccuracy of determining virtual resources based only on historical experience is avoided, thereby improving the effect of issuing virtual resources.

[0070] In an exemplary embodiment, the virtual resource parameter group includes a conversion parameter, a condition parameter, and an adjustment parameter;

[0071] like Figure 3 As shown, in step S210, the step of generating at least one virtual resource parameter group can be specifically implemented by the following steps:

[0072] In step S211, at least one conversion parameter within a first preset range and at least one resource parameter group within a second preset range are obtained; the resource parameter group includes a condition parameter and an adjustment parameter, and the adjustment parameter is less than or equal to the condition parameter.

[0073] Among them, conversion parameters, condition parameters and adjustment parameters are the three parameters required to constitute a virtual resource parameter group; condition parameters and adjustment parameters constitute a resource parameter group separately; condition parameters are the provisions of the applicable conditions for virtual resources, and resource parameters refer to the provisions of the specific numerical values ​​of virtual resources.

[0074] Among them, the conversion parameter is a target setting for the effect that the virtual resources to which the conditional parameters and adjustment parameters are applied can achieve. For example, if it is hoped that the proportion of participants can be increased by X% after a certain virtual resource is issued, then the "X%" parameter will be used as a conversion parameter and together with the conditional parameters and adjustment parameters will form a virtual resource parameter group.

[0075] The first preset range is a restriction condition on the value range of the conversion parameter; for example, if the conversion parameter is limited to a value between 1% and 10%, the first preset range is 0.01-0.1.

[0076] Among them, the second preset range is a restriction condition on the common value range of the conditional parameter and the adjustment parameter in the resource parameter group; for example, if the conditional parameter and the adjustment parameter are both limited to values ​​between 10 and 100, then the second preset range is 10-100; the adjustment parameter is less than or equal to the conditional parameter.

[0077] In step S212, at least one conversion parameter is combined with at least one resource parameter group to obtain at least one virtual resource parameter group.

[0078] Specifically, the conversion parameter and at least one resource parameter group can be randomly combined to obtain a virtual resource parameter group. For example, the generated conversion parameters are 1%, 2%, and 3% respectively; the resource parameter combinations including the condition parameter and the adjustment parameter are [99, 40] and [80, 60%] respectively; then the obtained virtual resource parameter group can be [1%, 99, 40] (conversion parameter is 1%, condition parameter is 99, adjustment parameter is 40, and so on), [2%, 99, 40], [3%, 99, 40], [1%, 80, 60%], [2%, 80, 60%], [3%, 80, 60%].

[0079] In the technical solution provided by the embodiment of the present disclosure, the conversion parameters and the resource parameter group including the conditional parameters and the adjustment parameters are respectively limited by the first preset range and the second preset range, thereby ensuring that the generated virtual resource parameters and the virtual resource parameter group meet the conditions of the virtual resource determination request; combining the conversion parameters with at least one resource parameter group can expand the number of virtual resource parameter groups, improve the comprehensiveness of the virtual resource parameter groups input into the evaluation model, and improve the accuracy of determining the effect of issuing virtual resources.

[0080] In an exemplary embodiment, in step S230, based on the resource evaluation results, a target virtual resource parameter group is obtained from multiple virtual resource parameter groups, which can be specifically achieved through the following steps: obtaining an evaluation value corresponding to each virtual resource parameter group from the resource evaluation results; obtaining a virtual resource parameter group whose evaluation value is greater than a preset threshold as the target virtual resource parameter group; and the preset threshold is determined based on the evaluation values ​​corresponding to each virtual resource parameter group.

[0081] Among them, the resource evaluation result is the result output by the evaluation model corresponding to one or more virtual resource parameter groups; the resource evaluation result is mainly characterized by the evaluation values ​​it contains; the preset threshold is a threshold parameter used to evaluate whether the evaluation value meets the conditions.

[0082] Among them, the preset threshold can be a fixed value. For example, if the evaluation values ​​corresponding to the virtual resource parameter group have both positive and negative values, the preset threshold can be determined as 0; the preset threshold can also be a dynamic value determined based on the evaluation values ​​corresponding to multiple virtual resource parameter groups, such as the value corresponding to the top 30% of all evaluation values ​​from large to small; in this way, the evaluation values ​​can be screened and the virtual resource parameter groups that meet the requirements can be selected.

[0083] The target virtual resource parameter group is a virtual resource parameter group selected from multiple virtual resource parameter groups and having an evaluation value greater than a preset threshold.

[0084] In the technical solution provided by the embodiment of the present disclosure, the evaluation value corresponding to each virtual resource parameter group is obtained from the resource evaluation result, and the target virtual resource parameter group is determined from the virtual resource parameter group using a preset threshold, thereby realizing the screening of multiple virtual resource parameter groups and the determination of the target virtual resource parameter group, thereby improving the efficiency of determining the target virtual resource parameter group.

[0085] In an exemplary embodiment, a virtual resource parameter group whose evaluation value is greater than a preset threshold is obtained as a target virtual resource parameter group. This can be specifically achieved through the following steps: if there are multiple virtual resource parameter groups whose evaluation values ​​are greater than the preset threshold, a virtual resource parameter group whose evaluation value is greater than the target preset threshold is obtained as the target virtual resource parameter group.

[0086] Specifically, if the evaluation values ​​of multiple virtual resource parameter groups are all greater than a preset threshold, the virtual resource parameter groups can be compared based on their specific values, and the virtual resource parameter group with the largest evaluation value can be used as the target virtual resource parameter group to determine the target virtual resource parameter group. Furthermore, the absolute values ​​of the evaluation values ​​of the virtual resource parameter groups can also be used for size comparison, which can be selected based on actual needs and the definition of the evaluation value.

[0087] In the technical solution provided by the embodiment of the present disclosure, by comparing the evaluation values ​​of multiple virtual resource parameter groups, a target virtual resource parameter group is determined from multiple virtual resource parameter groups that meet preset thresholds, thereby improving the efficiency and accuracy of determining the target virtual resource parameter group.

[0088] In an exemplary embodiment, in step S220, before inputting at least one virtual resource parameter group into a pre-built evaluation model, it also includes: obtaining historical data of virtual resources corresponding to the virtual resource determination request; determining evaluation parameters based on the historical data, and building an evaluation model based on the evaluation parameters.

[0089] Among them, historical data refers to the status record information generated after a certain type of virtual resource is issued; historical data may include information left when the status changes after issuance, and may also include information about virtual resources whose status has not changed after issuance but have exceeded a preset validity period. Historical data can also be obtained by testing a pre-set virtual account in a virtual scenario; that is, historical data can be a kind of historical test data. Among them, evaluation parameters refer to the parameter information used in the specific calculation process of the input virtual resource parameter group in the evaluation model; evaluation parameters can be obtained by fitting after multiple test processes using a pre-set test account or virtual account in a pre-built test environment or test scenario.

[0090] Specifically, the server determines the specific type or identification information of the virtual resource to be determined according to the virtual resource determination request; obtains historical data of matching historical virtual resources from a database according to the identification or type information; obtains evaluation parameters that can be used for evaluation by analyzing the historical data; and constructs a corresponding evaluation model according to the evaluation parameters.

[0091] In the technical solution provided by the embodiment of the present disclosure, historical data is used to obtain corresponding evaluation parameters, and the evaluation model established based on the historical data can evaluate virtual resources of the same or similar types, thereby improving the accuracy of the evaluation results output by the evaluation model.

[0092] In an exemplary embodiment, the historical data includes an account type identifier; determining the evaluation parameters based on the historical data can be specifically achieved through the following steps: obtaining target historical data within a preset time range with an account type identifier of a preset account type; analyzing preset indicators based on the target historical data to obtain the evaluation parameters.

[0093] Among them, the account type can be used to classify historical data; the preset time range can be used to obtain historical data generated within a certain time range; the preset indicators are used to determine specific evaluation parameters. The account type can also be the type corresponding to the test account specifically used in the test environment.

[0094] Specifically, the server determines the selection range of historical data through a preset time range, and selects historical data with an account type of the preset account type from the selection range to obtain target historical data, thereby completing the screening of historical data; and then analyzes the target historical data using predetermined preset indicators to obtain various evaluation parameters.

[0095] In the technical solution provided by the embodiment of the present disclosure, historical data of a preset account type is screened by a preset time range and an account type identifier to obtain target historical data; the evaluation parameters determined by the target historical data can more accurately calculate the input virtual resource parameter group, thereby improving the accuracy of the virtual resource determination result.

[0096] In an exemplary embodiment, before inputting at least one virtual resource parameter group into a pre-built evaluation model, it also includes: identifying the type of virtual resource to be determined in the virtual resource determination request; and obtaining an evaluation model matching the type from multiple evaluation models as a pre-built evaluation model.

[0097] The type of the virtual resource to be determined can be determined from the virtual resource determination request, and different types correspond to different evaluation methods, so there are multiple different evaluation models corresponding to the type of the virtual resource to be determined. The evaluation model is pre-constructed, so according to the type of the virtual resource to be determined in the virtual resource determination request, a matching evaluation model can be obtained as the pre-constructed evaluation model.

[0098] Specifically, a plurality of evaluation models are pre-built and stored in the server, and each evaluation model processes a different type of virtual resources; the server obtains the type of the virtual resource to be determined according to the virtual resource determination request; then, according to the type, an evaluation model matching the type is obtained from the plurality of evaluation models, and a pre-built evaluation model for processing the virtual resource parameter group is obtained.

[0099] In the technical solution provided by the embodiment of the present disclosure, by identifying the type of virtual resources to be determined and acquiring an evaluation model that matches the type from multiple evaluation models, accurate acquisition of the pre-built evaluation model is achieved to improve the accuracy of the resource evaluation results output by the virtual resource parameter group.

[0100] In an exemplary embodiment, a virtual resource determination method is provided.

[0101] One of the pre-built evaluation models can be expressed as follows, including:

[0102] G(A,a,X)

[0103] =N*X*[(Aa)+(num–1)*lost*g*(1-z)]

[0104] -(N*X*aN*X*lost*g*z)

[0105] -(N*x*aN*X*lost*z);

[0106] Where G is a pre-built evaluation model, (A, a, X) is a set of virtual resource parameters input to the evaluation model, where A is a condition parameter, a is an adjustment parameter, and X is a conversion parameter;

[0107] Among them, N is the number of objects of virtual resources issued; num is the number of state changes of the virtual resources of the object; lost is the state change loss after the virtual resources are issued; g is the adjustment coefficient for the object account type, which can be adjusted according to the operation of the evaluation model; z is the loss rate of each state change of virtual resources, which can be obtained by adjusting the ratio between the parameter and the total state change value of the virtual resource state change; x is the proportion of the state change value of virtual resources in all accounts that exceeds the condition parameter. The above parameters N, num, lost, g, z and x are evaluation parameters of the evaluation model, which can be obtained from the analysis results of historical data or based on test data.

[0108] It should be understood that although Figure 2-Figure 3The steps in the flowchart are shown in sequence as indicated by the arrows, but these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified in this document, there is no strict order restriction for the execution of these steps, and these steps can be executed in other orders. Moreover, Figure 2-Figure 3 At least part of the steps may include multiple steps or multiple stages. These steps or stages are not necessarily performed at the same time, but can be performed at different times. The execution order of these steps or stages is not necessarily sequential, but can be performed in turn or alternately with other steps or at least part of the steps or stages in other steps.

[0109] It can be understood that the same / similar parts between the various embodiments of the above method in this specification can refer to each other, and each embodiment focuses on the differences from other embodiments. For related points, please refer to the description of other method embodiments.

[0110] Figure 4 is a block diagram of a virtual resource determination device according to an exemplary embodiment. Figure 4 The device includes a parameter group generating unit 402, an evaluation result output unit 404 and a resource result determining unit 406.

[0111] The parameter group generating unit 402 is configured to generate at least one virtual resource parameter group in response to the virtual resource determination request; the virtual resource parameter group includes a plurality of virtual resource parameters that meet preset conditions;

[0112] The evaluation result output unit 404 is configured to input at least one virtual resource parameter group into a pre-built evaluation model to obtain a resource evaluation result output by the evaluation model for the at least one virtual resource parameter group;

[0113] The resource result determination unit 406 is configured to obtain a target virtual resource parameter group from a plurality of virtual resource parameter groups according to the resource evaluation result as a virtual resource determination result for the virtual resource determination request.

[0114] In an exemplary embodiment, the virtual resource parameter group includes a conversion parameter, a condition parameter, and an adjustment parameter;

[0115] The parameter group generation unit 402 is also configured to execute the acquisition of at least one conversion parameter within a first preset range and at least one resource parameter group within a second preset range; the resource parameter group includes a condition parameter and an adjustment parameter, and the adjustment parameter is less than or equal to the condition parameter; and at least one conversion parameter is combined with at least one resource parameter group to obtain at least one virtual resource parameter group.

[0116] In an exemplary embodiment, the resource result determination unit 406 is also configured to execute obtaining evaluation values ​​corresponding to each virtual resource parameter group from the resource evaluation results; obtaining a virtual resource parameter group whose evaluation value is greater than a preset threshold as a target virtual resource parameter group; and the preset threshold is determined according to the evaluation values ​​corresponding to each virtual resource parameter group.

[0117] In an exemplary embodiment, the resource result determination unit 406 is further configured to execute, if there are multiple virtual resource parameter groups whose evaluation values ​​are greater than a preset threshold, obtaining a virtual resource parameter group whose evaluation value is greater than a target preset threshold as a target virtual resource parameter group.

[0118] In an exemplary embodiment, the evaluation result output unit 404 is further configured to execute acquiring historical data of the virtual resource corresponding to the virtual resource determination request; determining evaluation parameters according to the historical data, and constructing an evaluation model according to the evaluation parameters.

[0119] In an exemplary embodiment, the historical data includes an account type identifier;

[0120] The evaluation result output unit 404 is further configured to obtain target historical data within a preset time range, with the account type identifier being a preset account type; and analyze the preset indicators according to the target historical data to obtain evaluation parameters.

[0121] In an exemplary embodiment, the evaluation result output unit 404 is further configured to identify the type of the virtual resource to be determined in the virtual resource determination request; and obtain an evaluation model matching the type from multiple evaluation models as a pre-built evaluation model.

[0122] Figure 5 is a block diagram of an electronic device 500 for determining virtual resources according to an exemplary embodiment. For example, the electronic device 500 may be a server. Figure 5 , the electronic device 500 includes a processing component 520, which further includes one or more processors, and a memory resource represented by a memory 522 for storing instructions that can be executed by the processing component 520, such as an application. The application stored in the memory 522 may include one or more modules, each corresponding to a set of instructions. In addition, the processing component 520 is configured to execute the instructions to perform the above method.

[0123] The electronic device 500 may further include a power supply component 524 configured to perform power management of the electronic device 500, a wired or wireless network interface 526 configured to connect the electronic device 500 to a network, and an input / output (I / O) interface 528. The electronic device 500 may operate based on an operating system stored in the memory 522, such as Windows Server, Mac OS X, Unix, Linux, FreeBSD, or the like.

[0124] In an exemplary embodiment, a computer-readable storage medium including instructions is also provided, such as a memory 522 including instructions, and the above instructions can be executed by a processor of the electronic device 500 to perform the above method. The storage medium can be a computer-readable storage medium, for example, a computer-readable storage medium can be a ROM, a random access memory (RAM), a CD-ROM, a magnetic tape, a floppy disk, an optical data storage device, etc.

[0125] In an exemplary embodiment, a computer program product is further provided. The computer program product includes instructions. The instructions can be executed by a processor of the electronic device 500 to complete the above method.

[0126] It should be noted that the above-mentioned devices, electronic devices, computer-readable storage media, computer program products, etc. may also include other implementation methods according to the description of the method embodiments. The specific implementation methods can refer to the description of the relevant method embodiments, which will not be described one by one here.

[0127] Those skilled in the art will readily appreciate other embodiments of the present disclosure after considering the specification and practicing the invention disclosed herein. The present disclosure is intended to cover any variations, uses or adaptations of the present disclosure that follow the general principles of the present disclosure and include common knowledge or customary techniques in the art that are not disclosed in the present disclosure. The description and examples are to be considered exemplary only, and the true scope and spirit of the present disclosure are indicated by the claims.

[0128] It should be understood that the present disclosure is not limited to the exact structures that have been described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present disclosure is limited only by the appended claims.

Claims

1. A method for determining virtual resources, characterized in that: include: In response to the virtual resource determination request, generating at least one virtual resource parameter group; the virtual resource parameter group includes a plurality of virtual resource parameters that meet preset conditions; The virtual resource parameters are parameters used to define and limit the virtual resources corresponding to the virtual resource determination request, including: conversion parameters, condition parameters and adjustment parameters; the virtual resources are virtual items used to reduce the resources paid for the preset behavior when performing the preset behavior; the condition parameters are used to specify the conditions that can be applied to the virtual resources, the adjustment parameters are used to specify the specific numerical values ​​of the virtual resources, and the conversion parameters are used to set the effects that can be played on the virtual resources to which the condition parameters and adjustment parameters are applied; Input at least one of the virtual resource parameter groups into a pre-constructed evaluation model to obtain a resource evaluation result output by the evaluation model for at least one of the virtual resource parameter groups; the evaluation model is constructed based on evaluation parameters; the evaluation parameters include: the number of objects to which the virtual resource is issued, the number of state changes of the virtual resource, the state change loss after the virtual resource is issued, the object account type adjustment coefficient of the object to which the virtual resource is issued, the state change loss rate of each virtual resource, and the proportion of the state change values ​​of the virtual resources in all accounts exceeding the condition parameter. According to the resource evaluation result, a target virtual resource parameter group is obtained from the multiple virtual resource parameter groups as a virtual resource determination result for the virtual resource determination request; the virtual resource determination result is used to indicate the release of virtual resources determined according to the target virtual resource parameter group.

2. The method for determining virtual resources according to claim 1, characterized in that: The generating at least one virtual resource parameter group comprises: Acquire at least one conversion parameter within a first preset range and at least one resource parameter group within a second preset range; the resource parameter group includes a condition parameter and an adjustment parameter, and the adjustment parameter is less than or equal to the condition parameter; The at least one conversion parameter is combined with the at least one resource parameter group to obtain the at least one virtual resource parameter group.

3. The method for determining virtual resources according to claim 1, characterized in that: The step of acquiring a target virtual resource parameter group from the plurality of virtual resource parameter groups according to the resource evaluation result comprises: Obtaining evaluation values ​​corresponding to each of the virtual resource parameter groups from the resource evaluation results; A virtual resource parameter group whose evaluation value is greater than a preset threshold is obtained as the target virtual resource parameter group; the preset threshold is determined according to the evaluation values ​​corresponding to each of the virtual resource parameter groups.

4. The method for determining virtual resources according to claim 3, characterized in that: The step of obtaining the virtual resource parameter group whose evaluation value is greater than a preset threshold as the target virtual resource parameter group includes: If there are multiple virtual resource parameter groups whose evaluation values ​​are greater than the preset threshold, a virtual resource parameter group whose evaluation value is greater than the target preset threshold is obtained as the target virtual resource parameter group.

5. The method for determining virtual resources according to claim 1, characterized in that: Before inputting at least one of the virtual resource parameter groups into a pre-built evaluation model, the method further includes: Acquire historical data of virtual resources corresponding to the virtual resource determination request; Evaluation parameters are determined according to the historical data, and the evaluation model is constructed according to the evaluation parameters.

6. The method for determining virtual resources according to claim 5, characterized in that: The historical data includes an account type identifier; Determining the evaluation parameters according to the historical data includes: Acquire target historical data within a preset time range, where the account type identifier is a preset account type; The preset indicators are processed according to the target historical data to obtain the evaluation parameters.

7. The method for determining virtual resources according to any one of claims 1 to 6, characterized in that: Before inputting at least one of the virtual resource parameter groups into a pre-built evaluation model, the method further includes: Identifying the type of virtual resource to be determined in the virtual resource determination request; From a plurality of evaluation models, an evaluation model matching the type is acquired as the pre-built evaluation model.

8. A virtual resource determination device, characterized in that: include: A parameter group generating unit is configured to generate at least one virtual resource parameter group in response to a virtual resource determination request; the virtual resource parameter group includes a plurality of virtual resource parameters that meet preset conditions; the virtual resource parameters are parameters used to define and limit the virtual resources corresponding to the virtual resource determination request, including: conversion parameters, condition parameters and adjustment parameters; the virtual resources are virtual items used to reduce the resources paid for the preset behavior when performing the preset behavior; the condition parameters are used to specify the conditions that can be applied to the virtual resources, the adjustment parameters are used to specify the specific numerical values ​​of the virtual resources, and the conversion parameters are used to set the effects that can be exerted on the virtual resources to which the condition parameters and adjustment parameters are applied; An evaluation result output unit is configured to execute inputting at least one of the virtual resource parameter groups into a pre-constructed evaluation model to obtain a resource evaluation result output by the evaluation model for at least one of the virtual resource parameter groups; the evaluation model is constructed based on evaluation parameters; the evaluation parameters include: the number of objects for issuing the virtual resource, the number of state changes of the virtual resource, the loss of state change after the virtual resource is issued, the object account type adjustment coefficient of the object for issuing the virtual resource, the loss rate of each state change of the virtual resource, and at least one of the proportions of the state change values ​​of the virtual resources in all accounts exceeding the conditional parameters; The resource result determination unit is configured to execute, based on the resource evaluation result, obtaining a target virtual resource parameter group from multiple virtual resource parameter groups as a virtual resource determination result for the virtual resource determination request; the virtual resource determination result is used to indicate the release of virtual resources determined according to the target virtual resource parameter group.

9. The virtual resource determination device according to claim 8, characterized in that: The parameter group generating unit is further configured to execute acquiring at least one conversion parameter within a first preset range and at least one resource parameter group within a second preset range; the resource parameter group includes a condition parameter and an adjustment parameter, and the adjustment parameter is less than or equal to the condition parameter; The at least one conversion parameter is combined with the at least one resource parameter group to obtain the at least one virtual resource parameter group.

10. The virtual resource determination device according to claim 8, characterized in that: The resource result determination unit is further configured to obtain evaluation values ​​corresponding to each of the virtual resource parameter groups from the resource evaluation results; obtain the virtual resource parameter group whose evaluation value is greater than a preset threshold as the target virtual resource parameter group; The preset threshold is determined according to the evaluation values ​​corresponding to each of the virtual resource parameter groups.

11. The virtual resource determination device according to claim 10, characterized in that: The resource result determination unit is further configured to execute, if there are multiple virtual resource parameter groups whose evaluation values ​​are greater than a preset threshold, obtaining a virtual resource parameter group whose evaluation value is greater than a target preset threshold as the target virtual resource parameter group.

12. The virtual resource determination device according to claim 8, characterized in that: The evaluation result output unit is further configured to execute acquisition of historical data of virtual resources corresponding to the virtual resource determination request; determine evaluation parameters according to the historical data, and construct the evaluation model according to the evaluation parameters.

13. The virtual resource determination device according to claim 12, characterized in that: The historical data includes an account type identifier; The evaluation result output unit is further configured to execute acquisition of target historical data within a preset time range, in which the account type identifier is a preset account type; and to analyze preset indicators according to the target historical data to obtain the evaluation parameters.

14. The virtual resource determination device according to any one of claims 8 to 13, characterized in that: The evaluation result output unit is further configured to identify the type of the virtual resource to be determined in the virtual resource determination request; and obtain an evaluation model matching the type from multiple evaluation models as the pre-built evaluation model.

15. A server, characterized in that: include: processor; a memory for storing instructions executable by the processor; The processor is configured to execute the instructions to implement the virtual resource determination method according to any one of claims 1 to 7.

16. A computer-readable storage medium, characterized in that: When the instructions in the computer-readable storage medium are executed by a processor of a server, the server is enabled to execute the virtual resource determination method according to any one of claims 1 to 7.

17. A computer program product, comprising instructions, characterized in that: When the instruction is executed by a processor of the server, the server is enabled to execute the virtual resource determination method according to any one of claims 1 to 7.

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